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At least 739 records · Page 41

V1309 Sco—understanding a merger

One of the two outcomes of a common envelope (CE) event is a merger of the two stars. To date, the best known case of a binary merger is the V1309 Sco outburst, where the orbital period was known and observed to decay up to the outburst. Using the hydrodynamical code StarSmasher, we study in detail which characteristics of the progenitor binary affect the outburst and produce the best match with observations. We have developed a set of tools in order to quantify any CE event. We consider binaries consisting of a 1.52 M {sub ☉} giant and a 0.16 M {sub ☉} companion with P {sub orb} ∼ 1.4 days, varying the nature of the companion and its synchronization. We show that all considered progenitor binaries evolve toward the merger primarily because of Darwin instability. The merger is accompanied by mass ejection that proceeds in several separate mass outbursts and takes away a few percent of the donor mass. This very small mass, nonetheless, is important as it is not only sufficient to explain the observed light curve, but it also carries away up to one-third of both the initial total angular momentum and initial orbital energy. We find that all synchronized systems experience L {sub 2} mass loss that operates during just a few days prior to the merger and produces ring-shaped ejecta. The formed star is always a strongly heated radiative star that differentially rotates. We conclude that the case of a synchronized binary with a main-sequence companion gives the best match with observations of V1309 Sco.

79 ASTRONOMY AND ASTROPHYSICS↗

Nitrogen addition alters soil fungal communities, but root fungal communities are resistant to change

Plants are colonized by numerous microorganisms serving important symbiotic functions that are vital to plant growth and success. Understanding and harnessing these interactions will be useful in both managed and natural ecosystems faced with global change, but it is still unclear how variation in environmental conditions and soils influence the trajectory of these interactions. In this study, we examine how nitrogen addition alters plant-fungal interactions within two species of Populus - Populus deltoides and P. trichocarpa. In this experiment, we manipulated plant host, starting soil (native vs. away for each tree species), and nitrogen addition in a fully factorial replicated design. After ~10 weeks of growth, we destructively harvested the plants and characterized plant growth factors and the soil and root endosphere fungal communities using targeted amplicon sequencing of the ITS2 gene region. Overall, we found nitrogen addition altered plant growth factors, e.g., plant height, chlorophyll density, and plant N content. Interestingly, nitrogen addition resulted in a lower fungal alpha diversity in soils but not plant roots. Further, there was an interactive effect of tree species, soil origin, and nitrogen addition on soil fungal community composition. Starting soils collected from Oregon and West Virginia were dominated by the ectomycorrhizal fungi Inocybe (55.8% relative abundance), but interestingly when P. deltoides was grown in its native West Virginia soil, the roots selected for a high abundance of the arbuscular mycorrhizal fungi, Rhizophagus. These results highlight the importance of soil origin and plant species on establishing plant-fungal interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Organic amendments change soil organic C structure and microbial community but not total organic matter on sub-decadal scales

Organic C has many benefits for soil, but it is depleted by tillage and crop harvest, and especially so for biofuel crops. Accordingly, strategies such as partially retaining stover or planting a cover crop can help ameliorate the negative effect of C removal. We used a long-term field experiment to study the impacts of stover retention and planting cover crop on soil organic matter (SOM), its extractable components and the soil microbial community. SOM chemical composition characterization was determined by electrospray ionization (ESI) coupled with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) in sequential water, methanol (MeOH), and chloroform (CHCl3) extracts. The characteristics of the soil bacterial community were measured by phospholipid fatty acid (PLFA), real-time quantitative PCR, and 16S rRNA gene sequence. The variations in total SOM content, total microbial biomass, and bacterial population were slight among treatments, but SOM chemical compounds, arbuscular mycorrhizal fungi (AMF) biomass, and bacterial structure changed significantly, and especially so in the coupled application of stover retention and cover crop. Specifically, stover retention enriched more lignin-like compounds in soil, whereas cover crop enriched more condensed hydrocarbons, and had more compounds with an aromaticity index (AI) >0.5. The bacterial community was not altered by the cover crop, but the corn stover retention increased the relative abundances of Myxococcales (Deltaproteobacteria) and decreased that of Actinobacteria. Redundancy analysis (RDA) further unveiled that the bacterial community in the stover treatments had significantly positive association with CHCl3-extracted chemical classes, i.e. unsaturated hydrocarbon and lipid with the coupled application (stover and cover crop), and lignin and protein with the single corn stover treatment. Taken together, our study shows how different C addition practices influence the molecular composition of SOM and the structure of soil microbial communities.

