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At least 937 records · Page 52

High-throughput characterization, correlation, and mapping of leaf photosynthetic and functional traits in the soybean ( Glycine max ) nested association mapping population

We report photosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.]. A challenge is that phenotyping photosynthetic traits by traditional approaches is slow and destructive. There is proof-of-concept for leaf hyperspectral reflectance as a rapid method to model photosynthetic traits. However, the crucial step of demonstrating that hyperspectral approaches can be used to advance understanding of the genetic architecture of photosynthetic traits is untested. To address this challenge, we used full-range (500–2,400 nm) leaf reflectance spectroscopy to build partial least squares regression models to estimate leaf traits, including the rate-limiting processes of photosynthesis, maximum Rubisco carboxylation rate, and maximum electron transport. In total, 11 models were produced from a diverse population of soybean sampled over multiple field seasons to estimate photosynthetic parameters, chlorophyll content, leaf carbon and leaf nitrogen percentage, and specific leaf area (with R 2 from 0.56 to 0.96 and root mean square error approximately <10% of the range of calibration data). We explore the utility of these models by applying them to the soybean nested association mapping population, which showed variability in photosynthetic and leaf traits. Genetic mapping provided insights into the underlying genetic architecture of photosynthetic traits and potential improvement in soybean. Notably, the maximum Rubisco carboxylation rate mapped to a region of chromosome 19 containing genes encoding multiple small subunits of Rubisco. We also mapped the maximum electron transport rate to a region of chromosome 10 containing a fructose 1,6-bisphosphatase gene, encoding an important enzyme in the regeneration of ribulose 1,5-bisphosphate and the sucrose biosynthetic pathway. The estimated rate-limiting steps of photosynthesis were low or negatively correlated with yield suggesting that these traits are not influenced by the same genetic mechanisms and are not limiting yield in the soybean NAM population. Leaf carbon percentage, leaf nitrogen percentage, and specific leaf area showed strong correlations with yield and may be of interest in breeding programs as a proxy for yield. This work is among the first to use hyperspectral reflectance to model and map the genetic architecture of the rate-limiting steps of photosynthesis.

54 ENVIRONMENTAL SCIENCES↗

A comparative analysis of the chemical compositions of Gaia-Enceladus/Sausage and Milky Way satellites using APOGEE

ABSTRACT We use data from the 17th data release of the Apache Point Observatory Galactic Evolution Experiment (APOGEE 2) to contrast the chemical composition of the recently discovered Gaia Enceladus/Sausage system (GE/S) to those of 10 Milky Way (MW) dwarf satellite galaxies: LMC, SMC, Boötes I, Carina, Draco, Fornax, Sagittarius, Sculptor, Sextans, and Ursa Minor. Our main focus is on the distributions of the stellar populations of those systems in the [Mg/Fe]–[Fe/H] and [Mg/Mn]–[Al/Fe] planes, which are commonly employed in the literature for chemical diagnosis and where dwarf galaxies can be distinguished from in situ populations. We show that, unlike MW satellites, a GE/S sample defined purely on the basis of orbital parameters falls almost entirely within the locus of ‘accreted’ stellar populations in chemical space, which is likely caused by an early quenching of star formation in GE/S. Due to a more protracted history of star formation, stars in the metal-rich end of the MW satellite populations are characterized by lower [Mg/Mn] than those of their GE/S counterparts. The chemical compositions of GE/S stars are consistent with a higher early star formation rate (SFR) than MW satellites of comparable and even higher mass, suggesting that star formation in the early universe was strongly influenced by other parameters in addition to mass. We find that the direction of the metallicity gradient in the [Mg/Mn]–[Al/Fe] plane of dwarf galaxies is an indicator of the early SFR of the system.

