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At least 1,117 records · Page 62

Human Host Cellular Response to HCoV-229E Infection Proteomics (ACS-JM-DP2)

The purpose of this experiment was to evaluate the human host cellular response to wild-type Human coronavirus strain 229E (HCoV-229E) infection. Sample data was obtained for mock and infected immortalized human lung epithelial cells (A549) (MOI 5) nuclear extracts, immortalized human lung fibroblasts cells (MRC5) (MOI5) nuclear extracts, and primary human airway epithelial (HAE) (MOI 3) cells from lung tissue and processed for proteome analysis. Processed datasets are openly accessible from the download button and contain secondary processed proteomic results files and supporting metadata materials. Experimental proteomics samples were prepared using Limited Proteolysis (LiP) methods for Label-free quantification (LFQ) and global proteomic evaluation. Sample data was acquired using a Q-Exactive HF-X mass spectrometer and was processed and compiled using MaxQuant software (v.1.6.17.0). Processed proteomic data downloads include a sample naming key, processed MaxQuant results/parameters, and protein annotated relative abundance files. See corresponding primary data accessions below and Viral Experiment LiP Analysis source code supporting data transparency and reuse. Experimental transcriptomics samples were collected in parallel and processed for RNA sequencing (RNA-Seq) as summarized under ACS-DP1 (https://data.pnnl.gov/group/nodes/dataset/34069).

59 BASIC BIOLOGICAL SCIENCES↗

County-Level Hourly Renewable Capacity Factor Dataset for the ReEDS Model

This dataset contains hourly capacity factors for each renewable resource class and region (in this case, county). Technologies like large-scale utility PV (UPV), onshore wind, offshore wind, and concentrating solar power (CSP) are included. The dataset contains 7 years of hourly weather data (2007-2013) for different sites across the US and is used as one of the inputs to the ReEDS-2.0 model (see the "ReEDS 2.0 GitHub Repository" resource link below), developed by NREL. The weather profiles apply to any capacity that exists or is built in each region and class. This helps calculate the generation that can be provided using these resources. Open, reference, and limited are 3 scenarios based on land-use allowance, derived from the Renewable Energy Potential (reV) model developed by NREL, which helps generate supply curves for renewable technologies and assess the maximum potential of renewable resources in a designated area. Each zipped file in this dataset corresponds to a technology and contains the respective land-use scenario files required to run that technology in ReEDS. To use this dataset, download and place the extracted files in the locally cloned ReEDS repository inside one of the folders (inputs/variability/multi_year). After completing this copy, upon running the ReEDS model at the county-level spatial resolution for respective analysis purposes, the program will detect the presence of these files and will not fail.

Array↗

Multi-Sensor Data Acquisition System for Process Monitoring

Idaho National Laboratory is building a new nuclear fuel cycle test bed. This fuel cycle test bed named “Beartooth” will give researchers the opportunity to study the nuclear fuel cycle process. The process operations include the use of centrifugal contactors and process flow for the purification of special nuclear material recovery in used fuel. This new research facility has the need to use non-traditional measurement sensors to determine the state-of-health of the solvent extraction process. These non-traditional sensors can also enhance nuclear nonproliferation supervision and other activities. The non-traditional sensors include accelerometers, acoustic, current, flow, colorimetric, temperature, pH and conductivity. The challenge behind deploying all these sensors, is the need for fast and reliable data collection. The data acquisition system (DAQ) needs to be capable of recording up to 12 accelerometers and/or acoustic microphones simultaneously at rates up to 12.8 kSamples/second/channel. This requires the need for a strong architecture and data collection solution. This summary identifies the system architecture, DAQ, and sensors needed to support non-traditional measurements in a solvent extraction process.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) Science Plan

