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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

An efficient cre‐based workflow for genomic integration and expression of large biosynthetic pathways in Eubacterium limosum

Abstract Acetogenic Clostridia are obligate anaerobes that have emerged as promising microbes for the renewable production of biochemicals owing to their ability to efficiently metabolize sustainable single‐carbon feedstocks. Additionally, Clostridia are increasingly recognized for their biosynthetic potential, with recent discoveries of diverse secondary metabolites ranging from antibiotics to pigments to modulators of the human gut microbiota. Lack of efficient methods for genomic integration and expression of large heterologous DNA constructs remains a major challenge in studying biosynthesis in Clostridia and using them for metabolic engineering applications. To overcome this problem, we harnessed chassis‐independent recombinase‐assisted genome engineering (CRAGE) to develop a workflow for facile integration of large gene clusters (>10 kb) into the human gut acetogen Eubacterium limosum . We then integrated a non‐ribosomal peptide synthetase gene cluster from the gut anaerobe Clostridium leptum , which previously produced no detectable product in traditional heterologous hosts. Chromosomal expression in E. limosum without further optimization led to production of phevalin at 2.4 mg/L. These results further expand the molecular toolkit for a highly tractable member of the Clostridia, paving the way for sophisticated pathway engineering efforts, and highlighting the potential of E. limosum as a Clostridial chassis for exploration of anaerobic natural product biosynthesis.

Sanford, Patrick A.↗
DOE OSTI2024

Acetaminophen production in the edible, filamentous cyanobacterium Arthrospira platensis

Abstract Spirulina is the common name for the edible, nonheterocystous, filamentous cyanobacteriumArthrospira platensisthat is grown industrially as a food supplement, animal feedstock, and pigment source. Although there are many applications for engineering this organism, until recently no genetic tools or reproducible transformation methods have been published. While recent work showed the production of a diversity of proteins inA. platensis, including single‐domain antibodies for oral delivery, there remains a need for a modular, characterized genetic toolkit. Here, we independently establish a reproducible method for the transformation ofA. platensisand engineer this bacterium to produce acetaminophen as proof‐of‐concept for small molecule production in an edible host. This work opensA. platensisto the wider scientific community for future engineering as a functional food for nutritional enhancement, modification of organoleptic traits, and production of pharmaceuticals for oral delivery.

Biotechnology & Applied Microbiology↗
DOE OSTI2024

Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F)

An open‐source modeling platform, called Anaerobic Digestion Model No. 1 Fast (ADM1F), is introduced to achieve fast and numerically stable simulations of anaerobic digestion processes. ADM1F is compatible with an iPython interface to facilitate model configuration, simulation, data analysis, and visualization. Faster simulations and more stable results are accomplished by implementing an advanced open‐source library of numerical methods called Portable Extensive Toolkit for Scientific Computation (PETSc) to solve the ADM1 system of equations. Leveraging PETSc, ADM1F can consistently complete a steady‐state simulation under 0.2 s, over 99% faster than a benchmark ADM1 model implemented with MATLAB while achieving agreement of model outputs within 1% of those obtained with the benchmark model. For dynamic simulations, however, ADM1F has a computational speed advantage only when the influent characteristics update more frequently than every 4 h. The ability of ADM1F to be useful as a tool to study anaerobic digestion systems is demonstrated through two example implementations of ADM1F: (1) a two‐phase co‐digestion scenario evaluating the impact of the organic loading rate and the substrate composition on reactor performance and stability, and (2) a conventional digester scenario assessing the effectiveness of recovery strategies after disruptions that led to instability. These examples demonstrate how the high simulation speed and the convenience of the iPython interface allow ADM1F to complete complex analyses within minutes, much faster than computational strategies currently reported in the literature.

anaerobic co-digestion↗
DOE OSTI2016

A new deadlock resolution protocol and message matching algorithm for the extreme-scale simulator

Investigating the performance of parallel applications at scale on future high-performance computing (HPC) architectures and the performance impact of different HPC architecture choices is an important component of HPC hardware/software co-design. The Extreme-scale Simulator (xSim) is a simulation toolkit for investigating the performance of parallel applications at scale. xSim scales to millions of simulated Message Passing Interface (MPI) processes. The overhead introduced by a simulation tool is an important performance and productivity aspect. This paper documents two improvements to xSim: (1)~a new deadlock resolution protocol to reduce the parallel discrete event simulation overhead and (2)~a new simulated MPI message matching algorithm to reduce the oversubscription management overhead. The results clearly show a significant performance improvement. The simulation overhead for running the NAS Parallel Benchmark suite was reduced from 102% to 0% for the embarrassingly parallel (EP) benchmark and from 1,020% to 238% for the conjugate gradient (CG) benchmark. xSim offers a highly accurate simulation mode for better tracking of injected MPI process failures. Furthermore, with highly accurate simulation, the overhead was reduced from 3,332% to 204% for EP and from 37,511% to 13,808% for CG.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