79 ASTRONOMY AND ASTROPHYSICS↗

Disorder broadening of even-denominator fractional quantum Hall states in the presence of a short-range alloy potential

We study energy gaps of the $\textit{ν}$ = 7/2 and $\textit{ν}$ = 5/2 fractional quantum Hall states in a series of two-dimensional electron gases containing alloy disorder. In this work we found that gaps at these two filling factors have the same suppression rate with alloy disorder. The dimensionless intrinsic gaps in our alloy samples obtained from the model proposed by Morf and d'Ambrumenil are consistent with numerical results, but are larger than those obtained from experiments on pristine samples published in the literature. The disorder broadening parameter has large uncertainties. However, a modified analysis relying on shared intrinsic gaps yields consistent results for both the $\textit{ν}$ = 5/2 and 7/2 fractional quantum Hall states and establishes a linear relationship between the disorder broadening parameter and alloy concentration. Furthermore, we find that we can separate contributions to the disorder broadening of the long-range and short-range scattering.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Cosmological inference from an emulator based halo model. II. Joint analysis of galaxy-galaxy weak lensing and galaxy clustering from HSC-Y1 and SDSS

Here, we present high-fidelity cosmology results from a blinded joint analysis of galaxy-galaxy weak lensing (ΔΣ) and projected galaxy clustering (w p ) measured from the Hyper Suprime-Cam Year-1 (HSC-Y1) data and spectroscopic Sloan Digital Sky Survey (SDSS) galaxy catalogs in the redshift range 0.15 < z < 0.7. We define luminosity-limited samples of SDSS galaxies to serve as the tracers of w p in three spectroscopic redshift bins, and as the lens samples for ΔΣ. For the ΔΣ measurements, we select a single sample of 4×10 6 source galaxies over 140 deg 2 from HSC-Y1 with photometric redshifts (photo z) greater than 0.75, enabling a better handle of photo- z errors by comparing the ΔΣ amplitudes for the three lens redshift bins. The deep, high-quality HSC-Y1 data enable significant detections of the ΔΣ signals, with integrated signal-to-noise ratio S/N ~ 15 in the range 3 ≤ R/[h –1 Mpc] ≤ 30 for the three lens samples, despite the small area coverage. For cosmological parameter inference, we use an input galaxy-halo connection model built on the dark emulator package (which uses an ensemble set of high-resolution N-body simulations and enables fast, accurate computation of the clustering observables) with a halo occupation distribution that includes nuisance parameters to marginalize over modeling uncertainties. We model the ΔΣ and wp measurements on scales from R≃3 and 2h –1 Mpc , respectively, up to 30 h –1 Mpc (therefore excluding the baryon acoustic oscillations information) assuming a flat Λ CDM cosmology, marginalizing over about 20 nuisance parameters and demonstrating the robustness of our results to them. With various tests using mock catalogs described in Miyatake et al. [preceding paper, Phys. Rev. D 106, 083519 (2022)], we show that any bias in the clustering amplitude S 8 ≡ σ 8 (Ω m /0.3) 0.5 due to uncertainties in the galaxy-halo connection is less than ~ 50 % of the statistical uncertainty of S 8 , unless the assembly biaseffect is unexpectedly large. Our best-fit models have S 8 = 0.795$_{-0.042}^{+0.049}$ (mode and 68% credible interval) for the flat Λ CDM model; we find tighter constraints on the quantity S 8 (α = 0.17)≡σ 8 (Ω m /0.3) 0.17 = 0.745$_{-0.031}^{+0.039}$.

79 ASTRONOMY AND ASTROPHYSICS↗

A modified Susceptible-Infected-Recovered model for observed under-reported incidence data

Fitting Susceptible-Infected-Recovered (SIR) models to incidence data is problematic when not all infected individuals are reported. Assuming an underlying SIR model with general but known distribution for the time to recovery, this paper derives the implied differential-integral equations for observed incidence data when a fixed fraction of newly infected individuals are not observed. The parameters of the resulting system of differential equations are identifiable. Using these differential equations, we develop a stochastic model for the conditional distribution of current disease incidence given the entire past history of reported cases. We estimate the model parameters using Bayesian Markov Chain Monte-Carlo sampling of the posterior distribution. We use our model to estimate the transmission rate and fraction of asymptomatic individuals for the current Coronavirus 2019 outbreak in eight American Countries: the United States of America, Brazil, Mexico, Argentina, Chile, Colombia, Peru, and Panama, from January 2020 to May 2021. Our analysis reveals that the fraction of reported cases varies across all countries. For example, the reported incidence fraction for the United States of America varies from 0.3 to 0.6, while for Brazil it varies from 0.2 to 0.4.

