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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Heterogeneity and Recombination of Foot-and-Mouth Disease Virus during Multi-Strain Coinfection of Cattle

Superinfection of cattle persistently infected with foot-and-mouth disease virus (FMDV), with a heterologous FMDV strain has been shown to generate novel recombinant viruses. In this study, we investigated the pathogenesis events within specific tissues associated with FMDV coinfections in cattle subjected to either simultaneous or serial exposure to two distinct strains of FMDV. Both strains of FMDV (one each of serotypes O and A) were similarly localized to the nasopharyngeal mucosa during the early stages of infection. However, while no recombinant FMDV genomes were recovered from simultaneously coinfected cattle, interserotypic recombinants were isolated from nasopharyngeal tissue samples obtained at 48 h after heterologous superinfection of a persistently infected FMDV carrier. Additionally, analysis of FMDV genomes obtained from replicate nasopharyngeal tissue samples demonstrated that adjacent segments of the mucosa were sometimes infected by distinct viruses, demonstrating a multifocal and heterogeneous distribution of FMDV infection during primary and persistent phases of infection. Furthermore, this work indicates that superinfection of FMDV carriers may be an important source of emergent recombinant strains of FMDV in areas where multiple strains are co-circulating.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Formation of a constructed microbial community in a nutrient-rich environment indicates bacterial interspecific competition

ABSTRACT Understanding the organizational principles of microbial communities is essential for interpreting ecosystem stability. Previous studies have investigated the formation of bacterial communities under nutrient-poor conditions or obligate relationships to observe cooperative interactions among different species. How microorganisms form stabilized communities in nutrient-rich environments, without obligate metabolic interdependency for growth, is still not fully disclosed. In this study, three bacterial strains isolated from the Populus deltoides rhizosphere were co-cultured in complex medium, and their growth behavior was tracked. These strains co-exist in mixed culture over serial transfer for multiple growth-dilution cycles. Competition is proposed as an emergent interaction relationship among the three bacteria based on their significantly decreased growth levels. The effects of different initial inoculum ratios, up to three orders of magnitude, on community structure were investigated, and the final compositions of the mixed communities with various starting composition indicate that community structure is not dependent on the initial inoculum ratio. Furthermore, the competitive relationships within the community were not altered by different initial inoculum ratios. The community structure was simulated by generalized Lotka-Volterra and dynamic flux balance analysis to provide mechanistic predictions into emergence of community structure under a nutrient-rich environment. Metaproteomic analyses provide support for the metabolite exchanges predicted by computational modeling and for highly altered physiologies when microbes are grown in co-culture. These findings broaden our understanding of bacterial community dynamics and metabolic diversity in higher-order interactions and could be significant in the management of rhizospheric bacterial communities. IMPORTANCE Bacteria naturally co-exist in multispecies consortia, and the ability to engineer such systems can be useful in biotechnology. Despite this, few studies have been performed to understand how bacteria form a stable community and interact with each other under nutrient-rich conditions. In this study, we investigated the effects of initial inoculum ratios on bacterial community structure using a complex medium and found that the initial inoculum ratio has no significant impact on resultant community structure or on interaction patterns between community members. The microbial population profiles were simulated using computational tools in order to understand intermicrobial relationships and to identify potential metabolic exchanges that occur during stabilization of the bacterial community. Studying microbial community assembly processes is essential for understanding fundamental ecological principles in microbial ecosystems and can be critical in predicting microbial community structure and function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Strain relaxation in multilayer III–N structures on Si(111) substrates

X-ray diffractometry and X-ray scattering reciprocal space maps have been used to study strain relaxation in a complex buffer composed of seven intermediate layers of Al{sub x}Ga{sub 1−x}N composition with different values of x, decreasing with an increase in the distance from the substrate. The layers have been grown by hydride metalorganic vapor phase epitaxy on silicon and sapphire substrates. Differences in the structural quality of the first four layers of a multilayer buffer grown on different substrates have been revealed. A gradual smoothing out of these differences in the next three layers with an increase in the layer serial number has been shown. The last grown intermediate Al{sub x}Ga{sub 1−x}N layer and the GaN layer grown on it have identical thicknesses and degrees of mosaicity, regardless of the substrate type. Device structures grown on a complex buffer demonstrate emission in approximately the same wavelength range.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Role of structure imperfection in the formation of the magnetotransport properties of rare-earth manganites with a perovskite structure

