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At least 505 records · Page 28

Distributed Hierarchical Contour Trees

Contour trees are a significant tool for data analysis as they capture both local and global variation. However, their utility has been limited by scalability, in particular for distributed computation and storage. We report a distributed data structure for storing the contour tree of a data set distributed on a cluster, based on a fan-in hierarchy, and an algorithm for computing it based on the boundary tree that represents only the superarcs of a contour tree that involve contours that cross boundaries between blocks. This allows us to limit the communication cost for contour tree computation to the complexity of the block boundaries rather than of the entire data set.

Carr, Hamish A↗

Manifold Learning: What, How, and Why

Manifold learning (ML), also known as nonlinear dimension reduction, is a set of methods to find the low-dimensional structure of data. Dimension reduction for large, high-dimensional data is not merely a way to reduce the data; the new representations and descriptors obtained by ML reveal the geometric shape of high-dimensional point clouds and allow one to visualize, denoise, and interpret them. This review presents the underlying principles of ML, its representative methods, and their statistical foundations, all from a practicing statistician's perspective. It describes the trade-offs and what theory tells us about the parameter and algorithmic choices we make in order to obtain reliable conclusions.

Mathematics↗

DENSS-Multiple

It takes multiple data sets from small-angle neutron scattering experiment at different contrast conditions to synthetically use DENSS algorithm (https://www.nature.com/articles/nmeth.4581) to combine all the information from each data set. As the multiple data set contains more information than a single data, all information in the multiple data set are collectively contribute to the final single synthetic structure that represents a molecular particle structure.

Qian, Shuo (000000024842828X)↗

cjohnson-LANL/GRL_Kilauea

The python routines are outlined in detail to perform the methods and results in the manuscript under review in the journal Geophysical Research Letters titled “Seismic features predict ground motions during repeating caldera collapse sequence” with LA-UR-23-33345. All routines are written in open source python and were applied to publicly available data sets. The codes formats the data into the appropriate structure required to train a boosted tree regression model. Other codes produce figure results.

Johnson, Christopher W↗

Confocal Raman Microscopy for Measuring In Situ Temperature-Dependent Structural Changes in Poly(Ethylene Oxide) Thin Films

Crystallization from the melt is a critical process governing the properties of semi-crystalline polymeric materials. While structural analyses of melting and crystallization transitions in bulk polymers have been widely reported, in contrast, those in thin polymer films on solid supports have been underexplored. Herein, in situ Raman microscopy and self-modeling curve resolution (SMCR) analysis are applied to investigate the temperature-dependent structural changes in poly(ethylene oxide) (PEO) films during melting and crystallization phase transitions. By resolving complex overlapping sets of spectra, SMCR analysis reveals that the thermal transitions of 50 µm thick PEO films comprise two structural phases: an ordered crystalline phase and a disordered amorphous phase. The ordered structure of the crystalline PEO film entirely disappears as the polymer is heated; conversely, the disordered structure of the amorphous PEO film reverts to the ordered structure as the polymer is cooled. Broadening of the Raman bands was observed in PEO films above the melting temperature (67 °C), while sharpening of bands was observed below the crystallization temperature (45 °C). The temperatures at which these spectral changes occurred were in good agreement with differential scanning calorimetry (DSC) measurements, especially during the melting transition. The results illustrate that in situ Raman microscopy coupled with SMCR analysis is a powerful approach for unraveling complex structural changes in thin polymer films during melting and crystallization processes. Furthermore, we show that confocal Raman microscopy opens opportunities to apply the methodology to interrogate the structural features of PEO or other surface-supported polymer films as thin as 2 µm, a thickness regime beyond the reach of conventional thermal analysis techniques.