Xu, Jiangbin↗

Genomics and functional genomics in Chlamydomonas reinhardtii

The availability of the Chlamydomonas reinhardtii nuclear genome sequence continues to enable researchers to address biological questions relevant to algae, land plants and animals in unprecedented ways. As we continue to characterize and understand biological processes in C. reinhardtii and translate that knowledge to other systems, we are faced with the realization that many genes encode proteins without a defined function. The field of functional genomics aims to close this gap between genome sequence and protein function. Transcriptomes, proteomes and phenomes can each provide layers of gene-specific functional data while supplying a global snapshot of cellular behavior under different conditions. Herein we present a brief history of functional genomics, the present status of the C. reinhardtii genome, how genome-wide experiments can aid in supplying protein function inferences, and provide an outlook for functional genomics in C. reinhardtii.

59 BASIC BIOLOGICAL SCIENCES↗

Structural insights into plasmalemma vesicle-associated protein (PLVAP): Implications for vascular endothelial diaphragms and fenestrae

In many organs, small openings across capillary endothelial cells (ECs) allow the diffusion of low–molecular weight compounds and small proteins between the blood and tissue spaces. These openings contain a diaphragm composed of radially arranged fibers, and current evidence suggests that a single-span type II transmembrane protein, plasmalemma vesicle-associated protein-1 (PLVAP), constitutes these fibers. Here, we present the three-dimensional crystal structure of an 89-amino acid segment of the PLVAP extracellular domain (ECD) and show that it adopts a parallel dimeric alpha-helical coiled-coil configuration with five interchain disulfide bonds. The structure was solved using single-wavelength anomalous diffraction from sulfur-containing residues (sulfur SAD) to generate phase information. Biochemical and circular dichroism (CD) experiments show that a second PLVAP ECD segment also has a parallel dimeric alpha-helical configuration—presumably a coiled coil—held together with interchain disulfide bonds. Overall, ~2/3 of the ~390 amino acids within the PLVAP ECD adopt a helical configuration, as determined by CD. We also determined the sequence and epitope of MECA-32, an anti-PLVAP antibody. Taken together, these data lend strong support to the model of capillary diaphragms formulated by Tse and Stan in which approximately ten PLVAP dimers are arranged within each 60- to 80-nm-diameter opening like the spokes of a bicycle wheel. Passage of molecules through the wedge-shaped pores is presumably determined both by the length of PLVAP—i.e., the long dimension of the pore—and by the chemical properties of amino acid side chains and N-linked glycans on the solvent-accessible faces of PLVAP.

59 BASIC BIOLOGICAL SCIENCES↗

Identifying Potential Geochemical and Microbial Impacts of Hydrogen Storage in a Deep Saline Aquifer

Hydrogen is valuable commodity and a promising energy carrier for variable energy production. Storage of hydrogen may occur through injection of hydrogen or a hydrogen/methane gas blend in subsurface reservoirs. However, the geochemical and biological reactions that may impact the stored hydrogen are not yet understood. Therefore, we collected samples from a deep storage aquifer located in the St. Peter Formation in southern Illinois. The reservoir material was primarily quartz with sulphur and iron deposits, while the major constituents of the fluid were chloride and sulphate. 16S rRNA gene amplicon sequencing revealed a low biomass microbial community that contained no obvious hydrogen-consuming bacteria. Next, we enriched a field sample to increase the biomass and completed a metagenomic analysis, finding a low number of genes present that are associated with hydrogen consumption. Then, we completed a series of reactor experiments under reservoir conditions with 15% H2/85% CH4 gas simulating a short-term hydrogen storage, high withdrawal scenario. We found minimal changes in the geochemistry or microbiology for the reactor experiments. This work suggests that short-term storage may be highly successful, although significant additional work needs to be completed in order to accurately evaluate the risks associated with long-term hydrogen storage scenarios. It is essential we continue to expand our understanding of the dynamics present in saline aquifers and provide new insights into how hydrogen storage may impact underground geological storage environments.