The structure, the structure imperfection, and the magnetoresistance, magnetotransport, and microstructure properties of rare-earth perovskite La{sub 0.3}Ln{sub 0.3}Sr{sub 0.3}Mn{sub 1.1}O{sub 3–δ} manganites are studied by X-ray diffraction, thermogravimetry, electrical resistivity measurement, magnetic, {sup 55}Mn NMR, magnetoresistance measurement, and scanning electron microscopy. It is found that the structure imperfection increases, and the symmetry of a rhombohedrally distorted R3̅c perovskite structure changes into its pseudocubic type during isovalent substitution for Ln = La{sup 3+}, Pr{sup 3+}, Nd{sup 3+}, Sm{sup 3+}, or Eu{sup 3+} when the ionic radius of an A cation decreases. Defect molar formulas are determined for a real perovskite structure, which contains anion and cation vacancies. The decrease in the temperatures of the metal–semiconductor (T{sub ms}) and ferromagnet–paramagnet (T{sub C}) phase transitions and the increase in electrical resistivity ρ and activation energy E{sub a} with increasing serial number of Ln are caused by an increase in the concentration of vacancy point defects, which weaken the double exchange 3d{sup 4}(Mn{sup 3+})–2p{sup 6}(O{sup 2–})–3d{sup 3}(Mn{sup 4+})–V{sup (a)}–3d{sup 4}(Mn{sup 3+}). The crystal structure of the compositions with Ln = La contains nanostructured planar clusters, which induce an anomalous magnetic hysteresis at T = 77 K. Broad and asymmetric {sup 55}Mn NMR spectra support the high-frequency electronic double exchange Mn{sup 3+}(3d{sup 4}) ↔ O{sup 2–}(2p{sup 6}) ↔ Mn{sup 4+}(3d{sup 3}) and indicate a heterogeneous surrounding of manganese by other ions and vacancies. A correlation is revealed between the tunneling magnetoresistance effect and the crystallite size. A composition–structure imperfection–property experimental phase diagram is plotted. This diagram supports the conclusion about a strong influence of structure imperfection on the formation of the magnetic, magnetotransport, and magnetoresistance properties of rare-earth perovskite manganites.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Current-carrying element based on second-generation high-temperature superconductor for the magnet system of a fusion neutron source

Application of current-carrying elements (CCEs) made of second-generation high-temperature superconductor (2G HTS) in magnet systems of a fusion neutron source (FNS) and other fusion devices will allow their magnetic field and thermodynamic stability to be increased substantially in comparison with those of low-temperature superconductor (LTS) magnets. For a toroidal magnet of the FNS, a design of a helical (partially transposed) CCE made of 2G HTS is under development with forced-flow cooling by helium gas, a current of 20–30 kA, an operating temperature of 10–20 K, and a magnetic field on the winding of 12–15 T (prospectively ∼20 T). Short-sized samples of the helical flexible heavy-current CCE are being fabricated and investigated; a pilot-line unit for production of long-sized CCE pieces is under construction. The applied fabrication technique allows the CCE to be produced which combines a high operating current, thermal and mechanical stability, manufacturability, and low losses in the alternating modes. The possibility of fabricating the CCE with the outer dimensions and values of the operating parameter required for the FNS (and with a significant margin) using already available serial 2G HTS tapes is substantiated. The maximum field of toroidal magnets with CCEs made of 2G HTS will be limited only by mechanical properties of the magnet’s casing and structure, while the thermal stability will be approximately two orders of magnitude higher than that of toroidal magnets with LTS-based CCEs. The helical CCE made of 2G HTS is very promising for fusion and hybrid electric power plants, and its design and technologies of production, as well as the prototype coils made of it for the FNS and other tokamaks, are worth developing now.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Polymorphism of ScBO{sub 3} at the Solid Phase Synthesis from Amorphous Precursors

Detailed X-ray studies of changes in the structure of the scandium orthoborate ScBO{sub 3} in the process of serial isothermal annealing of the initial charge in the form of amorphous precursor were carried out. It was shown that upon successive annealing of the amorphous precursor, the crystalline phase first forms at an annealing temperature of 710°C, the positions of the reflections of which do not coincide with the positions that of the known calcite structure. This phase exists in a very narrow temperature range (≈30°C) and, when the annealing temperature is increased to 750°C, it completely transfers to the known rhombohedral phase of calcite. Using the ENDEAVOR software, the cell parameters, atom positions in the cell, and the spatial symmetry group of the new phase were determined. It turned out that the new phase corresponds to the hexagonal structure of the faterite (S.G. P63/mmc), known for other orthoborates of rare-earth elements (REE).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Generation of Giant Amplitude Pulses in a Klystron Chaos Auto-Oscillator

