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At least 1,117 records · Page 62

Towards optimized viral metagenomes for double-stranded and single-stranded DNA viruses from challenging soils

Soils impact global carbon cycling and their resident microbes are critical to their biogeochemical processing and ecosystem outputs. Based on studies in marine systems, viruses infecting soil microbes likely modulate host activities via mortality, horizontal gene transfer, and metabolic control. However, their roles remain largely unexplored due to technical challenges with separating, isolating, and extracting DNA from viruses in soils. Some of these challenges have been overcome by using whole genome amplification methods and while these have allowed insights into the identities of soil viruses and their genomes, their inherit biases have prevented meaningful ecological interpretations. Here we experimentally optimized steps for generating quantitatively-amplified viral metagenomes to better capture both ssDNA and dsDNA viruses across three distinct soil habitats along a permafrost thaw gradient. First, we assessed differing DNA extraction methods (PowerSoil, Wizard mini columns, and cetyl trimethylammonium bromide) for quantity and quality of viral DNA. This established PowerSoil as best for yield and quality of DNA from our samples, though ∼1/3 of the viral populations captured by each extraction kit were unique, suggesting appreciable differential biases among DNA extraction kits. Second, we evaluated the impact of purifying viral particles after resuspension (by cesium chloride gradients; CsCl) and of viral lysis method (heat vs bead-beating) on the resultant viromes. DNA yields after CsCl particle-purification were largely non-detectable, while unpurified samples yielded 1–2-fold more DNA after lysis by heat than by bead-beating. Virome quality was assessed by the number and size of metagenome-assembled viral contigs, which showed no increase after CsCl-purification, but did from heat lysis relative to bead-beating. We also evaluated sample preparation protocols for ssDNA virus recovery. In both CsCl-purified and non-purified samples, ssDNA viruses were successfully recovered by using the Accel-NGS 1S Plus Library Kit. While ssDNA viruses were identified in all three soil types, none were identified in the samples that used bead-beating, suggesting this lysis method may impact recovery. Further, 13 ssDNA vOTUs were identified compared to 582 dsDNA vOTUs, and the ssDNA vOTUs only accounted for ∼4% of the assembled reads, implying dsDNA viruses were dominant in these samples. This optimized approach was combined with the previously published viral resuspension protocol into a sample-to-virome protocol for soils now available at protocols.io , where community feedback creates ‘living’ protocols. This collective approach will be particularly valuable given the high physicochemical variability of soils, which will may require considerable soil type-specific optimization. This optimized protocol provides a starting place for developing quantitatively-amplified viromic datasets and will help enable viral ecogenomic studies on organic-rich soils.

dsDNA viruses↗

Depth‐dependent concentrations of hematopoietic stem cells in the adult skeleton: Implications for active marrow dosimetry

Purpose The hematopoietically active (or red) bone marrow is the target tissue assigned in skeletal dosimetry models for assessment of stochastic effects (leukemia induction) as well as tissue reactions (marrow toxicity). Active marrow, however, is in reality a surrogate tissue region for specific cell populations, namely the hematopoietic stem and progenitor cells. Present models of active marrow dosimetry implicitly assume that these cells are uniformly localized throughout the marrow spaces of trabecular spongiosa. Data from Watchman et al. and Bourke et al., however, clearly indicate that there is a substantial spatial concentration gradient of these cells with the highest concentrations localized near the bone trabeculae surfaces. The purpose of the present study was thus to explore the dosimetric implications of these spatial gradients on active marrow dosimetry. Methods Images of several bone sites from a 45‐yr female were retagged to group active marrow voxels into 50 μm increments of marrow depth, after which electron and alpha‐particle depth‐dependent specific absorbed fractions were computed for four source tissues — active marrow, inactive marrow, bone trabeculae volumes, and bone trabeculae surfaces. Corresponding depth‐dependent S values (dose to a target tissue per decay in a source tissue) were computed and further weighted by the relative target cell concentration. These depth‐weighted radionuclide S values were systematically compared to the more traditional volume‐averaged radionuclide S values of the MIRD schema for both individual bones of the skeleton and their skeletal‐averaged quantities. Results For both beta‐emitters and alpha‐emitters localized in the active and inactive marrow, depth‐weighted S values were shown to differ from volume‐averaged S values by only a few percent, as dose gradients across the marrow tissues are nonexistent. For bone volume and bone surface sources of alpha‐emitters and lower energy beta‐emitters, when marrow dose gradients are expected, explicit consideration of target cell spatial concentration gradients are shown to significantly impact marrow dosimetry. Conclusions For medical isotopes currently utilized for treatment of skeletal metastases, namely 153 Sm and 223 Ra, accounting for hematopoietic stem and progenitor cell concentration gradients resulted in maximum percent differences to reference skeletal‐averaged S values of ~21% and 55%, respectively.