54 ENVIRONMENTAL SCIENCES↗

Responses of vascular plant fine roots and associated microbial communities to whole-ecosystem warming and elevated CO 2 in northern peatlands

Warming and elevated CO 2 (eCO 2 ) are expected to facilitate vascular plant encroachment in peatlands. The rhizosphere, where microbial activity is fueled by root turnover and exudates, plays a crucial role in biogeochemical cycling, and will likely at least partially dictate the response of the belowground carbon cycle to climate changes. We leveraged the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment, to explore the effects of a whole-ecosystem warming gradient (+0°C to 9°C) and eCO 2 on vascular plant fine roots and their associated microbes. We combined trait-based approaches with the profiling of fungal and prokaryote communities in plant roots and rhizospheres, through amplicon sequencing. Warming promoted self-reliance for resource uptake in trees and shrubs, while saprophytic fungi and putative chemoorganoheterotrophic bacteria utilizing plant-derived carbon substrates were favored in the root zone. Conversely, eCO 2 promoted associations between trees and ectomycorrhizal fungi. Trees mostly associated with short-distance exploration-type fungi that preferentially use labile soil N. Additionally, eCO 2 decreased the relative abundance of saprotrophs in tree roots. Our results indicate that plant fine-root trait variation is a crucial mechanism through which vascular plants in peatlands respond to climate change via their influence on microbial communities that regulate biogeochemical cycles.

59 BASIC BIOLOGICAL SCIENCES↗

Converging towards atomic and nuclear pressures (Final Report)

his report details the development of transformational tools and techniques, allowing the accurate characterization of matter at the most extreme conditions yet studied in the high energy density (HED) domain. Before this work, most experiments quantitatively mapping the nature of matter in the HED realm were performed using planar geometry, which allows for the isolation and measurement of variables in a single thermodynamic state. Such measurements include equation of state variables, optical conductivity, heat transport and more. However, due to a variety of plasma processes, such experiments are limited to below ~10 TPa (100 Mbar) pressures. To achieve higher pressures, convergent experiments are needed. Historically, convergent experiments have not been used for benchmark data because they are integral measurements. That is each part of a convergent target undergoes a time dependent wide range of states, making it difficult to accurately isolate any particular quantity for a given thermodynamic state. This effort developed innovative convergent HED platforms and techniques enabling the exploration of matter from atomic to nuclear scale pressures. This effort also performed pioneering experiments that yielded the first rigorous benchmark data at these extreme conditions. This funding award began with the overarching goal to understand the behavior of matter at extreme (atomic-to-nuclear scale) pressures. The motivation for these goals lie in the fact that every time scientists explore matter beyond the threshold of an atomic unit, there is a fundamental shift in science. The atomic unit for energy, mass, charge, length, and time have each been explored, and each time such a threshold was crossed, a new sequence of discoveries was made resulting in significant awards such as the Nobel Prize. The only unexplored atomic unit is pressure, and this effort set the course for exploring matter at and beyond such pressures. That most of the recently discovered extrasolar planets and stars, as well as matter in the late implosion stages of inertial fusion targets, have deep internal pressures at and beyond atomic pressures amplifies the importance of this effort. Much of the initial work in developing techniques to create these atomic-to-nuclear pressures already existed within the HED community, predominantly at large scale laser facilities such as the National Ignition Facility (NIF) and the Omega60 laser the University of Rochester and although these experiments were routinely performed the ability to extract information about the underlying physical states and processes remained elusive due to the complexity of the experiments, extreme scales in both time and space, and the integrated nature of all the measurements. This work built a rigorous framework so such measurements can routinely be made. This was done in part through the introduction of Bayesian inference techniques into the field of HED science. These techniques allow for the self-consistent extraction of the relevant variables and their explicit and implicit correlations, so as to make use of integrated experimental data to constrain physical models and provide accurate uncertainty bounds for the data. The techniques developed here are fully transparent and proved immediately useful providing quantitative rigorous benchmarks for physical states and processes at some of the most extreme conditions yet explored on Earth. This funding is directly or partly responsible for 7 publications in major peer-reviewed scientific journals, a doctoral thesis, 3 invited talks at major conferences, and the training of a post-doc, 2 graduate students, and 1 undergraduate student. Beyond the effort supported by this award launched the introduction of Bayesian inference into the HED physics community and helped push the usage if modern data-science techniques within the physics community at large.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Metal-Free, Oxidative Condensation of Heteroaryl- and Aryl Carbaldehydes towards Functionalized Carbonitriles

Functionalization of pyridines with the carbonitrile group for advanced cyclization reactions routinely incorporates metals, toxic oxidants, and cyanide reagents, often in linear synthetic sequences. Here, motivated by the strategic need of a heteroaryl carbonitrile synthon for further elaboration, we disclose an efficient, metal-free, one-pot reaction sequence that uses ammonium acetate as the nitrogen source and bis-acetoxyiodobenzene as the oxidant with low loadings. The developed method tolerates a diverse substrate scope including heteroaryl, aryl, and alkyl substrates with similar efficiency and expands the practitioner's reaction. Method development, optimization, substrate scope, preliminary mechanistic observations, competition experiments, and a scale up reaction are delineated herein.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Weakly supervised classification of aortic valve malformations using unlabeled cardiac MRI sequences