The presented experimental results demonstrate that microwave pulses of giant amplitude are generated in a klystron generator operating in the self-excited mode of chaotic oscillations. The auto-oscillator is assembled using a noisetron scheme that contains two five-cavity floating-drift klystrons serially connected in a ring, one of which operates in the mode of linear signal amplification (the linear klystron) and the other works in the mode of nonlinear signal amplification (the nonlinear klystron). It is established that, at a certain value of the beam current of a nonlinear klystron, intermittency of chaos–chaos type is realized in the auto-oscillation system in the form of chaotic sequences of microwave pulses of giant amplitude formed over the chaotic amplitude background. This type of intermittency is caused by the amplitude bistability of the nonlinear floating-drift klystron.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Algebraic multigrid domain and range decomposition (AMG-DD / AMG-RD)*

In modern large-scale supercomputing applications, algebraic multigrid (AMG) is a leading choice for solving matrix equations. However, the high cost of communication relative to that of computation is a concern for the scalability of traditional implementations of AMG on emerging architectures. This paper introduces two new algebraic multilevel algorithms, algebraic multigrid domain decomposition (AMG-DD) and algebraic multigrid range decomposition (AMG-RD), that replace traditional AMG V-cycles with a fully overlapping domain decomposition approach. While the methods introduced here are similar in spirit to the geometric methods developed by Brandt and Diskin [Multigrid solvers on decomposed domains, in Domain Decomposition Methods in Science and Engineering, Contemp. Math. 157, AMS, Providence, RI, 1994, pp. 135--155], Mitchell [Electron. Trans. Numer. Anal., 6 (1997), pp. 224--233], and Bank and Holst [SIAM J. Sci. Comput., 22 (2000), pp. 1411--1443], they differ primarily in that they are purely algebraic: AMG-RD and AMG-DD trade communication for computation by forming global composite “grids” based only on the matrix, not the geometry. (As is the usual AMG convention, “grids” here should be taken only in the algebraic sense, regardless of whether or not it corresponds to any geometry.) Another important distinguishing feature of AMG-RD and AMG-DD is their novel residual communication process that enables effective parallel computation on composite grids, avoiding the all-to-all communication costs of the geometric methods. The main purpose of this paper is to study the potential of these two algebraic methods as possible alternatives to existing AMG approaches for future parallel machines. As a result, this paper develops some theoretical properties of these methods and reports on serial numerical tests of their convergence properties over a spectrum of problem parameters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Fast Mesh-to-Mesh Remaps Using Hash Algorithms

Here, we explore the potential uses of hash-based algorithms in the remap operation, mapping one computational mesh onto another. We implement and test optimizations designed to reduce memory operations and compare these optimizations in order to evaluate the performance impact across different meshes. In particular, we created a new remap method that creates a structured hierarchy of hashes. Tests were run on 2D meshes on up to 14 levels of mesh refinement and hundreds of millions of cells to measure the algorithms' relative speeds under differing circumstances. We show that our methods perform two orders of magnitude better than the standard kD-tree algorithm and that on different meshes different hash methods can be optimal. We explore these algorithms on serial CPUs, GPUs using OpenCL, and multi-core CPUs using OpenMP.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Parallel-In-Time Magnus Integrators

Magnus integrators are a subset of geometric integration methods for the numerical solution of ordinary differential equations that conserve certain invariants in the numerical solution. Our report explores temporal parallelism of Magnus integrators, particularly in the context of nonlinear problems. The method combines the concurrent computation of matrix commutators and exponentials within a time step with a pipelined iteration applied to multiple time steps in parallel. The accuracy and efficiency of time parallel Magnus methods up to order six are highlighted through numerical examples and demonstrate that critical parallel speedup is possible compared to serial methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Nonconforming Mesh Refinement for High-Order Finite Elements