A PETSc Parallel-in-Time Solver based on MGRIT algorithm

We address the development of a modular implementation of the MGRIT (MultiGrid-In-Time) algorithm to solve linear and nonlinear systems that arise from the discretization of evolutionary models with a parallel-in-time approach in the context of the PETSc (the Portable, Extensible Toolkit for Scientific computing) library. Our aim is to give the opportunity of predicting the performance gain achievable when using the MGRIT approach instead of the Time Stepping integrator (TS). To this end, we analyze the performance parameters of the algorithm that provide a-priori the best number of processing elements and grid levels to use to address the scaling of MGRIT, regarded as a parallel iterative algorithm proceeding along the time dimension.

Mele, Valeria↗
DOE OSTI2021

FPGA-based HPC accelerators: An evaluation on performance and energy efficiency

Hardware specialization is a promising direction for the future of digital computing. Reconfigurable technologies enable hardware specialization with modest non-recurring engineering cost, but their performance and energy efficiency compared to state-of-the-art processor architectures remain an open question. In this article, we use FPGAs to evaluate the benefits of building specialized hardware for numerical kernels found in scientific applications. In order to properly evaluate performance, we not only compare Intel Arria 10 and Xilinx U280 performance against Intel Xeon, Intel Xeon Phi, and NVIDIA V100 GPUs, but we also extend the Empirical Roofline Toolkit (ERT) to FPGAs in order to assess our results in terms of the Roofline model. We show design optimization and tuning techniques for peak FPGA performance at reasonable hardware usage and power consumption. As FPGA peak performance is known to be far less than that of a GPU, we also benchmark the energy efficiency of each platform for the scientific kernels comparing against microbenchmark and technological limits. Results show that while FPGAs struggle to compete in absolute terms with GPUs on memory- and compute-intensive kernels, they require far less power and can deliver nearly the same energy efficiency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Retrospective evaluation of dosimetric quality for prostate carcinomas treated with 3D conformal, intensity modulated and volumetric modulated arc radiotherapy

This study examines and compares the dosimetric quality of radiotherapy treatment plans for prostate carcinoma across a cohort of 163 patients treated across five centres: 83 treated with three-dimensional conformal radiotherapy (3DCRT), 33 treated with intensity modulated radiotherapy (IMRT) and 47 treated with volumetric modulated arc therapy (VMAT). Treatment plan quality was evaluated in terms of target dose homogeneity and organs at risk (OAR), through the use of a set of dose metrics. These included the mean, maximum and minimum doses; the homogeneity and conformity indices for the target volumes; and a selection of dose coverage values that were relevant to each OAR. Statistical significance was evaluated using two-tailed Welch's T-tests. The Monte Carlo DICOM ToolKit software was adapted to permit the evaluation of dose metrics from DICOM data exported from a commercial radiotherapy treatment planning system. The 3DCRT treatment plans offered greater planning target volume dose homogeneity than the other two treatment modalities. The IMRT and VMAT plans offered greater dose reduction in the OAR: with increased compliance with recommended OAR dose constraints, compared to conventional 3DCRT treatments. When compared to each other, IMRT and VMAT did not provide significantly different treatment plan quality for like-sized tumour volumes. This study indicates that IMRT and VMAT have provided similar dosimetric quality, which is superior to the dosimetric quality achieved with 3DCRT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

ReactionMechanismSimulator.jl: A modern approach to chemical kinetic mechanism simulation and analysis

Abstract We present ReactionMechanismSimulator.jl (RMS), a modern differentiable software for the simulation and analysis of chemical kinetic mechanisms, including multiphase systems. RMS has already been applied to problems in combustion, pyrolysis, polymers, pharmaceuticals, catalysis, and electrocatalysis. RMS is written in Julia, making it easy to develop and allowing it to take advantage of Julia's extensive numerical computing ecosystem. In addition to its extensive library of optimized analytic Jacobians, RMS can generate and use Jacobians computed using automatic differentiation and symbolically generated analytic Jacobians. RMS is demonstrated to be faster than Cantera and Chemkin in several benchmarks. RMS also implements an extensive set of features for analyzing chemical mechanisms, including a library of easy‐to‐call plotting functions, molecular structure resolved flux diagram generation, crash analysis, traditional sensitivity analysis, transitory sensitivity analysis, and an automatic mechanism analysis toolkit. RMS implements efficient adjoint and parallel forward sensitivity analyses. We also demonstrate the ease of adding new features to RMS.

