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At least 253 records · Page 14

Upgrade and Operation of the ATLAS Radiation Interlock System (ARIS)

ATLAS (the Argonne Tandem Linac Accelerator Sys-tem) is a superconducting heavy ion accelerator which can accelerate nearly all stable, and some unstable, iso-topes between hydrogen and uranium. Prompt radiation fields from gamma and or neutron are typically below 1 rem/hr at 30 cm, but are permitted up to 300 rem/hr at 30 cm. The original ATLAS Radiation Interlock System (ARIS), hereafter referred to as ARIS 1.0 was installed 30 years ago. While it has been a functional critical safe-ty system, its age has exposed the facility to high risk of temporary shutdown due to failure of obsolete compo-nents. Topics discussed will be architecture, hardware improvements, functional improvements, and operation permitting personnel access to areas with low levels of radiation.

Blomberg, B. R.↗

Prospects for Higgs and di-Higgs measurements at the ATLAS experiment

The large dataset of about 3000 {fb}^{-1} f b − 1 that will be collected at the High Luminosity LHC (HL-LHC) will be used to measure Higgs boson processes in detail. This large dataset will also provide sensitivity to di-Higgs processes and will allow for the improvement of the constraints on the Higgs boson self coupling. Studies based on current ATLAS analyses using LHC Run 2 data have been carried out to understand the expected precision and limitations of the Higgs and di-Higgs measurements at the HL-LHC. This paper presents the ATLAS prospects for Higgs and di-Higgs results at the HL-LHC.

Betti, Alessandra↗

Global Soil Virus (GSV) Atlas

Historically neglected by microbial ecologists, soil viruses are now thought to be critical to global biogeochemical cycles. However, our understanding of their global distribution, activities, and interactions with the soil microbiome remains limited. Here, we present the Global Soil Virus (GSV) Atlas, a comprehensive dataset from 2,953 soils that comprises 616,935 uncultivated virus genomes (UViGs) and 38,508 unique viral operational taxonomic units (vOTUs). Rarefaction curves from the GSV Atlas indicate that most soil viral diversity remains unexplored, further underscored by high spatial turnover and low rates of shared vOTUs across samples. By examining genes associated with biogeochemical functions, we also demonstrate the viral potential to impact soil carbon and nutrient cycling. This study represents the most extensive characterization of soil viral diversity to date and provides a foundation for developing testable hypotheses regarding the role of the virosphere in the soil microbiome and global biogeochemistry.

Graham, Emily B↗

Disintegration of Long-period Comet C/2019 Y4 (ATLAS). I. Hubble Space Telescope Observations

The near-Sun comet C/2019 Y4 (ATLAS) is the first member of a long-period comet group observed to disintegrate well before perihelion. Here we present our investigation into this disintegration event using images obtained in a three-day Hubble Space Telescope campaign. We identify two fragment clusters produced by the initial disintegration event, corresponding to fragments C/2019 Y4-A and C/2019 Y4-B identified in ground-based data. These two clusters started with similar integrated brightness but exhibit different evolutionary behavior. C/2019 Y4-A was much shorter-lived compared to C/2019 Y4-B and showed signs of significant mass loss and changes in size distribution throughout the three-day campaign. The cause of the initial fragmentation is undetermined by the limited evidence but crudely compatible with either the spin-up disruption of the nucleus or runaway sublimation of subsurface supervolatile ices, either of which would lead to the release of a large amount of gas as inferred from the significant bluing of the comet observed shortly before its disintegration. Gas can only be produced by the sublimation of volatile ices, which must have survived at least one perihelion passage at a perihelion distance of q = 0.25 au. We speculate that Comet ATLAS is derived from the ice-rich interior of a nonuniform, kilometer-wide progenitor that split during its previous perihelion. This suggests that comets down to a few kilometers in diameter can still possess complex, nonuniform interiors that can protect ices against intense solar heating.