Geyer, Amy M.↗

SU-E-J-275: Review - Computerized PET/CT Image Analysis in the Evaluation of Tumor Response to Therapy

Purpose: To review the literature in using computerized PET/CT image analysis for the evaluation of tumor response to therapy. Methods: We reviewed and summarized more than 100 papers that used computerized image analysis techniques for the evaluation of tumor response with PET/CT. This review mainly covered four aspects: image registration, tumor segmentation, image feature extraction, and response evaluation. Results: Although rigid image registration is straightforward, it has been shown to achieve good alignment between baseline and evaluation scans. Deformable image registration has been shown to improve the alignment when complex deformable distortions occur due to tumor shrinkage, weight loss or gain, and motion. Many semi-automatic tumor segmentation methods have been developed on PET. A comparative study revealed benefits of high levels of user interaction with simultaneous visualization of CT images and PET gradients. On CT, semi-automatic methods have been developed for only tumors that show marked difference in CT attenuation between the tumor and the surrounding normal tissues. Quite a few multi-modality segmentation methods have been shown to improve accuracy compared to single-modality algorithms. Advanced PET image features considering spatial information, such as tumor volume, tumor shape, total glycolytic volume, histogram distance, and texture features have been found more informative than the traditional SUVmax for the prediction of tumor response. Advanced CT features, including volumetric, attenuation, morphologic, structure, and texture descriptors, have also been found advantage over the traditional RECIST and WHO criteria in certain tumor types. Predictive models based on machine learning technique have been constructed for correlating selected image features to response. These models showed improved performance compared to current methods using cutoff value of a single measurement for tumor response. Conclusion: This review showed that computerized PET/CT image analysis holds great potential to improve the accuracy in evaluation of tumor response. This work was supported in part by the National Cancer Institute Grant R01CA172638.

60 APPLIED LIFE SCIENCES↗

Control theory based airfoil design for potential flow and a finite volume discretization

This paper describes the implementation of optimization techniques based on control theory for airfoil design. In previous studies it was shown that control theory could be used to devise an effective optimization procedure for two-dimensional profiles in which the shape is determined by a conformal transformation from a unit circle, and the control is the mapping function. The goal of our present work is to develop a method which does not depend on conformal mapping, so that it can be extended to treat three-dimensional problems. Therefore, we have developed a method which can address arbitrary geometric shapes through the use of a finite volume method to discretize the potential flow equation. Here the control law serves to provide computationally inexpensive gradient information to a standard numerical optimization method. Results are presented, where both target speed distributions and minimum drag are used as objective functions.

Reuther, J.↗

A Variational Method for Interpolation Between Zone Centers in 2-D Geometry

Radiation-hydrodynamics codes are often based on a zone centered discretization strategy for the hydrodynamics, while transport requires a higher order interpolated treatment of the material state variable to produce a correct solution in optically thick media. In this paper, we use a variational method to generalize a previously developed 1-D interpolation method to 2-D geometries. While our interpolation method was developed to handle the gradient source term for thermal photons in the Difference Formulation, it may also be useful for the generation of an accurate zone centered discretization for diffusion methods. We provide a detailed description of the 2-D interpolation method and how it relates to the 1-D method that was developed earlier. We also discuss how this interpolation strategy can be extended to 3-D, but do not work through the details.