In this study, we propose a general algorithm for nonconforming adaptive mesh refinement (AMR) of unstructured meshes in high-order finite element codes. Our focus is on $h$-refinement with a fixed polynomial order. The algorithm handles triangular, quadrilateral, hexahedral, and prismatic meshes of arbitrarily high-order curvature, for any order finite element space in the de Rham sequence. We present a flexible data structure for meshes with hanging nodes and a general procedure to construct the conforming interpolation operator, both in serial and in parallel. The algorithm and data structure allow anisotropic refinement of tensor product elements in two and three dimensions and support unlimited refinement ratios of adjacent elements. We report numerical experiments verifying the correctness of the algorithms and perform a parallel scaling study to show that we can adapt meshes containing billions of elements and run efficiently on 393,000 parallel tasks. Finally, we illustrate the integration of dynamic AMR into a high-order Lagrangian hydrodynamics solver.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Layer-Parallel Training of Deep Residual Neural Networks

Residual neural networks (ResNets) are a promising class of deep neural networks that have shown excellent performance for a number of learning tasks, e.g., image classification and recognition. Mathematically, ResNet architectures can be interpreted as forward Euler discretizations of a nonlinear initial value problem whose time-dependent control variables represent the weights of the neural network. Hence, training a ResNet can be cast as an optimal control problem of the associated dynamical system. For similar time-dependent optimal control problems arising in engineering applications, parallel-in-time methods have shown notable improvements in scalability. This paper demonstrates the use of those techniques for efficient and effective training of ResNets. The proposed algorithms replace the classical (sequential) forward and backward propagation through the network layers with a parallel nonlinear multigrid iteration applied to the layer domain. This adds a new dimension of parallelism across layers that is attractive when training very deep networks. From this basic idea, we derive multiple layer-parallel methods. The most efficient version employs a simultaneous optimization approach where updates to the network parameters are based on inexact gradient information in order to speed up the training process. Finally, using numerical examples from supervised classification, we demonstrate that the new approach achieves a training performance similar to that of traditional methods, but enables layer-parallelism and thus provides speedup over layer-serial methods through greater concurrency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Additive Polynomial Time Integrators, Part I: Framework and Fully Implicit-Explicit Collocation Methods

In this paper we generalize the polynomial time integration framework to additively partitioned initial value problems. The framework we present is general and enables the construction of many new families of additive integrators with arbitrary order-of-accuracy and varying degree of implicitness. In this first work, we focus on a new class of implicit-explicit polynomial block methods that are based on fully implicit Runge–Kutta methods with Radau nodes and that possess high stage order. Here, we show that the new fully implicit-explicit (FIMEX) integrators have improved stability compared to existing IMEX Runge–Kutta methods, while also being more computationally efficient due to recent developments in preconditioning techniques for solving the associated systems of nonlinear equations. For PDEs on periodic domains where the implicit component is trivial to invert, we will show how parallelization of the right-hand side evaluations can be exploited to obtain significant speedup compared to existing serial IMEX Runge–Kutta methods. For parallel (in space) finite element discretizations, the new methods can achieve orders of magnitude better accuracy than existing IMEX Runge–Kutta methods and/or achieve a given accuracy several times times faster in terms of computational runtime.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Multigrid Reduction in Time for Chaotic Dynamical Systems

As CPU clock speeds have stagnated and high performance computers continue to have ever higher core counts, increased parallelism is needed to take advantage of these new architectures. Traditional serial time-marching schemes can be a significant bottleneck, as many types of simulations require large numbers of time-steps which must be computed sequentially. Parallel-in-time schemes, such as the Multigrid Reduction in Time (MGRIT) method, remedy this by parallelizing across time-steps and have shown promising results for parabolic problems. However, chaotic problems have proved more difficult, since chaotic initial value problems (IVPs) are inherently ill-conditioned. MGRIT relies on a hierarchy of successively coarser time-grids to iteratively correct the solution on the finest time-grid, but due to the nature of chaotic systems, small inaccuracies on the coarser levels can be greatly magnified and lead to poor coarse-grid corrections. Here we introduce a modified MGRIT algorithm based on an existing quadratically converging nonlinear extension to the multigrid Full Approximation Scheme (FAS), as well as a novel time-coarsening scheme. Together, these approaches better capture long-term chaotic behavior on coarse-grids and greatly improve convergence of MGRIT for chaotic IVPs. Further, we introduce a novel low-memory variant of the algorithm for solving chaotic PDEs with MGRIT which not only solves the IVP, but also provides estimates for the unstable Lyapunov vectors of the system. Finally, we provide supporting numerical results for the Lorenz system and demonstrate parallel speedup for the chaotic Kuramoto–Sivashinsky PDE over a significantly longer time-domain than in previous works.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Open database for GPD analyses

