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At least 829 records · Page 46

Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets v1.1.0

BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets) uses a data brokering approach to synthesize diverse earth science data from a variety of remote sources in real-time without the need for additional storage. BASIN-3D is an extendable Django web framework application using a generalized data synthesis model that makes the synthesized data available via REpresentational State Transfer (REST) Application Programming Interface (API). We have currently implemented our data synthesis model to represent sensor-based time series earth science observations across a hierarchy of spatial locations. Supporting our data synthesis model is a plugin framework that allows developers to map data sources of interest to the BASIN-3D synthesis model

Varadharajan, Charuleka↗

Idaho National Laboratory Quality Of Service Dataset

The code is designed to run tests to generate and collect data from a Wi-Fi network using OPENWRT or a simulated a 5G network using Open5gs and UERANSIM. The tests simulate the network performing downloads or uploads of various files with a varying number of concurrent users. The tests use tcpdump to collect the network traffic but only stores the summarized data. The summarized datasets will be included.

Krome, Cameron [Idaho National Laboratory (INL), I↗

Contribution to Open Molecules Dataset (coordcomplexsampling)

The Open Molecules Dataset is a project led by external collaborators, focused on the production of a wide diversity of molecular chemistries. This project will include high-throughput electronic structure calculations on metal coordination complexes, biomolecules, and electrolytes. Solvation effects, conformers, chemical reactivity, and spin/charge sampling will be pursued for elements on the periodic table up to, but not including the actinides. We aim to contribute code related to sampling for transition metal complexes, in particular, and expand software capabilities related to other thrusts desired.

Taylor, Michael G. [Los Alamos National Laboratory↗

SUNSet: The Software Understanding for National Security Dataset Repo

SAND2025-00511O SUNSet: The Software Understanding for National Security Dataset Repo serves as a repository for software understanding researchers to conduct systematic research in the field. It provides a platform for storing questions, answers, and scripts related to software programs, supporting research in software understanding. The repository is a nascent effort aimed at exploring the support needed by researchers and documenting how software understanding questions can be addressed using existing tools. The software consists of a simple database and front end interface for easy access and management of the stored information. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Amon, Tod [Sandia National Lab. (SNL-CA), Livermor↗

DRB-ML-Dataset

This datastet contains kernels extracted from OpenMP microbenchmarks collected in DataRaceBench. The purpose of this dataset is to serve as training data for machine learning with programming language processing (PLP).

Lin, Pei-Hung↗

P-MartCancer–Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets

P-MartCancer is a new interactive web-based software environment that enables biomedical and biological scientists to perform in-depth analyses of global proteomics data without requiring direct interaction with the data or with statistical software. P-MartCancer offers a series of statistical modules associated with quality assessment, peptide and protein statistics, protein quantification and exploratory data analyses driven by the user via customized workflows and interactive visualization. Currently, P-MartCancer offers access to multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium (CPTAC) at the peptide, gene and protein levels. P-MartCancer is deployed using Azure technologies (http://pmart.labworks.org/cptac.html), the web-service is alternatively available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/) and many statistical functions can be utilized directly from an R package available on GitHub (https://github.com/pmartR).

Webb-Robertson, Bobbie-Jo M.↗

Sea Surface Salinity Reemergence in an Updated North Atlantic In Situ Salinity Dataset

Monthly sea surface salinity (SSS) fields are constructed from observations, using objective mapping on a 1° x 1° grid in the Atlantic between 30°S and 50°N in the 1970-2016 period in an update of the dataset of Reverdin et al. Data coverage is heterogeneous, with increased density in 2002 when Argo floats become available, high density along Voluntary Observing Ship lines, and low density south of 10°S. Using lag correlation, the seasonal reemergence of SSS anomalies is investigated between 20° and 50°N in 5° x 5° boxes during the 1993-2016 period, both locally and remotely following the displacements of the deep mixed-layer waters estimated from virtual float trajectories derived from the daily AVISO surface geostrophic currents. Although SSS data are noisy, local SSS reemergence is detected in about half of the boxes, notably in the northeast and southeast, while little reemergence is seen in the central and part of the eastern subtropical gyre. In the same period, sea surface temperature (SST) reemergence is found only slightly more frequently, reflecting the short data duration. However, taking geostrophic advection into account degrades the detection of remote SSS and even SST reemergence. When anomalies are averaged over broader areas, robust evidence of a second and third SSS reemergence peak is found in the northeastern and southeastern parts of the domain, indicating long cold-season persistence of large-scale SSS anomalies, while only a first SST reemergence is seen. Finally, an oceanic reanalysis is used to confirm that the correlation analysis indeed reflects the reemergence of subsurface salinity anomalies.