97 MATHEMATICS AND COMPUTING↗

Exploring the posterior surface of the large scale structure reconstruction

The large scale structure (LSS) of the universe is generated by the linear density gaussian modes, which are evolved into the observed nonlinear LSS. Given a set of data the posterior surface of the modes is convex in the linear regime, leading to a unique global maximum (MAP), but this is no longer guaranteed in the nonlinear regime. In this paper we investigate the nature of posterior surface using the recently developed MAP reconstruction method, with a simplified but realistic N-body simulation as the forward model. The reconstruction method uses optimization with analytic gradients from back-propagation through the simulation. For low noise cases we recover the initial conditions well into the nonlinear regime (k~ 1 h/Mpc) nearly perfectly. We show that the large scale modes can be recovered more precisely than the linear expectation, which we argue is a consequence of nonlinear mode coupling. For noise levels achievable with current and planned LSS surveys the reconstruction cannot recover very small scales due to noise. We see some evidence of non-convexity, specially for smaller scales where the non-injective nature of the mappings: several very different initial conditions leading to the same near perfect final data reconstruction. We investigate the nature of these phenomena further using a 1-d toy gravity model, where many well separated local maximas are found to have identical data likelihood but differ in the prior. We also show that in 1-d the prior favors some solutions over the true solution, though no clear evidence of these in 3-d. Our main conclusion is that on very small scales and for a very low noise the posterior surface is multi-modal and the global maximum may be unreachable with standard methods, while for realistic noise levels in the context of the current and next generation LSS surveys MAP optimization method is likely to be nearly optimal.

79 ASTRONOMY AND ASTROPHYSICS↗

Gradient-Based Optimization of the Common Research Model Wing Subject to CFD-Based Gust and Flutter Constraints

The linearized frequency-domain method was recently implemented in the stabilized finite element solver in NASA’s FUN3D code. Previous work by the authors used this method for enforcing flutter constraints during gradient-based optimizations. More recently, the solver was expanded to account for continuous (also known as stochastic) gust responses. This paper expands on recent Common Research Model wing optimization work, which demonstrated gradient-based optimization with flutter and stochastic gust constraints, among others. While that work utilized FUN3D for static aeroelastic solutions but relied on doublet lattice aerodynamics for gust and flutter responses, the present work replaces these unsteady aerodynamic analyses with those of FUN3D’s linearized frequency-domain solver. With analytic derivatives available, gradient-based optimization is performed through the use of the OpenMDAO/MPhys libraries with over 700 shape, structural, and aerodynamic design variables and over 10 nonlinear constraints. Comparisons of analysis results and optimized designs are made between doublet lattice and linearized frequency-domain solutions.

aeroelasticity↗

Density Functional Theory Study on Electronic Structures and Magnetism for Nitrogen-Doped ZnS

Using the full-potential linearized augmented plane wave method, together with the generalized gradient approximation and modified Becke-Johnson as correlation potential, the electronic structures and magnetism for nitrogen-doped ZnS are investigated. Based on the generalized gradient approximation, calculations show nitrogen-substituting sulfur (N{sub S}) would induce the ZnS to be paramagnetic metal. As the band gap increasing to the experimental results (obtained by the modified Becke-Johnson potential), the N{sub S} defects would induce the ZnS to be a ferromagnetic metal. The total magnetic moment for ZnS supercell with single N{sub S} defect is 0.85 μ{sub B}. Positive chemical pair interactions imply that N{sub S} defects would form homogeneous distribution in ZnS host. Sulfur vacancies would give rise to the ZnS with N{sub S} defects system losing the magnetism. Moderate formation energy (0.71 eV) indicates ZnS with N{sub S} defects could be fabricated experimentally.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Adaptive, Active Learning, and Multifidelity Monte Carlo Methods in the MOOSE Stochastic Tools Module