This article summarizes the main ideas behind creating an open database proposed for use in the exploration of generalized parton distributions (GPDs). This lightweight database is well suited for GPD phenomenology and is designed to store both experimental and lattice-QCD data. It can also aid in benchmarking GPD-related developments, such as GPD models. The database utilizes a new data format based on the YAML serialization language, enabling the storage of essential information for modern analyses, such as replica values. It includes interfaces for both Python and C++, allowing straightforward integration with analysis codes.

Burkert, V. D. [Thomas Jefferson National Accelera↗
DOE OSTI2023

GPU acceleration of Swendsen–Wang dynamics

When simulating a lattice system near its critical temperature, local algorithms for modeling the system’s evolution can introduce very large autocorrelation times into sampled data. Here, this critical slowing down places restrictions on the analysis that can be completed in a timely manner of the behavior of systems around the critical point. Because it is often desirable to study such systems around this point, a new algorithm must be introduced. Therefore, we turn to cluster algorithms, such as the Swendsen–Wang algorithm and the Wolff clustering algorithm. They incorporate global updates which generate new lattice configurations with little correlation to previous states, even near the critical point. We look to accelerate the rate at which these algorithm are capable of running by implementing and benchmarking a parallel implementation of each algorithm designed to run on GPUs under NVIDIA’s CUDA framework. A 17 and 90 fold increase in the computational rate was, respectively, experienced when measured against the equivalent algorithm implemented in serial code.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Distributed merge trees

Improved simulations and sensors are producing datasets whose increasing complexity exhausts our ability to visualize and comprehend them directly. To cope with this problem, we can detect and extract significant features in the data and use them as the basis for subsequent analysis. Topological methods are valuable in this context because they provide robust and general feature definitions. As the growth of serial computational power has stalled, data analysis is becoming increasingly dependent on massively parallel machines. To satisfy the computational demand created by complex datasets, algorithms need to effectively utilize these computer architectures. The main strength of topological methods, their emphasis on global information, turns into an obstacle during parallelization. We present two approaches to alleviate this problem. We develop a distributed representation of the merge tree that avoids computing the global tree on a single processor and lets us parallelize subsequent queries. To account for the increasing number of cores per processor, we develop a new data structure that lets us take advantage of multiple shared-memory cores to parallelize the work on a single node. Finally, we present experiments that illustrate the strengths of our approach as well as help identify future challenges. Copyright © 2013 ACM 978-1-4503-1922-5/13/ 02...$15.00.

Morozov, D↗
DOE OSTI2016

Evaluation of Graph Pattern Matching Workloads in Graph Analysis Systems

Graph analysis has emerged as a powerful method for data scientists to represent, integrate, query, and explore heterogeneous data sources. As a result, graph data management and mining became a popular area of research, and led to the development of plethora of systems in recent years. Unfortunately, the number of emerging graph analysis systems and the wide range of applications, coupled with a lack of apples-to-apples comparisons, make it difficult to understand the trade-offs between different systems and the graph operations for which they are designed. A fair comparison of these systems is a challenging task for the following reasons: multiple data models, non-standardized serialization formats, various query interfaces to users, and diverse environments they operate in. To address these key challenges, in this paper we present a new benchmark suite by extending the Lehigh University Benchmark (LUBM) to cover the most common capabilities of various graph analysis systems. We provide the design process of the benchmark, which generalizes the workflow for data scientists to conduct the desired graph analysis on different graph analysis systems. Equipped with this extended benchmark suite, we present performance comparison for nine subgraph pattern retrieval operations over six graph analysis systems, namely NetworkX, Neo4j, Jena, Titan, GraphX, and uRiKA. Through the proposed benchmark suite, this study reveals both quantitative and qualitative findings in (1) implications in loading data into each system; (2) challenges in describing graph patterns for each query interface; and (3) different sensitivity of each system to query selectivity. We envision that this study will pave the road for: (i) data scientists to select the suitable graph analysis systems, and (ii) data management system designers to advance graph analysis systems.

Hong, Seokyong↗