Johnson, Matthew S.↗
DOE OSTI2025

Results of a Geant4 benchmarking study for bio‐medical applications, performed with the G4‐Med system

Geant4, a Monte Carlo Simulation Toolkit extensively used in bio-medical physics, is in continuous evolution to include newest research findings to improve its accuracy and to respond to the evolving needs of a very diverse user community. In 2014, the G4-Med benchmarking system was born from the effort of the Geant4 Medical Simulation Benchmarking Group, to benchmark and monitor the evolution of Geant4 for medical physics applications. The G4-Med system was first described in our Medical Physics Special Report published in 2021. Results of the tests were reported for Geant4 10.5. Purpose In this work, we describe the evolution of the G4-Med benchmarking system. Methods The G4-Med benchmarking suite currently includes 23 tests, which benchmark Geant4 from the calculation of basic physical quantities to the simulation of more clinically relevant set-ups. New tests concern the benchmarking of Geant4-DNA physics and chemistry components for regression testing purposes, dosimetry for brachytherapy with a 125 I source, dosimetry for external x-ray and electron FLASH radiotherapy, experimental microdosimetry for proton therapy, and in vivo PET for carbon and oxygen beams. Regression testing has been performed between Geant4 10.5 and 11.1. Finally, a simple Geant4 simulation has been developed and used to compare Geant4 EM physics constructors and physics lists in terms of execution times. Results In summary, our EM tests show that the parameters of the multiple scattering in the Geant4 EM constructor G4EmStandardPhysics_option3 in Geant4 11.1, while improving the modeling of the electron backscattering in high atomic number targets, are not adequate for dosimetry for clinical x-ray and electron beams. Therefore, these parameters have been reverted back to those of Geant4 10.5 in Geant4 11.2.1. The x-ray radiotherapy test shows significant differences in the modeling of the bremsstrahlung process, especially between G4EmPenelopePhysics and the other constructors under study (G4EmLivermorePhysics, G4EmStandardPhysics_option3, and G4EmStandardPhysics_option4). These differences will be studied in an in-depth investigation within our Group. Improvement in Geant4 11.1 has been observed for the modeling of the proton and carbon ion Bragg peak with energies of clinical interest, thanks to the adoption of ICRU90 to calculate the low energy proton stopping powers in water and of the Linhard–Sorensen ion model, available in Geant4 since version 11.0. Nuclear fragmentation tests of interest for carbon ion therapy show differences between Geant4 10.5 and 11.1 in terms of fragment yields. In particular, a higher production of boron fragments is observed with Geant4 11.1, leading to a better agreement with reference data for this fragment. Conclusions Based on the overall results of our tests, we recommend to use G4EmStandardPhysics_option4 as EM constructor and QGSP_BIC_HP with G4EmStandardPhysics_option4, for hadrontherapy applications. The Geant4-DNA physics lists report differences in modeling electron interactions in water, however, the tests have a pure regression testing purpose so no recommendation can be formulated.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Tuning Interface Electronic Properties via Chiral Two‐Dimensional Metal‐Organic Frameworks

Control over structural symmetries in nanomaterials offers a powerful approach to engineer electronic properties. For instance, breaking of mirror symmetries in two-dimensional (2D) materials with a hexagonal lattice can lead to nontrivial electronic topologies and correlated-electron phenomena. Yet, the impact of structural chirality on the electronic properties of 2D materials and interfaces remains underexplored. Here, how chiral phases of a 2D metal-organic framework (MOF) with a hexagonal lattice—consisting of hexaazatriphenylene molecules coordinated to Cu atoms—scatter, confine, and perturb the Shockley surface state (SS) electrons of an underlying Ag(111) substrate is investigated. Via low-temperature scanning tunneling microscopy and spectroscopy, noncontact atomic force microscopy, and numerical calculations based on an electronic plane-wave expansion method, modifications of the Ag(111) SS band structure are shown and quantified, including gap openings and lifts of band degeneracies, driven exclusively by the structural chirality of the 2D MOF phases. These findings highlight how structural symmetries, in particular chirality, affect electronic states at material interfaces, expanding on the toolkit for designing 2D materials with tailored electronic properties.