47 OTHER INSTRUMENTATION↗

Upgrades of the ATLAS Zero Degree Calorimeter System for Run 3 at the Large Hadron Collider

Experimental studies of ultra-relativistic heavy ion collisions at the Large Hadron Collider (LHC) depend crucially on Zero Degree Calorimeters (ZDCs) that measure neutrons produced at near-beam rapidity in nucleus-nucleus collisions. In hadronic nuclear collisions these neutrons are mainly spectator neutrons, those that do not scatter from opposing nucleons during the collision. As a result, the ZDCs provide a vital probe of heavy ion collision geometry. The ZDCs are also essential in the study of ultra-peripheral collisions that are initiated by photons associated with the electric fields of one or both nuclei. Coherent photon emission typically leaves the photon emitter intact, making the observation of no ZDC signal, on one or both sides, a tag of such processes. The ATLAS ZDCs, built prior to Run 1 were substantially upgraded for LHC Run 3. The primary upgrades included replacement of the quartz Cherenkov radiator with $\text{H}_2$-doped fused silica rods; installation of fast air-core signal cables between the ZDC and the ATLAS USA15 cavern; new LED-based calibration system; and new electronics implemented for readout and fully-digital triggering. The ZDCs were also augmented with new "Reaction Plane Detectors" (RPDs) designed to measure the transverse centroid of multi-neutron showers to allow event-by-event reconstruction of the directed-flow plane in nuclear collisions. The Run~3 ZDC detectors, including the RPDs, are described in detail with emphasis on aspects that are new for Run~3.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Data items will occasionally be removed from OSM if they are misidentified, if they no longer exist, if they are duplicates of another item, or similar. For that reason, updated versions of this database may not contain all data center locations included in previous versions. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗

Plant Bioengineering Atlas: A Knowledge Graph of Genes, DNA Constructs, and Plant Traits.

Plant bioengineering has generated tens of thousands of genotype-to-phenotype relationships, but this knowledge remains fragmented across narrative literature and difficult to use computationally. Inconsistent descriptions of DNA constructs, host species, and traits, including variable species names, omitted regulatory elements, and inconsistent gene symbols, impede data reuse, comparative analysis, and design-build-test-learn cycles. Here, we present the Plant Bioengineering Atlas, a literature-mined, ontology-grounded knowledge base assembled using an artificial intelligence (AI)-aided extraction pipeline. A large language model parsed open-access primary research articles to generate structured, provenance-anchored records of engineered genes, modification types, promoter-gene-terminator constructs, host species, target traits, and reported phenotypes, with every record traceable to its source. The current release contains 14,358 curated records encompassing 6,998 distinct genes across 436 plant species from 6,452 papers published between 2000 and 2026. Corpus analysis reveals that experiments are concentrated in a small group of model and crop species, disease and pathogen resistance is the most frequently engineered trait class, and constitutive regulatory parts (particularly the CaMV 35S promoter and NOS terminator) remain pervasive. Two in five records omit one or both flanking regulatory elements (i.e., promoter and terminator), while only 23.4% describe cassettes in which both elements resolve to named part classes, exposing a systematic reproducibility gap. We organize these data into a knowledge graph linking genes, constructs, species, and traits; provide access through an interactive web portal; and propose an AI-compatible documentation standard for AI-ready reporting. The Plant Bioengineering Atlas provides a foundation for data-driven hypothesis generation and AI-aided plant biodesign.

, Genes, DNA Constructs↗

Flight performance of Atlas-Agena launch vehicles in support of the Lunar Orbiter missions 3, 4, and 5

Atlas-Agena launch vehicles successfully boosted a series of five Lunar Orbiters into proper lunar transfer trajectories. This report discusses the flight performance of the last three Atlas-Agenda launch vehicles (for Lunar Orbiters 111, IV, and V) from lift-off through the Agenda retromaneuver. The objective of these flights was to perform seleno- graphic investigations including photography of the lunar surface. Lunar Orbiter V, launched in August 1967, concluded the Lunar Orbiter missions

Source record↗

Atlas-Centaur AC-17 performance for applications technology satellite ATS-D mission

The Atlas-Centaur launch vehicle (AC-17) with Applications Technology Satellite-D (ATS-D) was launched from Cape Kennedy in August 1968. Mission objectives were not achieved because the Centaur main engine failed to start for the second powered phase. An evaluation is reported of the performance of the Atlas-Centaur systems, from lift off through the Centaur restart attempt. A brief analysis of the Centaur failure is included.