Koh, Miharu [Department of Chemistry, University o↗

Wind Turbine Sound Setbacks and Supply Curves: Ordinances and Extrapolated Trends, 110 Hub Height, 130 Rotor Diameter

This dataset provides a comprehensive set of wind turbine sound setbacks from every residential structure in the contiguous United States (CONUS). A sound setback is defined as the minimum required distance between a residential structure and a hypothetical turbine installation site to ensure that modeled sound levels received at the residence do not exceed local sound ordinances, which are commonly expressed in A-weighted decibels (dBA). Therefore, sound setbacks are a local spatial assessment combining multiple factors, including the sound pressure curve as a function of the observer location (distance and direction) relative to the turbine, local sound regulations, and the geographical distribution of residential structures. The dataset is organized into multiple scenario-based products, detailed as follows: 1. Existing and extrapolated sound setbacks. An existing scenario characterizes sound setbacks only in states or counties that have implemented sound regulations as of 2022. The extrapolated scenarios extend a constant sound threshold to counties that lack explicit sound regulations, with thresholds ranging from 35 to 60 dBA, in 5-dBA increments reflecting the variation observed in current sound ordinances. 2. Sound setbacks in directional and worst scenarios. The directional scenario accounts for the distance and orientation of residential structures relative to a hypothetical turbine location, utilizing the turbine's sound emissions in that specific direction. In contrast, the worst scenario takes loudest sound level at each distance step from the turbine, irrespective of directional considerations, which aligns with current industry practice. 3. Supply curves for Open and Reference Access scenarios. This dataset includes supply curves generated by the reV model, which integrates each of the above sound setbacks into both Open and Reference siting scenarios. In addition, two Open and Reference baselines scenarios were included which do not consider sound setbacks for comparative analysis. All sound setback data are stored in TIF files, with partial maps of the data provided in PNG format. The values in the sound setback raster range from 0 to 1, representing the fraction of developable land within a 90 meter by 90 meter pixel due to sound ordinances. A value of 0 indicates areas where wind energy development is prohibited, while a value of 1 signifies areas fully permissible. The wind turbine parameters used in the sound modeling are based on the land-based turbine from International Energy Agency (IEA), featuring a rated electrical power of 3.4 MW, a rotor diameter of 130 meters, and a hub height of 110 meters. The atmospheric conditions, including wind speed/direction, turbulence, air temperature, relative humidity, and air pressure, that drive the sound generation are obtained from the WIND Toolkit dataset.

Array↗

Properties of Gaseous Deprotonated L-Cysteine S-Sulfate Anion [cysS-SO3]−: Intramolecular H-Bond Network, Electron Affinity, Chemically Active Site, and Vibrational Fingerprints

L-cysteine S-sulfate, Cys-SSO3H, and their derivatives play essential roles in biological chemistry and pharmaceutical synthesis, yet their intrinsic molecular properties have not been studied to date. In this contribution, the deprotonated anion [cysS-SO3]− was introduced in the gas phase by electrospray and characterized by size-selected, cryogenic, negative ion photoelectron spectroscopy. The electron affinity of the [cysS-SO3]• radical was determined to be 4.95 ± 0.10 eV. In combination with theoretical calculations, it was found that the most stable structure of [cysS-SO3]− (S1) is stabilized via three intramolecular hydrogen bonds (HBs); i.e., one O-H……N between the -COOH and -NH2 groups, and two N-H……O HBs between -NH2 and -SO3, in which the amino group serves as both HB acceptor and donor. In addition, a nearly iso-energetic conformer (S2) with the formation of an O-H……N-H……O-S chain-type binding motif competes with S1 in the source. The most reactive site of the molecule susceptible for electrophilic attacks is the linkage S atom. Theoretically predicted infrared spectra indicate that O-H and N-H stretching modes are the fingerprint region (2800 to 3600 cm−1) to distinguish different isomers. The obtained information lays out a foundation to better understand the transformation and structure–reactivity correlation of Cys-SSO3H in biologic settings.