band structure engineering↗
DOE OSTI2026

DNA Crystals as a Template for Patterned Functional Materials

DNA nanotechnology offers a wide toolkit of molecular functionalities and scales, including intricate motifs less than 10 nm and periodic structures exceeding 100 µm. At larger scales, however, there are often significant tradeoffs for DNA structures, namely stability and mechanical strength. This work describes the design, synthesis, and characterization of a functionalized DNA crystal. Using a ligated DNA crystal grants significant freedom for various functional materials to be applied, in this case, semiconducting cadmium sulfide and palladium metal. Properties investigated in this study include stability, mechanical strength, and optoelectronic properties such as photoluminescence (PL) and electric conductivity. Significant changes are observed based on the functional material applied to DNA crystals. The Young's modulus of the crystal varies by about five orders of magnitude when functionalized with palladium. PL and semiconductive behaviors were observed when cadmium sulfide was attached. These crystals represent an expansion of the capabilities of DNA structures at these length scales, and additionally a platform for future studies exchanging the materials or altering the ligation scheme.

CdS↗
DOE OSTI2023

Developing Ultrahigh-Resolution E3SM Land Model for GPU Systems

Designing and refactoring complex scientific code, such as the E3SM land model (ELM), for new computing architectures is challenging. This paper presents design strategies and technical approaches to develop a data-oriented, GPU-ready ELM model using compiler directives (OpenACC/OpenMP). We first analyze the datatypes and processes in the original ELM code. Then we present design considerations for ultrahigh-resolution ELM (uELM) development for massive GPU systems. These techniques include the global data-oriented simulation workflow, domain partition, code porting and data copy, memory reduction, parallel loop restructure and flattening, and race condition detection. We implemented the first version of uELM using OpenACC targeting the NVidia GPUs in the Summit supercomputer at Oak Ridge National Laboratory. During the implementation, we developed a software tool (named SPEL) to facilitate code generation, verification, and performance tuning using these techniques. The first uELM implementation for Nvidia GPUs on Summit delivered promising results: 1) over 98% of the ELM code was automatically generated and tuned by scripts. Most ELM modules had better computational performances than the original ELM code for CPUs. The GPU-ready uELM is more scalable than the CPU code on fully-loaded Summit nodes. Example profiling results from several modules are also presented to illustrate the performance improvements and race condition detection. The lessons learned and toolkit developed in the study are also suitable for further uELM deployment using OpenMP on the first US exascale computer, Frontier, equipped with AMD CPUs and GPUs.

Schwartz, Peter↗
DOE OSTI2015

TECA: Petascale pattern recognition for climate science

Climate Change is one of the most pressing challenges facing humanity in the 21st century. Climate simulations provide us with a unique opportunity to examine effects of anthropogenic emissions. Highresolution climate simulations produce “Big Data”: contemporary climate archives are ≈ 5PB in size and we expect future archives to measure on the order of Exa-Bytes. In this work, we present the successful application of TECA (Toolkit for Extreme Climate Analysis) framework, for extracting extreme weather patterns such as Tropical Cyclones, Atmospheric Rivers and Extra-Tropical Cyclones from TB-sized simulation datasets. TECA has been run at full-scale on Cray XE6 and IBM BG/Q systems, and has reduced the runtime for pattern detection tasks from years to hours. TECA has been utilized to evaluate the performance of various computational models in reproducing the statistics of extreme weather events, and for characterizing the change in frequency of storm systems in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Measuring quantum discord at the LHC

There has been an increasing interest in exploring quantities associated with quantum information at colliders. We perform a detailed analysis describing how to measure the quantum discord in the top anti-top quantum state at the Large Hadron Collider (LHC). While for pure states, quantum discord, entanglement, and Bell nonlocality all probe the same correlations, for mixed states they probe different aspects of quantum correlations. The quantum discord, in particular, is interesting because it aims to encapsulate all correlations between systems that cannot have a classical origin. We employ two complementary approaches for the study of the top anti-top system, namely the decay method and the kinematic method. We highlight subtleties associated with measuring discord for reconstructed quantum states at colliders. Usually quantum discord is difficult to compute due to an extremization that must be performed. We show, however, that for the $t\bar{t}$ system this extremization can be performed analytically and we provide closed-form formulas for the quantum discord. We demonstrate that with current LHC datasets, quantum discord can be observed at 3.6 – 5.7σ, depending on the signal region, with the decay method and can be measured at a precision of 0.1 – 0.2% with the kinematic method. At the high luminosity LHC, the observation of quantum discord is expected to be > 5σ using both the decay and kinematic methods and can be measured with a precision of 5% with the decay method and 0.05% with the kinematic method. Additionally, we identify the kinematic cuts at the LHC to isolate the $t\bar{t}$ state that is separable but has non-zero discord. By systematically investigating quantum discord for the first time through a detailed collider analysis, this work expands the toolkit for quantum information studies in particle physics and lays the groundwork for deeper insights into the quantum properties in high-energy collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Expected sensitivity of the Light Dark Matter eXperiment to long-lived dark photons and axion-like particles