54 ENVIRONMENTAL SCIENCES↗

Constructing a Merged Cloud-Precipitation Radar Dataset for Tropical Convective Clouds during the DYNAMO/AMIE Experiment at Addu Atoll

To improve understanding of the convective processes key to the Madden-Julian-Oscillation (MJO) initiation, the Dynamics of the MJO (DYNAMO) and Atmospheric Radiation Measurement MJO Investigation Experiment (AMIE) collected four months of observations from three radars, the S-band Polarization Radar (S-Pol), the C-band Shared Mobile Atmospheric Research & Teaching Radar (SMART-R), and Ka-band Zenith Radar (KAZR) on Addu Atoll in the tropical Indian Ocean. This study compares the measurements from the S-Pol and SMART-R to those from the more sensitive KAZR in order to characterize the hydrometeor detection capabilities of the two scanning precipitation radars. Frequency comparisons for precipitating convective clouds and non-precipitating high clouds agree much better than non-precipitating low clouds for both scanning radars due to issues in ground clutter. On average, SMART-R underestimates convective and high cloud tops by 0.3 to 1.1 km, while S-Pol underestimates cloud tops by less than 0.4 km for these cloud types. S-Pol shows excellent dynamic range in detecting various types of clouds and therefore its data are well suited for characterizing the evolution of the 3D cloud structures, complementing the profiling KAZR measurements. For detecting non-precipitating low clouds and thin cirrus clouds, KAZR remains the most reliable instrument. However, KAZR is attenuated in heavy precipitation and underestimates cloud top height due to rainfall attenuation 4.3% of the time during DYNAMO/AMIE. An empirical method to correct the KAZR cloud top heights is described, and a merged radar dataset is produced to provide improved cloud boundary estimates, microphysics and radiative heating retrievals.

Addu Atoll↗

Predicting discomfort from glare with pedestrian-scale lighting: A comparison of candidate models using four independent datasets

After dark, pedestrians may experience discomfort from glare caused by outdoor lighting. While several models for measuring discomfort have been proposed, there is no consensus as to which model should be used. The performances of different models were investigated using datasets from four independent studies, comparing the degree of association between model predictions and subjective ratings, and the ability of a model to distinguish between discomfort and non-discomfort situations. The models tested are those proposed by Petherbridge and Hopkinson in 1950, Schmidt-Clausen and Bindels in 1974, Bullough et al. in 2008 and Lin et al. in 2014 and 2015. They also include two quantities: direct illuminance at the eye from the glare source and average source luminance. Of the models tested, the best performance was found using either the model proposed by Bullough et al. in 2008 or by direct illuminance at the eye.

Abboushi, B.↗

Recovering complete and draft population genomes from metagenome datasets

Assembly of metagenomic sequence data into microbial genomes is of fundamental value to improving our understanding of microbial ecology and metabolism by elucidating the functional potential of hard-to-culture microorganisms. Here, we provide a synthesis of available methods to bin metagenomic contigs into species-level groups and highlight how genetic diversity, sequencing depth, and coverage influence binning success. Despite the computational cost on application to deeply sequenced complex metagenomes (e.g., soil), covarying patterns of contig coverage across multiple datasets significantly improves the binning process. We also discuss and compare current genome validation methods and reveal how these methods tackle the problem of chimeric genome bins i.e., sequences from multiple species. Finally, we explore how population genome assembly can be used to uncover biogeographic trends and to characterize the effect of in situ functional constraints on the genome-wide evolution.

59 BASIC BIOLOGICAL SCIENCES↗

SARS-CoV2 Protein-Ligand Simulation Dataset: Layer 2 (Lowest Temperature Extracted Protein Coordinate Trajectories)

Protein-only trajectories of the lowest-temperature window (310K) extracted from temperature replica-exchange molecular dynamics simulations of 23 different SARS CoV-2 systems, including S Protein ACE2-receptor binding-domain, MPro, PLPro, NSP3 ADRP (X-domain/macrodomain/phosphatase), NSP15 (endoribonuclease), NSP9, NSP10, NSP16, and N-protein N-terminus. Systems were prepared with charmm-gui and simulated using the GROMACS simulation software suite. Trajectories are provided in compressed dcd format with accompanying coordinate/topology files in pdb and psf formats. This data supplements the data release, DOI: 10.13139/OLCF/1650650 ('SARS-CoV2 Protein-Ligand Simulation Dataset: Layer 1 (Simulation Initial Conditions and Parameters)')