60 APPLIED LIFE SCIENCES↗

Electron Linear Accelerator Additive Manufacturing

Superconducting electron linear accelerators open up new opportunities for advanced materials processing. High energy electrons penetrate deeper within materials, increase the processing depth and rate and enables production of far-from-equilibrium materials and selective processing within a material surface and subsurface. With support from the Office of Naval Research, NASA, and DoE, Mainstream Engineering commissioned a superconducting linear electron accelerator to investigate advanced materials processing and additive manufacturing. The goal of Mainstream's Electron Beam Enabled Advanced Manufacturing (EBEAM) center is to develop unique, far-from-equilibrium materials and alleviate significant technological deficiencies. We will present results of irradiating various metals and their unique material properties. Monte Carlo simulations electron beam and sample interaction were used to optimize the processing parameters and study far-from-equilibrium processing conditions. Applications include stainless steel additive manufacturing for small modular nuclear reactors and dissimilar metal bonding of corrosion-resistant cladding for next-generation molten salt reactors.

36 MATERIALS SCIENCE↗

Deeply Rooted: Evaluating Plant Rooting Depth as a Means for Enhanced Soil Carbon Sequestration (Full Technical Report)

Soils store three times as much carbon (C) as the atmosphere, but are not at capacity, and enhanced soil C storage is considered an essential strategy to mitigate rising atmospheric CO 2 levels. Agricultural soils have experienced substantial C loss in the past century due to poor agricultural practices and erosion. A shift towards deep-rooting crops and low-impact soil management could potentially increase long-term sequestration of C fixed by plants and stored in their root tissues, particularly for crops that have naturally deep root systems (>1 meter). A substantial amount of the CO 2 taken up by plants is allocated to their root systems, and because C deposited in deep soil layers has a longer residence time (up to millennia, in contrast to C deposited in topsoils), C increases at depth may have better long-term C sequestration potential than topsoils. However, the accrual, turnover, and stabilization of C in subsoils is a critical knowledge gap. We investigated a deeply rooted plant, switchgrass (Panicum virgatum), as a means of increasing carbon stocks in marginal and agricultural soils. We hypothesized that deep (>30 cm) SOC stocks would be greater under bioenergy crops relative to stocks under shallow-rooted conventional crop cover. To test this hypothesis, we compared soil depth profiles beneath deeply rooted switchgrass (cultivated for 4-30 years) and paired shallowrooted annual controls. We studied 12 field sites, 3 that were collected in 2018 before the start of the project as part a Department of Energy (DOE) Sustainable Biofuels study, and 9 that we collected in 2019 on a national field sampling campaign across the eastern US. In our publication from the 2018 study, which was written in collaboration with the LLNL Soil Microbiome Scientific Focus Area (SFA), we found that C stocks increased under switchgrass, but that the increases were dependent on soil texture. In the 2019 study, we found that carbon accrual tended to occur most consistently in low C soil in the southern US, which could indicate that perennial grasses may be a viable strategy to increase SOC in marginals soils in this region. We have published two studies from the 2019 sampling campaign thus far, we measured microbial growth parameters that will aid in modeling subsoil carbon cycling, and we found that switchgrass appears to move water upward in the soil profile and could promote drought tolerance, which a phenomenon commonly performed by trees known as ‘hydraulic redistribution;’ our study is the first to show this can occur in deep-rooted grasses. Finally, we published a modeling paper in collaboration with the LLNL Soil Microbiome SFA, where we found that poorly crystalline minerals are abundant and strongly correlated with organic C in geographically limited zones with enhanced weathering rates. Our results will inform technological development in the agricultural carbon sequestration sector as well as future negative emissions policies.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Short-Depth QAOA circuits and Quantum Annealing on Higher-Order Ising Models (Rev.2)