Biomedical repositories such as the UK Biobank provide increasing access to prospectively collected cardiac imaging, however these data are unlabeled, which creates barriers to their use in supervised machine learning. We develop a weakly supervised deep learning model for classification of aortic valve malformations using up to 4,000 unlabeled cardiac MRI sequences. Instead of requiring highly curated training data, weak supervision relies on noisy heuristics defined by domain experts to programmatically generate large-scale, imperfect training labels. For aortic valve classification, models trained with imperfect labels substantially outperform a supervised model trained on hand-labeled MRIs. In an orthogonal validation experiment using health outcomes data, our model identifies individuals with a 1.8-fold increase in risk of a major adverse cardiac event. This work formalizes a deep learning baseline for aortic valve classification and outlines a general strategy for using weak supervision to train machine learning models using unlabeled medical images at scale.

60 APPLIED LIFE SCIENCES↗

MULTICOM2 open-source protein structure prediction system powered by deep learning and distance prediction

Protein structure prediction is an important problem in bioinformatics and has been studied for decades. However, there are still few open-source comprehensive protein structure prediction packages publicly available in the field. In this paper, we present our latest open-source protein tertiary structure prediction system—MULTICOM2, an integration of template-based modeling (TBM) and template-free modeling (FM) methods. The template-based modeling uses sequence alignment tools with deep multiple sequence alignments to search for structural templates, which are much faster and more accurate than MULTICOM1. The template-free (ab initio or de novo) modeling uses the inter-residue distances predicted by DeepDist to reconstruct tertiary structure models without using any known structure as template. In the blind CASP14 experiment, the average TM-score of the models predicted by our server predictor based on the MULTICOM2 system is 0.720 for 58 TBM (regular) domains and 0.514 for 38 FM and FM/TBM (hard) domains, indicating that MULTICOM2 is capable of predicting good tertiary structures across the board. It can predict the correct fold for 76 CASP14 domains (95% regular domains and 55% hard domains) if only one prediction is made for a domain. The success rate is increased to 3% for both regular and hard domains if five predictions are made per domain. Moreover, the prediction accuracy of the pure template-free structure modeling method on both TBM and FM targets is very close to the combination of template-based and template-free modeling methods. This demonstrates that the distance-based template-free modeling method powered by deep learning can largely replace the traditional template-based modeling method even on TBM targets that TBM methods used to dominate and therefore provides a uniform structure modeling approach to any protein. Finally, on the 38 CASP14 FM and FM/TBM hard domains, MULTICOM2 server predictors (MULTICOM-HYBRID, MULTICOM-DEEP, MULTICOM-DIST) were ranked among the top 20 automated server predictors in the CASP14 experiment. After combining multiple predictors from the same research group as one entry, MULTICOM-HYBRID was ranked no. 5. The source code of MULTICOM2 is freely available at https://github.com/multicom-toolbox/multicom/tree/multicom_v2.0 .

97 MATHEMATICS AND COMPUTING↗

Nonlinear force-free field modeling of the solar magnetic carpet and comparison with SDO/HMI and Sunrise/IMAX observations

In the quiet solar photosphere, the mixed polarity fields form a magnetic carpet that continuously evolves due to dynamical interaction between the convective motions and magnetic field. This interplay is a viable source to heat the solar atmosphere. In this work, we used the line-of-sight (LOS) magnetograms obtained from the Helioseismic and Magnetic Imager on the Solar Dynamics Observatory, and the Imaging Magnetograph eXperiment instrument on the Sunrise balloon-borne observatory, as time-dependent lower boundary conditions, to study the evolution of the coronal magnetic field. We use a magneto-frictional relaxation method, including hyperdiffusion, to produce a time series of three-dimensional nonlinear force-free fields from a sequence of photospheric LOS magnetograms. Vertical flows are added up to a height of 0.7 Mm in the modeling to simulate the non-force-freeness at the photosphere-chromosphere layers. Among the derived quantities, we study the spatial and temporal variations of the energy dissipation rate and energy flux. Our results show that the energy deposited in the solar atmosphere is concentrated within 2 Mm of the photosphere and there is not sufficient energy flux at the base of the corona to cover radiative and conductive losses. Possible reasons and implications are discussed. Better observational constraints of the magnetic field in the chromosphere are crucial to understand the role of the magnetic carpet in coronal heating.