With their extensive coverage, low clouds greatly impact global climate. Presently, low clouds are poorly represented in global climate models (GCMs), and the response of low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The poor representations of low clouds in GCMs are in part due to inadequate observations of their microphysical and macrophysical structures, radiative effects, and the associated aerosol distribution and budget in regions where the aerosol impact is the greatest. The Eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary-layer (MBL) clouds, whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. Boundary-layer aerosol in the ENA region is influenced by a variety of sources, leading to strong variations in cloud condensation nuclei (CCN) concentration and aerosol optical properties. Recently a permanent ENA site was established by the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility on Graciosa Island in the Azores, providing invaluable information on MBL aerosol and low clouds. At the same time, the vertical structures and horizontal variabilities of aerosol, trace gases, cloud, drizzle, and atmospheric thermodynamics are critically needed for understanding and quantifying the budget of MBL aerosol, the radiative properties, precipitation efficiency, and lifecycle of MBL clouds, and the cloud response to aerosol perturbations. Much of this data can be obtained only through aircraft-based measurements. In addition, the interconnected aerosol and cloud processes are best investigated by a study involving simultaneous in situ aerosol, cloud, and thermodynamics measurements. Furthermore, in situ measurements are also necessary for validating and improving ground-based retrieval algorithms at the ENA site. This project is motivated by the need for comprehensive in situ characterizations of boundary-layer structure, and associated vertical distributions and horizontal variabilities of low clouds and aerosol over the Azores. ARM Aerial Facility (AAF) Gulfstream-1 (G-1) aircraft will be deployed at the ENA site during two intensive operational periods (IOPs) of early summer (June to July) of 2017 and winter (January to February) of 2018, respectively. Deployments during both seasons allow for examination of key aerosol and cloud processes under a variety of representative meteorological and cloud conditions. The science themes for the deployments include: 1) Budget of MBL CCN and its seasonal variation; 2) Effects of aerosol on cloud and precipitation; 3) Cloud microphysical and macrophysical structures, and entrainment mixing; 4) Advancing retrievals of turbulence, cloud, and drizzle; and 5) Model evaluation and processes studies. A key advantage of the deployments is the strong synergy between the measurements onboard the G-1 and the routine measurements at the ENA site, including state-of-the-art profiling and scanning radars. The 3D cloud structures provided by the scanning radars will put the detailed in situ measurements into mesoscale and cloud lifecycle contexts. On the other hand, high quality in situ measurements will enable validation and improvements of ground-based retrieval algorithms at the ENA site, leading to high-quality and statistically robust data sets from the routine measurements. The deployments, combined with the routine measurements at the ENA site, will have a long lasting impact on the research and modeling of low clouds and aerosols in the remote marine environment.

54 ENVIRONMENTAL SCIENCES↗

Brochure for the DOE Office of Science Workshop on Envisioning Frontiers in AI and Computing for Biological Research

In February of 2025 a joint ASCR/BER workshop was held to identify key transformational research directions for understanding biology using artificial intelligence (AI), digital twins and high-performance (HPC) computational methods to facilitate scientific discovery and innovation in support of the Department of Energy mission. AI technologies offer exciting new groundbreaking methods to analyze large volumes of complex biological data, thereby greatly accelerating the ability to understand, predict, and design biological processes for beneficial purposes. In the laboratory, the bridging of AI-enabled automated experimental technologies, HPC and digital twins will provide potent tools for researchers to explore the fundamental nature of biology and harness its inherent metabolic potential for a variety of beneficial purposes. The focus of this workshop was on how high-performance computational methods can impact this objective by exploring digital twins, foundational models, and data-driven approaches with applications to advance automated laboratory experiments, modeling of complex living systems and engineering new functions into plants and microbial systems relevant to DOE mission. Workshop attendees with expertise in plant science, microbiology, mathematics, computer science, and AI assessed the current state of the science, trends, and AI challenges at the interface of plant and microbial systems biology and computational science to identify opportunities for high-impact research. This collaborative effort capitalized on ASCR's advancements in applied mathematics, computer science, and Exascale systems, and BER's expertise in basic genomics-enabled research on DOE relevant plant and microbial systems. The workshop culminated in four key priority research directions to guide future research and development within DOE Office of Science programs.

59 BASIC BIOLOGICAL SCIENCES↗

TU-A-19A-01: Image Registration I: Deformable Image Registration, Contour Propagation and Dose Mapping: 101 and 201

Deformable image registration, contour propagation and dose mapping have become common, possibly essential tools for modern image-guided radiation therapy. Historically, these tools have been largely developed at academic medical centers and used in a rather limited and well controlled fashion. Today these tools are now available to the radiotherapy community at large, both as stand-alone applications and as integrated components of both treatment planning and treatment delivery systems. Unfortunately, the details of how these tools work and their limitations are not generally documented or described by the vendors that provide them. Although “it looks right”, determining that unphysical deformations may have occurred is crucial. Because of this, understanding how and when to use, and not use these tools to support everyday clinical decisions is far from straight forward. The goal of this session will be to present both the theory (basic and advanced) and practical clinical use of deformable image registration, contour propagation and dose mapping. To the extent possible, the “secret sauce” that different vendor use to produce reasonable/acceptable results will be described. A detailed explanation of the possible sources of errors and actual examples of these will be presented. Knowing the underlying principles of the process and understanding the confounding factors will help the practicing medical physicist be better able to make decisions (about making decisions) using these tools available. Learning Objectives: Understand the basic (101) and advanced (201) principles of deformable image registration, contour propagation and dose mapping data mapping. Understand the sources and impact of errors in registration and data mapping and the methods for evaluating the performance of these tools. Understand the clinical use and value of these tools, especially when used as a “black box”.