The Quantum Alternating Operator Ansatz (QAOA) and Quantum Annealing (QA) are quantum algorithms that are both based on the adiabatic theorem and both have the goal of sampling the optimal solution(s) of combinatorial optimization problems. Quantum annealing has been physically instantiated on D-Wave devices using superconducting flux qubits, and QAOA can be programmed on digital gate-model quantum computers such as the programmable superconducting transmon qubits devices of the IBMQ series, for instance ibm washington. QAOA and QA address the same types of problems, but it is unclear how they will scale to large problem sizes and to larger and higher-fidelity quantum computers. In this article, we present a direct comparison between QAOA, one and two rounds, run on all 127 qubits of ibm washington and QA run on D-Wave Advantage system4.1 and Advantage system6.1. The problems which allow for this comparison are random Ising model problems whose connectivity matches the heavy hexagonal lattice topology of ibm washington and the Pegasus graph connectivity of the two D-Wave devices. We create two classes of problem instances for this comparison: one with higher order terms (ZZZ variable interactions), linear terms, and quadratic terms, and a separate problem type with only linear and quadratic terms. Our QAOA circuits are novel and extremely short depth, with a CNOT depth of 6 per round, which allows whole chip usage of ibm washington’s heavy hexagonal lattice and can be applied to future heavy-hex chips. We also test the effectiveness of the error suppression technique digital dynamical decoupling on the QAOA circuits. The QAOA circuits compiled to ibm washington are composed of several thousand circuit instructions, approximately 3, 000 depending on the details of the circuit, making these some the largest quantum circuits ever executed on a digital quantum processor. QAOA and QA are compared against the classical heuristic algorithm of simulated annealing and all problem instances are exactly solved using CPLEX in order to evaluate which samplers, if any, correctly found the ground state solution(s) of the problem instances. We find that (i) QA outperforms QAOA on all problem instances, (ii) QAOA samples the problems better than random sampling, and (iii) QAOA angle computation exhibits clear parameter concentration across the ensemble of Ising models.

127 Qubits↗

Circular Perspective for Utilization of Industrial Wastewaters via Phytoremediation

Wastewater generated in municipal rendering facilities requires multi-step treatment, but it may also serve as a source of nutrients and water and thus may be valorized before or instead of the necessary wastewater treatment operations. In this work, wastewaters from a composting plant were utilized to support the growth of Miscanthus x giganteus, known as both a remediation plant and an energy biomass source. A pot experiment was established to compare the effects of different wastewater doses (0, 50, 100, and 200 mL per pot per week) on the miscanthus biomass yield, phytoextraction of heavy metals, biomass heat of combustion, and plant condition. The increase in the wastewater dose resulted in increases in both biomass yield (from about 44 to 139%) and biomass heat of combustion (from 7 to 17%) when compared to the control sample, with no adverse effects on plant physiological parameters. The highest concentrations of metals were found in miscanthus grown with the highest dose of wastewaters. It was found that higher wastewater dose correlates to both higher phytoextraction and phytorecovery of metals from plant substrate and wastewaters. The highest metal uptake was identified for Fe (431 mg·pot −1 ), followed by Al, Zn, Mn, Cu, Ni, Cr. The lowest metal uptake was noted for Pb, Co and Cd (0.88, 0.11, and 0.95 mg·pot −1 , respectively). The results indicate that miscanthus can be recommended for industrial wastewater treatment. In addition, due to high absorption efficiency of the substrate components, miscanthus can be used as a remediation tool, e.g., for the ecological stabilization of remediation of metal-polluted soils, especially in municipal facilities like rendering plants. This presents a circular perspective for the valorization of post-fermentation wastewaters with subsequent growth of energy crops, with other potential benefits for the environment, such as soil treatment, absorption of CO 2 , and air purification.