MOOSE is an open-source computational platform for constructing multi-physics models and executing them in a massively parallel fashion. It has a stochastic tools module (STM) for forward/inverse uncertainty quantification (UQ) and surrogate modeling. This presentation details some recent developments to the STM with respect to the implementation of adaptive, active learning, and multifidelity Monte Carlo methods for forward UQ of computational models. Specifically, the adaptive Monte Carlo methods include Markov Chain Monte Carlo (MCMC)-driven algorithms like adaptive importance sampling and parallelized subset simulation for statistical QoI estimation, rare events analysis, and stochastic gradient-free optimization. The active learning methods include Gaussian Process (GP) surrogates and their training via Adam optimization, design of acquisition functions, and integration with samplers like Monte Carlo, adaptive importance, and parallelized subset simulation. These active learning methods are also designed to work in a batch mode, wherein, the required calls to the full computational model are executed in parallel whenever a user-specified batch size is met. The multifidelity methods in STM are broadly divided into two categories: hierarchical, where a defined hierarchy exists among the low-fidelity models, and peer, where all the low-fidelity models are treated equally. A GP surrogate is used to learn the differences between the low- and high-fidelity models in both multifidelity categories, and acquisition functions from the active learning classes are used to decide whether to rely on a low-fidelity model or call the expensive high-fidelity model. Alongside the software description and usage, applications are also presented to nuclear engineering computational models including a TRISO nuclear fuel particle, a reactor pressure vessel, and a heat-pipe microreactor.

97 MATHEMATICS AND COMPUTING↗

Characterizing Peatland Microtopography Using Gradient and Microform-Based Approaches

Abstract Peatlands represent an important component of the global carbon cycle, storing 180–621 Gt of carbon (C). Small-scale spatial variations in elevation, frequently referred to as microtopography, influence ecological processes associated with the peatland C cycle, including Sphagnum photosynthesis and methane flux. Microtopography can be characterized with measures of topographic variability and by using conceptual classes (microforms) linked to function: most commonly hummocks and hollows. However, the criteria used to define these conceptual classes are often poorly described, if at all, and vary between studies. Such inconsistencies compel development of explicit quantitative methods to classify microforms. Furthermore, gradient-based characterizations that describe spatial variability without the use of microforms are lacking in the literature. Therefore, the objectives of this study were to (1) calculate peatland microtopographical elevation gradients and measures of spatial variability, (2) develop three microform classification methods intended for specific purposes, and (3) evaluate and contrast classification methods. Our results suggest that at spatial scales much larger than microforms, elevation distributions are unimodal and are well approximated with parametric probability density functions. Results from classifications were variable between methods and years and exhibited significant differences in mean hollow areal coverages of a raised ombrotrophic bog. Our results suggest that the conceptualization and classification of microforms can significantly influence microtopographic structural metrics. The three explicit methods for microform classification described here may be used and built upon for future applications.

54 ENVIRONMENTAL SCIENCES↗

Temperature drives local contributions to beta diversity in mountain streams: stochastic and deterministic processes

Community variation (i.e. beta diversity) in geographical coenoclines is of substantial interest in ecology, yet the elevational patterns in beta diversity are still understudied, and no general conclusions have been reached. Here, we explored local contributions to beta diversity (LCBD) of stream bacteria, diatoms and macroinvertebrates on mountainsides. Across all taxa, we revealed a general U-shaped LCBD-elevation relationships (LCBDer), suggesting higher uniqueness of community composition at the two ends of the elevational gradients. This pattern was confirmed by coenocline simulations based on observed communities, and supported by the dominance of species replacement in total beta diversity. Across mountains and taxonomic groups, temperature was the main environmental factor underlying elevational patterns in LCBD and its metric relatives, which were also mediated by local environmental variables. The observed magnitudes of U-shaped LCBDer across mountains and taxonomic groups were specifically related to the heterogeneity of stream morphology, and the mean annual temperature on each mountain. U-shaped LCBDer were strengthened by the occurrence of generalist species with large elevational ranges, while rare species had a lesser effect on the patterns. Raup-Crick beta diversity indicated that both stochastic and deterministic processes drove the community assembly, and the latter one was positively related to the magnitudes of LCBDer. Our synthesis across mountains and taxonomic groups clearly shows that there are consistent elevational patterns in LCBD among taxonomic groups, and that these patterns are explained by similar ecological mechanisms, producing a more complete picture in understanding and bridging the spatial variation in biodiversity under changing climate.