60 APPLIED LIFE SCIENCES↗

PDBx/mmCIF Ecosystem: Foundational Semantic Tools for Structural Biology

PDBx/mmCIF, Protein Data Bank Exchange (PDBx) macromolecular Crystallographic Information Framework (mmCIF), has become the data standard for structural biology. With its early roots in the domain of small-molecule crystallography, PDBx/mmCIF provides an extensible data representation that is used for deposition, archiving, remediation, and public dissemination of experimentally determined three-dimensional (3D) structures of biological macromolecules by the Worldwide Protein Data Bank (wwPDB, wwpdb.org). Extensions of PDBx/mmCIF are similarly used for computed structure models by ModelArchive (modelarchive.org), integrative/hybrid structures by PDB-Dev (pdb-dev.wwpdb.org), small angle scattering data by Small Angle Scattering Biological Data Bank SASBDB (sasbdb.org), and for models computed generated with the AlphaFold 2.0 deep learning software suite (alphafold.ebi.ac.uk). Community-driven development of PDBx/mmCIF spans three decades, involving contributions from researchers, software and methods developers in structural sciences, data repository providers, scientific publishers, and professional societies. Having a semantically rich and extensible data framework for representing a wide range of structural biology experimental and computational results, combined with expertly curated 3D biostructure data sets in public repositories, accelerates the pace of scientific discovery. Herein, we describe the architecture of the PDBx/mmCIF data standard, tools used to maintain representations of the data standard, governance, and processes by which data content standards are extended, plus community tools/software libraries available for processing and checking the integrity of PDBx/mmCIF data. Use cases exemplify how the members of the Worldwide Protein Data Bank have used PDBx/mmCIF as the foundation for its pipeline for delivering Findable, Accessible, Interoperable, and Reusable (FAIR) data to many millions of users worldwide.

59 BASIC BIOLOGICAL SCIENCES↗

Processing Techniques for ODS Stainless Steels

Oxide dispersion-strengthened (ODS) alloys have been studied extensively, in part as a response to the need to develop the high-temperature materials that are required for energy efficient systems. ODS stainless steels, in particular, are of technological interest because of their high ductility and high strength at elevated temperatures, which when combined with their resistance to corrosion, render them ideal for many applications that require extreme performance quality. Survey of the published literature reveals that efforts have been devoted to incorporate specific strengthening mechanisms in order to meet demanding performance criteria for ODS alloys. As a result, a number of novel processing approaches have been developed in an effort to design distinct microstructures that can enhance the performance of ODS alloys. In the current paper, various techniques used to manufacture ODS stainless steel alloys are compared and summarized on the basis of a literature search, and results are contrasted with selected experimental data obtained by the authors. In particular, cryomilling, water-atomization, and melt-spinning processes are described in detail as three novel approaches that can be effectively used to distribute nanometric oxides in 316L stainless steel matrix. The microstructural features, mechanical properties, and sintering behavior of the fabricated materials are described and discussed. The critical processing parameters for each processing technique are discussed with reference to the properties of the material. The versatility and potential challenges of the individual techniques are also described and contrasted.

36 MATERIALS SCIENCE↗

A technique for searching for the 2K capture in {sup 124}Xe with a copper proportional counter

An experimental technique for searching for the 2K capture in {sup 124}Xe with a large low-background copper proportional counter is described. Such an experiment is conducted at the Baksan Neutrino Observatory of the Institute for Nuclear Research of the Russian Academy of Sciences. The experimental setup is located in the Low-Background Deep-Level Laboratory at a depth of 4900 m.w.e., where the flux of muons of cosmic rays is suppressed by a factor of 10{sup 7} relative to that at the Earth’s surface. The setup incorporates a proportional counter and low-background shielding (18 cm of copper, 15 cm of lead, and 8 cm of borated polyethylene). The results of processing the data obtained in 5 months of live measurement time are presented. A new limit on the half-life of {sup 124}Xe with respect to the 2K capture is set at the level of 2.5 × 10{sup 21} years.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Runtime System for I/O Staging in Support of In-Situ Processing of Extreme Scale Data

Our research in this project focused on creating and evaluating an I/O infrastructure and tools for extreme-scale applications and machines so that scientists can reduce their time to discovery at small cost in machine resources and consequent power consumption. We wanted to provide tools that are highly scalable, portable, and easy-to-use, so that scientists can gain control of their science, and concentrate on producing important scientific discovery in their own domain. Accelerating the rate of insight and scientific productivity, therefore, demands new solutions to managing the avalanche of data expected at extreme scale.