74 ATOMIC AND MOLECULAR PHYSICS↗

The Exploration of Local VolumE Satellites (ELVES) Survey: A Nearly Volume-limited Sample of Nearby Dwarf Satellite Systems

We present the final sample of the Exploration of Local VolumE Satellites (ELVES) survey, a survey of the dwarf satellites of a nearly volume-limited sample of Milky Way (MW)-like hosts in the Local Volume. Hosts are selected simply via a cut in luminosity (${M}_{{K}_{s}}\lt -22.1$ mag) and distance (D < 12 Mpc). We cataloged the satellites of 25 of the 31 such hosts, with another five taken from the literature. All hosts are surveyed out to at least 150 projected kpc ( ~ R vir /2), with the majority surveyed to 300 kpc ( ~ R vir ). Satellites are detected using a consistent semiautomated algorithm specialized for low surface brightness dwarfs. As shown through extensive tests with injected galaxies, the catalogs are complete to M V ~ -9 mag and μ 0,V ~ 26.5 mag arcsec -2 . Candidates are confirmed to be real satellites through distance measurements including redshift, tip of the red giant branch, and surface brightness fluctuations. Across all 30 surveyed hosts, there are 338 confirmed satellites with M V < -9 mag, with a further 106 candidates awaiting distance measurement. For the vast majority of these, we provide consistent multiband Sérsic photometry. We show that satellite abundance correlates with host mass, with the MW being quite typical among comparable systems, and that satellite quenched fraction rises steeply with decreasing satellite mass, mirroring the quenched fraction for the MW and M31. The ELVES survey represents a massive increase in the statistics of surveyed systems with known completeness, and the provided catalogs are a unique data set to explore various aspects of small-scale structure and dwarf galaxy evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

The quenching of galaxies, bulges, and disks since cosmic noon

Here, we present an analysis of the quenching of star formation in galaxies, bulges, and disks throughout the bulk of cosmic history, from z = 2 – 0. We utilise observations from the Sloan Digital Sky Survey and the Mapping Nearby Galaxies at Apache Point Observatory survey at low redshifts. We complement these data with observations from the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey at high redshifts. Additionally, we compare the observations to detailed predictions from the LGalaxies semi-analytic model. To analyse the data, we developed a machine learning approach utilising a Random Forest classifier. We first demonstrate that this technique is extremely effective at extracting causal insight from highly complex and inter-correlated model data, before applying it to various observational surveys. Our primary observational results are as follows: at all redshifts studied in this work, we find bulge mass to be the most predictive parameter of quenching, out of the photometric parameter set (incorporating bulge mass, disk mass, total stellar mass, and B/T structure). Moreover, we also find bulge mass to be the most predictive parameter of quenching in both bulge and disk structures, treated separately. Hence, intrinsic galaxy quenching must be due to a stable mechanism operating over cosmic time, and the same quenching mechanism must be effective in both bulge and disk regions. Despite the success of bulge mass in predicting quenching, we find that central velocity dispersion is even more predictive (when available in spectroscopic data sets). In comparison to the LGalaxies model, we find that all of these observational results may be consistently explained through quenching via preventative ‘radio-mode’ active galactic nucleus feedback. Furthermore, many alternative quenching mechanisms (including virial shocks, supernova feedback, and morphological stabilisation) are found to be inconsistent with our observational results and those from the literature.

79 ASTRONOMY AND ASTROPHYSICS↗

GMFOLD: Subgraph matching for high-throughput DNA-aptamer secondary structure classification and machine learning interpretability