Wang, Jianjun↗

Frequency and Time Domain Modeling of Acoustic Liner Boundary Conditions

As part of a research program directed at the acoustics of advanced subsonic propulsion systems undertaken at NASA Langley, Duke University was funded to develop a boundary condition model for bulk-reacting nacelle liners. The overall objective of the Langley program was to understand and predict noise from advanced subsonic transport engines and to develop related noise control technology. The overall technical areas included: fan and propeller source noise, acoustics of ducts and duct liners, interior noise, subjective acoustics, and systems noise prediction. The Duke effort was directed toward duct liner acoustics for the development of analytical methods to characterize liner behavior in both frequency domain and time domain. A review of duct acoustics and liner technology can be found in Reference [1]. At that time, NASA Langley was investigating the propulsion concept of an advanced ducted fan, with a large diameter housed inside a relatively short duct. Fan diameters in excess of ten feet were proposed. The lengths of both the inlet and exhaust portions of the duct were to be short, probably less than half the fan diameter. The nacelle itself would be relatively thin-walled for reasons of aerodynamic efficiency. The blade-passage frequency was expected to be less than I kHz, and very likely in the 200 to 300 Hz range. Because of the design constraints of a short duct, a thin nacelle, and long acoustic wavelengths, the application of effective liner technology would be especially challenging. One of the needs of the NASA Langley program was the capability to accurately and efficiently predict the behavior of the acoustic liner. The traditional point impedance method was not an adequate model for proposed liner designs. The method was too restrictive to represent bulk reacting liners and to allow for the characterization of many possible innovative liner concepts. In the research effort at Duke, an alternative method, initially developed to handle bulk reacting layers as described in Reference [2], was extended to apply to a broad range of liner types. This method included the effect of local gradients along the liner surface, and was particularly appropriate for situations with flow over the liner and grazing incidence acoustic fields. In order to utilize time domain computational methods to solve for the propfan acoustic field, corresponding liner boundary conditions were developed for time domain solutions rather than frequency domain solutions.

Bliss, Donald B.↗

Development of an Innovative Algorithm for Aerodynamics-Structure Interaction Using Lattice Boltzmann Method

The lattice Boltzmann equation (LBE) is a kinetic formulation which offers an alternative computational method capable of solving fluid dynamics for various systems. Major advantages of the method are owing to the fact that the solution for the particle distribution functions is explicit, easy to implement, and the algorithm is natural to parallelize. In this final report, we summarize the works accomplished in the past three years. Since most works have been published, the technical details can be found in the literature. Brief summary will be provided in this report. In this project, a second-order accurate treatment of boundary condition in the LBE method is developed for a curved boundary and tested successfully in various 2-D and 3-D configurations. To evaluate the aerodynamic force on a body in the context of LBE method, several force evaluation schemes have been investigated. A simple momentum exchange method is shown to give reliable and accurate values for the force on a body in both 2-D and 3-D cases. Various 3-D LBE models have been assessed in terms of efficiency, accuracy, and robustness. In general, accurate 3-D results can be obtained using LBE methods. The 3-D 19-bit model is found to be the best one among the 15-bit, 19-bit, and 27-bit LBE models. To achieve desired grid resolution and to accommodate the far field boundary conditions in aerodynamics computations, a multi-block LBE method is developed by dividing the flow field into various blocks each having constant lattice spacing. Substantial contribution to the LBE method is also made through the development of a new, generalized lattice Boltzmann equation constructed in the moment space in order to improve the computational stability, detailed theoretical analysis on the stability, dispersion, and dissipation characteristics of the LBE method, and computational studies of high Reynolds number flows with singular gradients. Finally, a finite difference-based lattice Boltzmann method is developed for inviscid compressible flows.