79 ASTRONOMY AND ASTROPHYSICS↗

Alignment of the ATLAS Inner Detector in Run 2

The performance of the ATLAS Inner Detector alignment has been studied using pp collision data at s√=13TeV collected by the ATLAS experiment during Run 2 (2015–2018) of the Large Hadron Collider (LHC). The goal of the detector alignment is to determine the detector geometry as accurately as possible and correct for time-dependent movements. The Inner Detector alignment is based on the minimization of track-hit residuals in a sequence of hierarchical levels, from global mechanical assembly structures to local sensors. Subsequent levels have increasing numbers of degrees of freedom; in total there are almost 750,000. The alignment determines detector geometry on both short and long timescales, where short timescales describe movements within an LHC fill. The performance and possible track parameter biases originating from systematic detector deformations are evaluated. Momentum biases are studied using resonances decaying to muons or to electrons. The residual sagitta bias and momentum scale bias after alignment are reduced to less than ~0.1 TeV -1 and 0.9×10 -3 , respectively. Impact parameter biases are also evaluated using tracks within jets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Investigation of Yersinia pestis laboratory adaptation through a combined genomics and proteomics approach

Here, the bacterial pathogen Yersinia pestis , the cause of plague in humans and animals, normally has a sylvatic lifestyle, cycling between fleas and mammals. In contrast, laboratory-grown Y. pestis experiences a more constant environment and conditions that it would not normally encounter. The transition from the natural environment to the laboratory results in a vastly different set of selective pressures, and represents what could be considered domestication. Understanding the kinds of adaptations Y. pestis undergoes as it becomes domesticated will contribute to understanding the basic biology of this important pathogen. In this study, we performed a Parallel Serial Passage Experiment (PSPE) to explore the mechanisms by which Y. pestis adapts to laboratory conditions, hypothesizing that cells would undergo significant changes in virulence and nutrient acquisition systems. Two wild strains were serially passaged in 12 independent populations each for ~750 generations, after which each population was analyzed using whole-genome sequencing. We observed considerable parallel evolution in the endpoint populations, detecting multiple independent mutations in ail , pepA , and zwf , suggesting that specific selective pressures are shaping evolutionary responses. Complementary LC-MS-based proteomic data provide physiological context to the observed mutations, and reveal regulatory changes not necessarily associated with specific mutations, including changes in amino acid metabolism, envelope biogenesis, iron storage and acquisition, and a type VI secretion system. Proteomic data support hypotheses generated by genomic data in addition to suggesting future mechanistic studies, indicating that future whole-genome sequencing studies be designed to leverage proteomics as a critical complement.

59 BASIC BIOLOGICAL SCIENCES↗

Eu speciation in apatite at 1 bar: An experimental study of valence-state partitioning by XANES, lattice strain, and Eu/Eu* in basaltic systems

Abstract Partition coefficients for rare earth elements (REEs) between apatite and basaltic melt were determined as a function of oxygen fugacity (fO2; iron-wüstite to hematite-magnetite buffers) at 1 bar and between 1110 and 1175 °C. Apatite-melt partitioning data for REE3+ (La, Sm, Gd, Lu) show near constant values at all experimental conditions, while bulk Eu becomes more incompatible (with an increasing negative anomaly) with decreasing fO2. Experiments define three apatite calibrations that can theoretically be used as redox sensors. The first, a XANES calibration that directly measures Eu valence in apatite, requires saturation at similar temperature-composition conditions to experiments and is defined by: ( E u 3 + ∑ E u ) Apatite = 1 1 + 10 - 0.10 ± 0.01 × l o g ⁡ ( f o 2 ) - 1.63 ± 0.16 . The second technique involves analysis of Sm, Eu, and Gd in both apatite and coexisting basaltic melt (glass), and is defined by: ( Eu E u * ) D Sm × Gd = 1 1 + 10 - 0.15 ± 0.03 × l o g ⁡ ( f o 2 ) - 2.46 ± 0.41 . The third technique is based on the lattice strain model and also requires analysis of REE in both apatite and basalt. This calibration is defined by ( Eu E u * ) D lattice strain = 1 1 + 10 - 0.20 ± 0.03 × l o g ⁡ ( f o 2 ) - 3.03 ± 0.42 . The Eu valence-state partitioning techniques based on (Sm×Gd) and lattice strain are virtually indistinguishable, such that either methodology is valid. Application of any of these calibrations is best carried out in systems where both apatite and coexisting glass are present and in direct contact with one another. In holocrystalline rocks, whole rock analyses can be used as a guide to melt composition, but considerations and corrections must be made to either the lattice strain or Sm×Gd techniques to ensure that the effect of plagioclase crystallization either prior to or during apatite growth can be removed. Similarly, if the melt source has an inherited either a positive or negative Eu anomaly, appropriate corrections must also be made to lattice strain or Sm×Gd techniques that are based on whole rock analyses. This being the case, if apatite is primary and saturates from the parent melt early during the crystallization sequence, these corrections may be minimal. The partition coefficients for the REE between apatite and melt range from a maximum DEu3+ = 1.67 ± 0.25 (as determined by lattice strain) to DLu3+ = 0.69 ± 0.10. The REE partition coefficient pattern, as observed in the Onuma diagram, is in a fortuitous situation where the most compatible REE (Eu3+) is also the polyvalent element used to monitor fO2. These experiments provide a quantitative means of assessing Eu anomalies in apatite and how they be used to constrain the oxygen fugacity of silicate melts.

