55 research outputs found

    Transgenic miR156 Switchgrass in the Field: Growth, Recalcitrance and Rust Susceptibility

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    Sustainable utilization of lignocellulosic perennial grass feedstocks will be enabled by high biomass production and optimized cell wall chemistry for efficient conversion into biofuels. MicroRNAs are regulatory elements that modulate the expression of genes involved in various biological functions in plants, including growth and development. In greenhouse studies, overexpressing a microRNA (miR156) gene in switchgrass had dramatic effects on plant architecture and flowering, which appeared to be driven by transgene expression levels. Highexpressing lines were extremely dwarfed, whereas low and moderate-expressing lines had higher biomass yields, improved sugar release and delayed flowering. Four lines with moderate or low miR156 overexpression from the prior greenhouse study were selected for a field experiment to assess the relationship between miR156 expression and biomass production over three years. We also analysed important bioenergy feedstock traits such as flowering, disease resistance, cell wall chemistry and biofuel production. Phenotypes of the transgenic lines were inconsistent between the greenhouse and the field as well as among different field growing seasons. One low expressing transgenic line consistently produced more biomass (25%–56%) than the control across all three seasons, which translated to the production of 30% more biofuel per plant during the final season. The other three transgenic lines produced less biomass than the control by the final season, and the two lines with moderate expression levels also exhibited altered disease susceptibilities. Results of this study emphasize the importance of performing multiyear field studies for plants with altered regulatory transgenes that target plant growth and development

    138Ba(d,α)^{138}{\rm Ba}(d,\alpha) study of states in 136Cs^{136}{\rm Cs}: Implications for new physics searches with xenon detectors

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    We used the 138^{138}Ba(d,α)(d,\alpha) reaction to carry out an in-depth study of states in 136^{136}Cs, up to around 2.5~MeV. In this work, we place emphasis on hitherto unobserved states below the first 1+1^+ level, which are important in the context of solar neutrino and fermionic dark matter (FDM) detection in large-scale xenon experiments. We identify for the first time candidate metastable states in 136^{136}Cs, which would allow a real-time detection of solar neutrino and FDM events in xenon detectors, with high background suppression. Our results are also compared with shell-model calculations performed with three Hamiltonians that were previously used to evaluate the nuclear matrix element (NME) for 136^{136}Xe neutrinoless double beta decay. We find that one of these Hamiltonians, which also systematically underestimates the NME compared to the others, dramatically fails to describe the observed low-energy 136^{136}Cs spectrum, while the other two show reasonably good agreement

    Cross Sections of the 83Rb (p,γ)84Sr and 84Kr(p,γ)85Rb Reactions at Energies Characteristic of the Astrophysical γ Process

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    We have measured the cross section of the 83 Rb ( p , γ ) 84 Sr radiative capture reaction in inverse kinematics using a radioactive beam of 83 Rb at incident energies of 2.4 and 2.7 A MeV. Prior to the radioactive beam measurement, the 84 Kr ( p , γ ) 85 Rb radiative capture reaction was measured in inverse kinematics using a stable beam of 84 Kr at an incident energy of 2.7 A MeV. The effective relative kinetic energies of these measurements lie within the relevant energy window for the γ process in supernovae. The central values of the measured partial cross sections of both reactions were found to be 0.17 – 0.42 times the predictions of statistical model calculations. Assuming the predicted cross section at other energies is reduced by the same factor leads to a slightly higher calculated abundance of the p nucleus 84 Sr , caused by the reduced rate of the 84 Sr ( γ , p ) 83 Rb reaction derived from the present measurement

    First Evidence of Axial Shape Asymmetry and Configuration Coexistence in 74^{74}Zn: Suggestion for a Northern Extension of the N=40N=40 Island of Inversion

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    The excited states of N=44N=44 74^{74}Zn were investigated via γ\gamma-ray spectroscopy following 74^{74}Cu β\beta decay. By exploiting γ\gamma-γ\gamma angular correlation analysis, the 22+2_2^+, 31+3_1^+, 02+0_2^+ and 23+2_3^+ states in 74^{74}Zn were firmly established. The γ\gamma-ray branching and E2/M1E2/M1 mixing ratios for transitions de-exciting the 22+2_2^+, 31+3_1^+ and 23+2_3^+ states were measured, allowing for the extraction of relative B(E2)B(E2) values. In particular, the 23+→02+2_3^+ \to 0_2^+ and 23+→41+2_3^+ \to 4_1^+ transitions were observed for the first time. The results show excellent agreement with new microscopic large-scale shell-model calculations, and are discussed in terms of underlying shapes, as well as the role of neutron excitations across the N=40N=40 gap. Enhanced axial shape asymmetry (triaxiality) is suggested to characterize 74^{74}Zn in its ground state. Furthermore, an excited K=0K=0 band with a significantly larger softness in its shape is identified. A shore of the N=40N=40 ``island of inversion'' appears to manifest above Z=26Z=26, previously thought as its northern limit in the chart of the nuclides

    An integrated online radioassay data storage and analytics tool for nEXO

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    Large-scale low-background detectors are increasingly used in rare-event searches as experimental collaborations push for enhanced sensitivity. However, building such detectors, in practice, creates an abundance of radioassay data especially during the conceptual phase of an experiment when hundreds of materials are screened for radiopurity. A tool is needed to manage and make use of the radioassay screening data to quantitatively assess detector design options. We have developed a Materials Database Application for the nEXO experiment to serve this purpose. This paper describes this database, explains how it functions, and discusses how it streamlines the design of the experiment
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