Mei, Ren-Wei↗

Simultaneous measurement of gravity acceleration and gravity gradient with an atom interferometer

We demonstrate a method to measure the gravitational acceleration with a dual cloud atom interferometer; the use of simultaneous atom interferometers reduces the effect of seismic noise on the gravity measurement. At the same time, the apparatus is capable of accurate measurements of the vertical gravity gradient. The ability to determine the gravity acceleration and gravity gradient simultaneously and with the same instrument opens interesting perspectives in geophysical applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Incompressible multiphase flow and encapsulation simulations using the moment-of-fluid method

A moment-of-fluid method is presented for computing solutions to incompressible multiphase flows in which the number of materials can be greater than two. In this work, the multimaterial moment-of-fluid interface representation technique is applied to simulating surface tension effects at points where three materials meet. The advection terms are solved using a directionally split cell integrated semi-Lagrangian algorithm, and the projection method is used to evaluate the pressure gradient force term. The underlying computational grid is a dynamic block-structured adaptive grid. The new method is applied to multiphase problems illustrating contact-line dynamics, triple junctions, and encapsulation in order to demonstrate its capabilities. Examples are given in two-dimensional, three-dimensional axisymmetric (R–Z), and three-dimensional (X–Y–Z) coordinate systems.

97 MATHEMATICS AND COMPUTING↗

Parabolized reduced Navier-Stokes computational techniques

A review is presented of methods in which composite or reduced Navier-Stokes (RNS) equations are treated with a pressure-gradient-based flux-vector splitting. The methods are similar to large Re asymptotic formulations, and streamwise diffusion terms are ignored in favor of an explicit deferred corrector based on higher-order diffusion terms. The methods can be used for 2D and 3D supersonic flows in which the effects of real gas are incorporated. Several examples of the procedure are given, and subsonic and supersonic flows are handled well with relaxation procedures that incorporate multigrid acceleration. Effective solutions are described for problems ranging from incompressible flows and supersonic flows to sharp shocks and reverse-flow capturing.

Rubin, Stanley G.↗

Structural optimization with approximate sensitivities

Computational efficiency in structural optimization can be enhanced if the intensive computations associated with the calculation of the sensitivities, that is, gradients of the behavior constraints, are reduced. Approximation to gradients of the behavior constraints that can be generated with small amount of numerical calculations is proposed. Structural optimization with these approximate sensitivities produced correct optimum solution. Approximate gradients performed well for different nonlinear programming methods, such as the sequence of unconstrained minimization technique, method of feasible directions, sequence of quadratic programming, and sequence of linear programming. Structural optimization with approximate gradients can reduce by one third the CPU time that would otherwise be required to solve the problem with explicit closed-form gradients. The proposed gradient approximation shows potential to reduce intensive computation that has been associated with traditional structural optimization.

Patnaik, S. N.↗

SU-E-T-100: An Approach to Improving the Dynamic Delivery Accuracy for Breast IMRT

Purpose: A method is established to improve the accuracy of the IMRT dose delivery for the treatment of breast and chest wall tumors when the higher dose gradient is delivered at the end of the leaf sequence. Methods: Dynamic MLC deliveries on Varian Linacs are achieved through the motion of the leaves from X1 to X2 direction. If the higher dose gradient is at the end of the leaf motion sequence, this can Result in an increased error in the overall dose delivery. Such errors have been observed in Lateral beams for Left-sided and Medial beams for Right-sided treatments. To evaluate and resolve this issue we adopted an approach where the fluence for such beams was geometrically flipped (mirrored) to treat the higher end of the dose gradient first. Results: Using this method, it was possible to deliver the optimized dose map to the area of interest still using only the X1–X2 direction of the leaf motion. The accuracy of this method was tested on different beam as part of our pre-treatment QA program on both Varian delivery systems. With this approach we found that there was significant improvement in delivery accuracy on both 21EX and TrueBeam systems. Beams of initial Gamma index (3% and 3mm) 89–93% were increased to 98–99%. We also observed superior delivery accuracy with TB compared to the 21EX Conclusion: This work demonstrate the need for a delivery sequence option from X2–X1 in situations where the MLC sequence indicates higher dose gradient component is being delivered at the end of the sequence. Results from this work can be considered in the IMRT beam optimization in the treatment planning systems. Further work will be required to establish the application of this approach in clinical setting.

60 APPLIED LIFE SCIENCES↗