Miscanthus x giganteus↗

A method for the measurement and analysis of ride vibrations of transportation systems

The measurement and recording of ride vibrations which affect passenger comfort in transportation systems and the subsequent data-reduction methods necessary for interpreting the data present exceptional instrumentation requirements and necessitate the use of computers for specialized analysis techniques. A method is presented for both measuring and analyzing ride vibrations of the type encountered in ground and air transportation systems. A portable system for measuring and recording low-frequency, low-amplitude accelerations and specialized data-reduction procedures are described. Sample vibration measurements in the form of statistical parameters representative of typical transportation systems are also presented to demonstrate the utility of the techniques.

Catherines, J. J.↗

Testing relativistic gravity theories using radio tracking data from planetary orbiting spacecraft.

We present a thorough analysis of a computational method for determining the numerical values of the relativity and other related dynamical parameters using two-way Doppler and ranging data from planetary orbiting spacecraft. The computational method consists of two parts. From Doppler data we first determine the earth-planet components of the position of the orbiting spacecraft relative to the center of gravity of the planet to high accuracy; adding the observed spacecraft range yields a range value to the center of the planet. These constructed earth-planet range data, referred to as normal points, are then treated as raw data in a regression analysis combined with planetary radar delay and meridian circle measurements to solve for the significant solar system dynamical parameters. The major errors sources in the planetary orbiter process are enumerated and their individual effects on the overall accuracy of the normal point accuracies are presented. The accuracies of the parameter estimates as a function of time, data sampling, and a priori assumptions are illustrated.

Jordan, J. F.↗

Survey of lunar carbon compounds. II - The carbon chemistry of Apollo 11, 12, 14, and 15 samples.

The methane and carbide concentrations of a number of Apollo 11, 12, 14, and 15 samples of fines and breccias have been examined by the deuterated acid dissolution method. Location studies indicate that these carbon compounds are concentrated in the outer surfaces of the fines particles of 48-152 micron diameter; for larger particles a volume-related component may contribute. In individual samples the methane and carbide concentrations correlate with parameters indicative of lunar surface exposure. The data provide further evidence that solar wind implantation is the major source of the methane in the fines and that the carbide originates from both solar wind implantation and meteorite impacts.

Cadogan, P. H.↗

A self-documenting source-independent data format for computer processing of tensor time series

The UCLA Space Science Group has developed a fixed format intermediate data set called a block data set, which is designed to hold multiple segments of multicomponent sampled data series. The format is sufficiently general so that tensor functions of one or more independent variables can be stored in the form of virtual data. This makes it possible for the unit data records of the block data set to be arrays of a single dependent variable rather than discrete samples. The format is self-documenting with parameter, label and header records completely characterizing the contents of the file. The block data set has been applied to the filing of satellite data (of ATS-6 among others).

Mcpherron, R. L.↗

A satellite digital controller or 'play that PID tune again, Sam'

The problem discussed is to design a digital controller for a typical satellite. The controlled plant is considered to be a rigid body acting in a plane. The controller is assumed to be a digital computer which, when combined with the proposed control algorithm, can be represented as a sampled-data system. The objective is to present a design strategy and technique for selecting numerical values for the control gains (assuming position, integral, and derivative feedback) and the sample rate. The technique is based on the parameter plane method and requires that the system be amenable to z-transform analysis.

Seltzer, S. M.↗

Experimental simulation of space plasma interactions with high voltage solar arrays

Operating high voltage solar arrays in the space environment can result in anomalously large currents being collected through small insulation defects. Tests of simulated defects have been conducted in a 45-cm vacuum chamber with plasma densities of 100,000 to 1,000,000/cu cm. Plasmas were generated using an argon hollow cathode. The solar array elements were simulated by placing a thin sheet of polyimide (Kapton) insulation with a small hole in it over a conductor. Parameters tested were: hole size, adhesive, surface roughening, sample temperature, insulator thickness, insulator area. These results are discussed along with some preliminary empirical correlations.

Stillwell, R. P.↗