Aptamers are oligonucleotide receptors that bind to their targets with high affinity. Here, we consider aptamers comprised of single-stranded DNA that undergo target-binding-induced conformational changes, giving rise to unique secondary and tertiary structures. Given a specific aptamer primary sequence, there are well-established computational tools (notably mfold) to predict the secondary structure via free energy minimization algorithms. While mfold generates secondary structures for individual sequences, there is a need for a high-throughput process whereby thousands of DNA structures can be predicted in real-time for use in an interactive setting, when combined with aptamer selections that generate candidate pools that are too large to be experimentally interrogated. We developed a new Python code for high-throughput aptamer secondary structure determination (GMfold). GMfold uses subgraph matching methods to group aptamer candidates by secondary structure similarities. We also improve an open-source code, SeqFold, to incorporate subgraph matching concepts. We represent each secondary structure as a lowest-energy bipartite subgraph matching of the DNA graph to itself. These new tools enable thousands of DNA sequences to be compared based on their secondary structures, using machine-learning algorithms. This process is advantageous when analyzing sequences that arise from aptamer selections via systematic evolution of ligands by exponential enrichment (SELEX). This work is a building block for future machine-learning-informed DNA-aptamer selection processes to identify aptamers with improved target affinity and selectivity and advance aptamer biosensors and therapeutics.

Aptamer↗

Seismic Performance of Deeply Embedded Conceptual Advanced Reactors: Three-Dimensional Nonlinear Soil-Structure Interaction Analyses

The U.S. Nuclear Regulatory Commission’s functional containment concept provides advanced nuclear power plant designers with more flexibility in terms of the civil/structural design if the appropriate set of barriers for prevention of radioactive material release exist. Some of the conceptual advanced reactor structures, without the traditional pressure boundaries of large containment structures, are proposed to be deeply embedded or buried into soil. This approach is expected to provide (1) lesser seismic demands on the structures and safety-critical structures, (2) eased regulatory efforts and overall design against other external hazards such as aircraft impact, and (3) overall cost savings. Further, one of the important aspects of assessing the technical and economic viability of deeply embedding advanced reactor buildings is to assess the seismic performance with the understanding of effects with material and geometric nonlinearities. This study investigates the seismic response of deeply embedded or buried advanced reactors by conducting three-dimensional nonlinear soil-structure interaction analyses. Although the results indicate that there is a general trend of decreased seismic response with increased embedment depths, the change in the dynamic environment with different embedment depths and the nonlinear environment under high-intensity seismic inputs may result in increased peak response at increased embedment depths.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

ASME Design Code Rule Changes for Nuclear Graphite

The American Society of Mechanical Engineers Boiler Pressure and Vessel Code (ASME BPVC) Section III, Division 5, Article HHA-3000 outlines graphite core component and graphite core assembly design guidelines. Graphite core components are defined as ?components manufactured from graphite that are installed to form a graphite core assembly within the reactor pressure vessel of a high temperature, graphite moderated fission reactor.? (p. 413) Graphites? inherent defect distributions do not allow for deterministic material reliability. Rather, graphite has variable strength distributions which change by grade. Article HHA-3000 outlines two semi-probabilistic methods, the full and simplified assessments, which set design load limit targets for each of three component structural reliability classes. The Design Task Group was officially recognized as a specialized task group within ASME November of 2023, though we?ve been collaborating since 2022. The purpose of the Design Task Group is to correct, clarify, and make HHA-3000 function as intended. The Design Task Group will sunset once we?ve achieved our objectives. The Design Task Group was specifically told to not write new Code. While there may be more precise and more accurate methods to determine reliability targets, the current methods are conservative, relatively simple to implement, and have thus far been considered satisfactory for setting design reliability targets. Much of the ground-work to write proposal files and background documents for records to make the changes needed to achieve our objective have been completed. The Design Task Group has documented much of their work through papers, presentations, and memorandums. Three memorandums in which INL team members had substantial contributions are found in the Appendices: FEA Modeling for the Baseline Program, Evaluating the Effects on Margin of Updating the Threshold and Shape Parameters in the Full Assessment, and Interpretations of the Full and Simplified Assessments in ASME BPVC. Most of the on-going work to achieve the Design Task Group?s objective will be addressing comments on existing records and moving records through the balloting process. The Design Task Group met bi-weekly mostly through the end of FY2023. Since February 2024, the Design Task Group has mostly been completed with solving and documenting the technical issues associated with the assessments. Unless new tasks are identified, the remaining work of the Design Task Group will be political and editorial.