97 MATHEMATICS AND COMPUTING↗

TH-A-BRC-00: New Task Groups for External Beam QA: An Overview

AAPM TG-135U1 QA for Robotic Radiosurgery - Sonja Dieterich Since the publication of AAPM TG-135 in 2011, the technology of robotic radiosurgery has rapidly developed. AAPM TG-135U1 will provide recommendations on the clinical practice for using the IRIS collimator, fiducial-less real-time motion tracking, and Monte Carlo based treatment planning. In addition, it will summarize currently available literature about uncertainties. Learning Objectives: Understand the progression of technology since the first TG publication Learn which new QA procedures should be implemented for new technologies Be familiar with updates to clinical practice guidelines AAPM TG-178 Gamma Stereotactic Radiosurgery Dosimetry and Quality Assurance - Steven Goetsch Purpose: AAPM Task Group 178 Gamma Stereotactic Radiosurgery Dosimetry and Quality Assurance was formed in August, 2008. The Task Group has 12 medical physicists, two physicians and two consultants. Methods: A round robin dosimetry intercomparison of proposed ionization chambers, electrometer and dosimetry phantoms was conducted over a 15 month period in 2011 and 2012 (Med Phys 42, 11, Nov, 2015). The data obtained at 9 institutions (with ten different Elekta Gamma Knife units) was analyzed by the lead author using several protocols. Results: The most consistent results were obtained using the Elekta ABS 16cm diameter phantom, with the TG-51 protocol modified as recommended by Alfonso et al (Med Phys 35, 11, Nov 2008). A key white paper (Med Phys, in press) sponsored by Elekta Corporation, was used to obtain correction factors for the ionization chambers and phantoms used in this intercomparison. Consistent results were obtained for both Elekta Gamma Knife Model 4C and Gamma Knife Perfexion units as measured with each of two miniature ionization chambers. Conclusion: The full report gives clinical history and background of gamma stereotactic radiosurgery, clinical examples and history, quality assurance recommendations and outline of possible dosimetry protocols. The report will be reviewed by the AAPM Working Group on Recommendations for Radiotherapy External Beam Quality Assurance and then by the AAPM Science Council before publication in Medical Physics Survey of possible calibration protocols for calibration of Gamma Stereotactic Radiosurgery (GSR) devices Overview of modern Quality Assurance techniques for GSR AAPM TG-218 Tolerance Levels and Methodologies for IMRT Verification QA - Moyed Miften Patient-specific IMRT QA measurement is a process designed to identify discrepancies between calculated and delivered doses. Error tolerance limits are not well-defined or consistently applied across centers. The AAPM TG-218 report has been prepared to improve the understanding and consistency of this process by providing recommendations for methodologies and tolerance limits in patient-specific IMRT QA. Learning Objectives: Review measurement methods and methodologies for absolute dose verification Provide recommendations on delivery methods, data interpretation, the use of analysis routines and choice of tolerance limits for IMRT QA Sonja Dieterich has a research agreement with Sun Nuclear Inc. Steven Goetsch is a part-time consultant for Elekta.

60 APPLIED LIFE SCIENCES↗

The Medical Science DMZ

Objective We describe use cases and an institutional reference architecture for maintaining high-capacity, data-intensive network flows (e.g., 10, 40, 100 Gbpsþ) in a scientific, medical context while still adhering to security and privacy laws and regulations. Materials and Methods High-end networking, packet filter firewalls, network intrusion detection systems. Results We describe a “Medical Science DMZ” concept as an option for secure, high-volume transport of large, sensitive data sets between research institutions over national research networks. Discussion The exponentially increasing amounts of “omics” data, the rapid increase of high-quality imaging, and other rapidly growing clinical data sets have resulted in the rise of biomedical research “big data.” The storage, analysis, and network resources required to process these data and integrate them into patient diagnoses and treatments have grown to scales that strain the capabilities of academic health centers. Some data are not generated locally and cannot be sustained locally, and shared data repositories such as those provided by the National Library of Medicine, the National Cancer Institute, and international partners such as the European Bioinformatics Institute are rapidly growing. The ability to store and compute using these data must therefore be addressed by a combination of local, national, and industry resources that exchange large data sets. Maintaining data-intensive flows that comply with HIPAA and other regulations presents a new challenge for biomedical research. Recognizing this, we describe a strategy that marries performance and security by borrowing from and redefining the concept of a “Science DMZ”—a framework that is used in physical sciences and engineering research to manage high-capacity data flows. Conclusion By implementing a Medical Science DMZ architecture, biomedical researchers can leverage the scale provided by high-performance computer and cloud storage facilities and national high-speed research networks while preserving privacy and meeting regulatory requirements.