Source record↗

The Copernicus ultraviolet spectral atlas Tau Scorpii

An ultraviolet spectral atlas was presented for the B0 V star, Tau Scorpii. It was scanned from 949 to 1560 A by the Princeton spectrometer aboard the Copernicus satellite. From 949 to 1420 A the observations have a nominal resolution of 0.05 A. At the longer wavelengths, the resolution was 0.1 A. The atlas was presented in both tables and graphs.

Rogerson, J. B., Jr.↗

Progress toward a circulation atlas for application to coastal water siting problems

Circulation data needed to resolve coastal siting problems are assembled from historical hydrographic and remote sensing studies in the form of a Circulation Atlas. Empirical data are used instead of numerical model simulations to achieve fine resolution and include fronts and convergence zones. Eulerian and Langrangian data are collected, transformed, and combined into trajectory maps and current vector maps as a function of tidal phase and wind vector. Initial Atlas development is centered on the Elizabeth River, Hampton Roads, Virgina.

Munday, J. C., Jr.↗

The Copernicus ultraviolet spectral atlas of Tau Scorpii

An ultraviolet spectral atlas is presented for the B0 V star, Tau Scorpii. It has been scanned from 949 to 1560 A by the Princeton spectrometer aboard the Copernicus satellite. From 949 to 1420 A the observations have a nominal resolution of 0.05 A. At the longer wavelengths, the resolution is 0.1 A. The atlas is presented in both tables and graphs.

Rogerson, J. B., Jr.↗

An atlas of Copernicus ultraviolet spectra of Wolf-Rayet stars

An atlas of Copernicus UV scans is presented, and line identifications are tabulated, for the Wolf-Rayet stars Gamma-2 Vel (WC 8 + O7), HD 50896 (= EZ CMa; WN 5), and HD 92740 (WN 7). The atlas covers the wavelength ranges from 946.8 to 3182 A for Gamma-2 Vel, from 1012 to 1294 A for HD 50896, and from 1051 to 1243 A for HD 92740. The wavelengths include corrections for components of satellite velocity, earth velocity, and stellar heliocentric velocity; each spectral feature is classified as interstellar, photospheric, emission, UV-displaced P Cygni line absorption, or P Cygni line emission. UV-edge velocities of the P Cygni profiles are estimated, P Cygni profile types are discussed, and the results are compared with Copernicus scans of OB stars exhibiting UV P Cygni profiles. It is noted that: (1) the line-strength ratio of molecular hydrogen to atomic species appears to be substantially greater in the scans of the WN stars than in the Gamma-2 Vel scans; (2) some of the P Cygni profiles in Gamma-2 Vel differ significantly from the corresponding profiles in OB stars; and (3) there may be a slight inverse correlation between ejection velocities and excitation potentials in Gamma-2 Vel.

Johnson, H. M.↗

ATLAS, an integrated structural analysis and design system. Volume 3: User's manual, input and execution data

The input data and execution control statements for the ATLAS integrated structural analysis and design system are described. It is operational on the Control Data Corporation (CDC) 6600/CYBER computers in a batch mode or in a time-shared mode via interactive graphic or text terminals. ATLAS is a modular system of computer codes with common executive and data base management components. The system provides an extensive set of general-purpose technical programs with analytical capabilities including stiffness, stress, loads, mass, substructuring, strength design, unsteady aerodynamics, vibration, and flutter analyses. The sequence and mode of execution of selected program modules are controlled via a common user-oriented language.

Dreisbach, R. L.↗

ATLAS, an integrated structural analysis and design system. Volume 5: System demonstration problems

One of a series of documents describing the ATLAS System for structural analysis and design is presented. A set of problems is described that demonstrate the various analysis and design capabilities of the ATLAS System proper as well as capabilities available by means of interfaces with other computer programs. Input data and results for each demonstration problem are discussed. Results are compared to theoretical solutions or experimental data where possible. Listings of all input data are included.

Samuel, R. A.↗

ATLAS, an integrated structural analysis and design system. Volume 6: Design module theory

The automated design theory underlying the operation of the ATLAS Design Module is decribed. The methods, applications and limitations associated with the fully stressed design, the thermal fully stressed design and a regional optimization algorithm are presented. A discussion of the convergence characteristics of the fully stressed design is also included. Derivations and concepts specific to the ATLAS design theory are shown, while conventional terminology and established methods are identified by references.

Backman, B. F.↗