97 MATHEMATICS AND COMPUTING↗

Improving scalability of electronic structure code for molecular simulations in the presence of environment

A scalable density functional electronic code with Gaussian basis set, called UTEP-NRLMOL, is developed to perform simulations of molecular systems in the presence of the environment with particular attention to the memory requirements. In the electronic structure calculations, the memory and computation time are proportional to the number of atoms. Memory requirements for density functional calculations scale as N*N, where N is the number of atoms. While the recent advances in HPC offer platforms with large numbers of cores, the limited amount of memory available on a given node and poor scalability of the electronic structure codes hinder their efficient usage of these platforms. We have introduced new scaling and parallelization paradigms using MPI-3 shared-memory functionality combined with usage of sparse algebra and storage of matrices in sparse format. This extends the range of applicability of the UTEP-NRLMOL code to large systems over 10,000 atoms, or using up to 67,000 basis functions, and making use of HPC architectures using over 6,000 processors utilizing all available cores. We have also interfaced code with effective fragment potential and polarizable continuum model libraries. The code was used in simulations of several applications which are published in reputed scientific journals.

74 ATOMIC AND MOLECULAR PHYSICS↗

A Comparison of Three Neodymium Atomic Data Sets for Kilonova Modeling

We examine the impact of input neodymium (Nd) atomic data on the light curves and spectra of kilonovae (KNe), probing the sensitivity of kilonova observables to the atomic physics of this important lanthanide element. We use the SuperNu Monte Carlo radiative transfer code, simulating a simple semianalytic 1D kilonova (KN) with a pure Nd atmosphere, fixing the radiative transfer method while using input atomic data generated by three different codes: the LANL suite of atomic physics codes, HULLAC, and Autostructure. We see that the choice of atomic data significantly shapes the resulting light curves and spectra. Peak bolometric luminosities differ by a ratio of nearly 1.5 between HULLAC/Autostructure and LANL data sets. Moreover, we observe significant near- to mid-IR differences in the structure of the spectra. We specifically attribute these differences to the choice of atomic data for neutral Nd I. Many of the results here have been adapted from a presentation at “Radiative Transfer and Atomic Physics of Kilonovae” in Stockholm, 2023. We additionally present a LANL data set with energies calibrated to available values in the NIST Atomic Spectra Database, and demonstrate that this calibration also significantly affects IR spectral structure at late time. The substantial differences in KN observables that arise from tuning the atomic data of just one lanthanide element highlight the special attention that must be paid to atomic physics uncertainties when modeling KNe, from AT2017gfo to beyond.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Utah FORGE: Composite 3D Seismic Velocity Model

This is a composite 3D seismic velocity that was constructed from compiled information from several local studies regarding seismic velocities and structural information. This seismic velocity model is provided in NonLinLoc format (slow_len), which is readily usable in NonLinLoc software. Other model formats and versions of the model can be produced using the Python script provided with this data set. Details on how the model was created and prior velocity and structural information was used is provided in the accompanying documentation.

15 GEOTHERMAL ENERGY↗

Structural regulation-induced Li-electron disentanglement for stabilized oxygen redox of Li-excess disordered rock-salt cathode materials

Since the discovery of its electrochemical activity, Li-excess disordered rock-salt (DRX) cathode material has received worldwide attention as it sets up a new way to exploit oxygen redox beyond the conventional layered structure with late-3d transition metals. However, the intricate structure-function relationship in the disordered lattice of the DRX material fogs the researcher's lens on the underlying redox mechanisms. Here, in this study, we employ a synergistic approach combining neutron total scattering with reverse Monte Carlo modeling and density functional theory calculations to unravel the landscape of oxygen redox reactions in DRX. Redox activities are evaluated in diverse oxygen clusters (OLi x TM 6-x ) and the spatial distribution of these clusters in the model DRX structure (Li 1.16 Ti 0.37 Ni 0.37 Nb 0.1 O 2 and Li 1.2 Ti 0.35 Ni 0.35 Nb 0.1 O 1.8 F 0.2 ) is explicitly determined. The results unveil that by regulating the short-range ordering between cations, fluorine atoms can effectively decouple the location of Li extraction and electron depletion. Such disentanglement between the Li reservoir and electron reservoir in the DRX lattice could play a pivotal role in protecting the oxidized oxygen and preserving the lattice framework during cycling. Through a tentatively designed non-fluorinated DRX oxide realizing similar Li-electron decoupling, an obvious enhancement of the cycling capability can be achieved without compromising the capacity release.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ELSI — An open infrastructure for electronic structure solvers