The Light Dark Matter eXperiment (LDMX) is an electron-beam fixed-target experiment primarily designed to achieve world-leading, model-independent sensitivity to sub-GeV dark matter particles. LDMX aims to identify dark sector particle production through the detection of events with substantial missing energy and momentum, a signature of invisible particles escaping detection. Beyond this primary objective, LDMX offers a complementary search strategy for long-lived, visibly decaying particles, such as dark photons and axion-like particles. We present the first detailed evaluation of the ability of LDMX to identify visibly decaying, long-lived particles that couple to electrons using a detailed simulation, based on the Geant 4-toolkit, that incorporates realistic detection efficiencies and background levels. We demonstrate that LDMX can achieve a sensitivity that is competitive with other experiments that are currently running. The models explored in this paper are distinct and complementary to those probed in the LDMX flagship missing-momentum analysis. Through searching for both invisible dark matter and visibly decaying long-lived signatures, LDMX will significantly advance the search for light dark matter and provide a broad exploration of the sub-GeV dark sector.[graphic not available: see fulltext]

Akesson, Torsten [Lund U.] (ORCID:0000000341415408↗
DOE OSTI2024

Explainable AI classification for parton density theory

Quantitatively connecting properties of parton distribution functions (PDFs, or parton densities) to the theoretical assumptions made within the QCD analyses which produce them has been a longstanding problem in HEP phenomenology. To confront this challenge, we introduce an ML-based explainability framework, XAI4PDF, to classify PDFs by parton flavor or underlying theoretical model using ResNet-like neural networks (NNs). By leveraging the differentiable nature of ResNet models, this approach deploys guided backpropagation to dissect relevant features of fitted PDFs, identifying x-dependent signatures of PDFs important to the ML model classifications. By applying our framework, we are able to sort PDFs according to the analysis which produced them while constructing quantitative, human-readable maps locating the x regions most affected by the internal theory assumptions going into each analysis. This technique expands the toolkit available to PDF analysis and adjacent particle phenomenology while pointing to promising generalizations.

Artificial Intelligence↗
DOE OSTI2019

Diffusion tensor imaging of the kidney in healthy controls and in children and young adults with autosomal recessive polycystic kidney disease

Objective: To compare diffusion tensor imaging (DTI) of the kidneys and its derived parameters in children with autosomal recessive polycystic kidney disease (ARPKD) versus healthy controls. Methods: In a prospective IRB-approved study, we evaluated the use of DTI to compare kidney parenchyma FA values in healthy controls (age-matched children with no history of renal disease) versus patients with ARPKD. A 20-direction DTI with b-values of b = 0 s/mm{sup 2} and b = 400 s/mm{sup 2} was used to acquire data in coronal direction using a fat-suppressed spin-echo echo-planar sequence. Diffusion Toolkit and TrackVis were used for analysis and segmentation. TrackVis was used to draw regions of interest (ROIs) covering the entire volume of the renal parenchyma, excluding the collecting system. Fibers were reconstructed using a deterministic fiber tracking algorithm. The FA values based on the ROI data, mean length, and volume of the tracks based on the fiber tracking data were recorded. Results: Eight healthy controls (mean age = 12.9 years ± 4.0; 1/8 males) and six ARPKD participants (mean age = 13.8 years ± 8.5; 5/6 males) were included in the study. Compared to healthy controls, patients with ARPKD had significantly lower FA values (0.33 ± 0.03 vs. 0.25 ± 0.02, p = 0.002) and mean track length (16.73 ± 3.43 vs. 11.61 ± 1.29 mm, p = 0.005). Conclusion: DTI of the kidneys shows significantly lower FA values and mean track length in children and young adults with ARPKD compared to normal subjects. DTI of the kidney offers a novel approach for characterizing renal disease based on changes in diffusion anisotropy and kidney structure.

62 RADIOLOGY AND NUCLEAR MEDICINE↗