59 BASIC BIOLOGICAL SCIENCES↗

Spatiotemporally Registered In-Situ and Ex-Situ Datasets for Laser-based Blown Powder Directed Energy Deposition

This dataset is comprised of in situ sensing data collected during laser-based, blown powder directed energy deposition (DED) of Inconel 718 representing eight different printing conditions: (1) nominal, (2) +15% scan speed, (3) +12% laser power, (4) +42% powder feed rate, (5) +100% jerk limit, (6) +10% layer height, (7) +20% hatch spacing, (8) +20% carrier gas flow. All eight DED builds constructed an identical test coupon geometry consisting of geometric features representative of industrial print requirements (e.g., bulk deposition, thin walls, overhangs). In situ data consists of xyz-coordinates (100 Hz) and on-axis melt pool camera video (60 Hz), both of which have been temporally synchronized to spatially map the melt pool camera data. In addition, post-build X-ray computed tomography (XCT) data for each of the eight test geometries have been spatially registered to the recorded xyz-coordinates, allowing for comparisons between melt pool camera data and flaws identified in the XCT data.

additive manufacturing↗

Disk Failure Dataset from the Campaign Storage System

This dataset consists of 1,389 disk (HDD) failure events collected from the Campaign storage system at LANL. The Campaign system supported various compute platforms throughout its lifespan, including Cielo, Fire, Ice, and notably, the Trinity supercomputer. Each recorded event includes its detection timestamp (in ISO 8601 format) and details such as its location within the storage system—rack, enclosure, and drive slot number. The data, spanning from May 4, 2021, to July 25, 2023 (2 years, 2 months, and 22 days), represents failure events from the terminal years of Campaign's operational period, accounting for 26% of its total operational time.

97 MATHEMATICS AND COMPUTING↗

Dataset for manuscript "Equipartition and the temperature of maximum density of TIP4P/2005 water"

We simulate TIP4P/2005 water in the temperature range of 257 K to 318 K with time-steps 0.25, 0.50, 1.00, 2.00, and 4.00 fs. The density-temperature behavior obtained using 0.25 or 0.50 fs are in excellent agreement with each other but differ from those obtained using time-steps that have been shown earlier to lead to a breakdown of equipartition. The temperature of maximum density (TMD) is 277.15 K with time-step 0.25 or 0.50 fs, but is shifted to progressively lower values for longer time-steps, a trend that holds for different thermostat/barostat combinations. Enhancing the water-water dispersion interaction, as has been recommended for simulating disordered proteins in TIP4P/2005, degrades the description of the liquid-vapor phase envelope. We present a simple physically transparent reasoning to highlight the separation of the time-scales between translational and rotational motion. We also develop a metric, Chi, that we term the equipartition anomaly, to detect equipartition violations in simulations that include molecules that are treated as rigid objects. Calculating Chi is shown to be straightforward and sensitive to equipartition violations. A key takeaway from this study is that using sufficiently short time-steps (less than or equal to 0.5 fs) to preserve equipartition is essential for obtaining meaningful liquid water properties and for producing reliable simulation data, as correct-ensemble sampling is fundamental to ensure reproducibility across codes and simulation alogrithms. The included dataset provides the raw data used in the preparation of the graphs noted in the manuscript.

36 MATERIALS SCIENCE↗

Dataset for manuscript "Rotational Memory Function of SPC/E water"

Memory effect are essential for dynamics of condensed materials and are responsible for non-exponential relaxation of correlation functions of dynamic variables through the memory function entering the memory equation. Memory functions of dipole rotations for polar liquids have never been calculated. We present here calculations of memory functions and single-dipole rotations and of the overall system dipole moment for SPC/E water measured by dielectric spectroscopy. The memory functions for single-particle and collective dynamics turn out to be nearly identical. This result validates theories of dielectric spectroscopy in terms of single-particle time correlation function and the connection between the collective and single-particle relaxation times in terms of the Kirkwood factor. The dataset includes single particle and system dipole moments, including their time-dependence.

74 ATOMIC AND MOLECULAR PHYSICS↗

Gridded Vegetation and Land Unit Datasets over North America (1km x 1km) for E3SM Land Model, Version 2

Gridded 1 km land-surface-property dataset for Energy Exascale Earth System Model Land Model (ELM) simulations over North America. Thirty-metre NALCMS land cover is aggregated to the Daymet grid; vegetation classes are cross-walked to ELM plant functional types using mean-temperature-of-the-coldest-month (MTCO) rules. NetCDF includes PFT and land-unit fractions, counts, and MTCO.

54 ENVIRONMENTAL SCIENCES↗