Geochemistry & Geophysics↗

Four-Dimensional Magnetic Resonance Imaging With 3-Dimensional Radial Sampling and Self-Gating–Based K-Space Sorting: Early Clinical Experience on Pancreatic Cancer Patients

Purpose: To apply a novel self-gating k-space sorted 4-dimensional MRI (SG-KS-4D-MRI) method to overcome limitations due to anisotropic resolution and rebinning artifacts and to monitor pancreatic tumor motion. Methods and Materials: Ten patients were imaged using 4D-CT, cine 2-dimensional MRI (2D-MRI), and the SG-KS-4D-MRI, which is a spoiled gradient recalled echo sequence with 3-dimensional radial-sampling k-space projections and 1-dimensional projection-based self-gating. Tumor volumes were defined on all phases in both 4D-MRI and 4D-CT and then compared. Results: An isotropic resolution of 1.56 mm was achieved in the SG-KS-4D-MRI images, which showed superior soft-tissue contrast to 4D-CT and appeared to be free of stitching artifacts. The tumor motion trajectory cross-correlations (mean ± SD) between SG-KS-4D-MRI and cine 2D-MRI in superior–inferior, anterior–posterior, and medial–lateral directions were 0.93 ± 0.03, 0.83 ± 0.10, and 0.74 ± 0.18, respectively. The tumor motion trajectories cross-correlations between SG-KS-4D-MRI and 4D-CT in superior–inferior, anterior–posterior, and medial–lateral directions were 0.91 ± 0.06, 0.72 ± 0.16, and 0.44 ± 0.24, respectively. The average standard deviation of gross tumor volume calculated from the 10 breathing phases was 0.81 cm{sup 3} and 1.02 cm{sup 3} for SG-KS-4D-MRI and 4D-CT, respectively (P=.012). Conclusions: A novel SG-KS-4D-MRI acquisition method capable of reconstructing rebinning artifact–free, high-resolution 4D-MRI images was used to quantify pancreas tumor motion. The resultant pancreatic tumor motion trajectories agreed well with 2D-cine-MRI and 4D-CT. The pancreatic tumor volumes shown in the different phases for the SG-KS-4D-MRI were statistically significantly more consistent than those in the 4D-CT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

How Good Is Your Location? Comparing and Understanding the Uncertainties in Location for the 1993 Rock Valley Sequence

Accurate event locations are important for many endeavors in seismology, and understanding the factors that contribute to uncertainties in those locations is complex. In this article, we present a case study that takes an in-depth look at the accuracy and precision possible for locating nine shallow earthquakes in the Rock Valley fault zone in southern Nevada. These events are targeted by the Rock Valley Direct Comparison phase of the Source Physics Experiment, as candidates for the colocation of a chemical explosion with an earthquake hypocenter to directly compare earthquake and explosion sources. For this comparison, it is necessary to determine earthquake hypocenters as accurately as possible so that different source types have nearly identical locations. Our investigations include uncertainty analysis from different sets of phase arrivals, stations, velocity models, and location algorithms. For a common set of phase arrivals and stations, we find that epicentral locations from different combinations of velocity models and algorithms are within 600 m of one another in most cases. Event depths exhibit greater uncertainties, but focusing on the S-P times at the nearest station allows for estimates within approximately 500 m.

58 GEOSCIENCES↗