Routine applications of electronic structure theory to molecules and periodic systems need to compute the electron density from given Hamiltonian and, in case of non-orthogonal basis sets, overlap matrices. System sizes can range from few to thousands or, in some examples, millions of atoms. Different discretization schemes (basis sets) and different system geometries (finite non-periodic vs. infinite periodic boundary conditions) yield matrices with different structures. The ELectronic Structure Infrastructure (ELSI) project provides an open-source software interface to facilitate the implementation and optimal use of high-performance solver libraries covering cubic scaling eigensolvers, linear scaling density-matrix-based algorithms, and other reduced scaling methods in between. In this paper, we present recent improvements and developments inside ELSI, mainly covering (1) new solvers connected to the interface, (2) matrix layout and communication adapted for parallel calculations of periodic and/or spin-polarized systems, (3) routines for density matrix extrapolation in geometry optimization and molecular dynamics calculations, and (4) general utilities such as parallel matrix I/O and JSON output. The ELSI interface has been integrated into four electronic structure code projects (DFTB+, DGDFT, FHI-aims, SIESTA), allowing us to rigorously benchmark the performance of the solvers on an equal footing. Based on results of a systematic set of large-scale benchmarks performed with Kohn–Sham density-functional theory and density-functional tight-binding theory, we identify factors that strongly affect the efficiency of the solvers, and propose a decision layer that assists with the solver selection process. As a result, we describe a reverse communication interface encoding matrix-free iterative solver strategies that are amenable, e.g., for use with planewave basis sets.

97 MATHEMATICS AND COMPUTING↗

Significance of pH and iron-sulfur chemistry for molybdenum sequestration under sulfidic conditions

Molybdenum (Mo), a redox-sensitive trace metal, plays an important role in recording ancient oxygenation and deoxygenation events as a paleoredox proxy. The mobility and reactivity of Mo in aqueous conditions are closely tied to the chemistry of reduced sulfur and iron species. However, our current knowledge on the formation, structure, stability, and condensation pathways of FeMoS clusters in aqueous settings remains limited, which has driven the current study. In this study, we conducted systematic experiments investigating the interactions between dissolved Mo (initially introduced as molybdate, MoO 4 2– , or tetrathiomolybdate, MoS 4 2– ), ferrous iron (Fe 2+ ), and sulfide (ΣH 2 S aq ) in variously defined abiotic sulfidic systems to determine the external conditions (i.e., pH, and reactant concentrations and ratios) necessary for the formation of solid-phase Fe-Mo sulfides. Solution samples of each system were monitored using ultraviolet-visible spectroscopy (UV–vis) to track the degree of thiolation of dissolved Mo species. Precipitates were analyzed using X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) to determine their elemental compositions and valences, and structure (i.e., crystalline or amorphous), respectively. All FeMoS precipitates were amorphous and contained 76–90% Mo(IV) and 10–24% Mo(V) with a trend toward lower Mo(IV):Mo(V) ratios with increasing pH. The degree of Mo thiolation, which was strongly dependent on solution pH and Fe 2+ concentrations, greatly affected the amount of Mo sequestered (i.e., an increased degree of Mo thiolation in solution led to an increased amount of Mo in the final FeMoS precipitate). Furthermore, these findings suggest that changes in pH and Fe 2+ concentrations may be responsible for the sulfide-independent variations in Mo behavior observed in euxinic basins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