97 MATHEMATICS AND COMPUTING↗

Discovery of optimal zeolites for challenging separations and chemical transformations using predictive materials modeling

Zeolites play numerous important roles in modern petroleum refineries and have the potential to advance the production of fuels and chemical feedstocks from renewable resources. The performance of a zeolite as separation medium and catalyst depends on its framework structure. To date, 213 framework types have been synthesized and >330000 thermodynamically accessible zeolite structures have been predicted. Hence, identification of optimal zeolites for a given application from the large pool of candidate structures is attractive for accelerating the pace of materials discovery. Here we identify, through a large-scale, multi-step computational screening process, promising zeolite structures for two energy-related applications: the purification of ethanol from fermentation broths and the hydroisomerization of alkanes with 18-30 carbon atoms encountered in petroleum refining. Finally, these results demonstrate that predictive modeling and data-driven science can now be applied to solve some of the most challenging separation problems involving highly non-ideal mixtures and highly articulated compounds.

36 MATERIALS SCIENCE↗

Seismic Tomography 2024

Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early-career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. Finally, it remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade.

58 GEOSCIENCES↗

Scalable Statistical Analysis of Gaussian Models for Petascale Spatiotemporal Data (Final Technical Report)

Gaussian process models for spatial and spatiotemporal data are ubiquitous in scientific and engineering applications. Likelihood-based methods for fitting such models, which includes all Bayesian methods, have desirable statistical properties and are thus the methods of choice when feasible. However, calculating the likelihood function even once can be a challenge for N irregularly sited observations from such a process, requiring O(N 2 ) memory and O(N 3 ) complexity. Thus, there is a need for fast and accurate likelihood approximation even for N on the order of 10 5 , not to mention the 10 15 implied by petascale data. The main objective of this research was to develop computational tools for the statistical analysis of massive spatiotemporal datasets based on Gaussian process models. Another important objective was the development of appropriate statistical models for specific spatiotemporal processes arising in the physical sciences.

97 MATHEMATICS AND COMPUTING↗

Mapping the Microstructure During the Historic U-Mo Monolithic Fuel Foil Fabrication Process

Since 2004, there has been extensive effort towards the development of a uranium molybdenum monolithic fuel system to convert high performance research and test reactors. The RERTR-6 experiment was the first to attempt a monolithic fuel instead of a dispersed fuel form. The fabrication methods evolved overtime and provided the basis for current fabrication methods. The various steps in the process inevitably tailor the fuel alloy microstructure which is known to influence irradiation behavior. This document aims to present and discuss the fabrication evolution that transpired through a recounting of historical data from the various fabrication campaigns. By overlaying this data with basic science studies on the U-Mo that explored transformation kinetics, it is possible to estimate a measure of the impact heat treatments have on the final as-fabricated microstructure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Modeling of heat transfer, fluid flow and solidification microstructure of nickel-base superalloy fabricated by laser powder bed fusion

Laser-Powder Bed Fusion (L-PBF), an additive manufacturing process, produces a distinctive microstructure that closely resembles the weld metal microstructure but at a much finer scale. The solidification parameters, particularly temperature gradient and solidification rate, are important to study the as-built microstructure. In the present paper, a computational framework with meso-scale resolution is developed for L-PBF of Inconel ® 718 (IN718), a Ni-base superalloy. The framework combines a powder packing model based on Discrete Element Method and a 3-D transient heat and fluid flow simulation. The latter, i.e., the molten pool model, captures the interaction between laser beam and individual powder particles including free surface evolution, surface tension and evaporation. The solidification parameters, calculated from the temperature fields, are used to assess the solidification morphology and grain size using existing theoretical models. The IN718 coupon built by L-PBF are characterized using optical and scanning electron microscopies. Finally, the experimental data of molten pool size and solidification microstructure are compared to the corresponding simulation results.

36 MATERIALS SCIENCE↗