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At least 703 records · Page 39

Temporal variation in skin microbiota of cohabitating amphibians

Temporal changes and transmission patterns in host-associated microbial communities have important implications for host health. The diversity of amphibian skin microbial communities is associated with disease outcome in amphibians exposed to the fungal pathogen Batrachochytrium dendrobatidis (Bd). To successfully develop conservation strategies against Bd, we need a comprehensive understanding of how skin microbes are maintained and transmitted over time within populations. Here we used 16S rRNA sequence analysis to compare Epipedobates anthonyi frogs housed with one conspecific to frogs housed singly at four time points over the course of 1 year. We found that both α and β diversity of frog skin bacterial communities changed significantly over the course of the experiment. Specifically, we found that bacterial communities of cohabitating frogs became more similar over time. We also observed that some bacterial taxa were differentially abundant between frogs housed singly and frogs housed with a conspecific. These results suggest that conspecific contact may play a role in mediating amphibian skin microbial diversity and that turnover of skin microbial communities can occur across time. Our findings provide rationale for future studies exploring horizontal transmission as a potential mechanism of host-associated microbial maintenance in amphibians.

59 BASIC BIOLOGICAL SCIENCES↗

Supporting the future nuclear workforce with computer-based procedures

Here we see that computer-based tools have dramatically increased ease and efficiency of everyday tasks. Gone are the days of paging through a paper catalog, transcribing product numbers, and calculating totals. Today, a consumer can find a product online with a simple search engine, and then purchase it in a matter of a few clicks. Paper catalogs have their place, but it is hard to imagine life without on-line shopping sites. All tasks conducted in a nuclear power plant are guided by procedures, which helps ensure safe and reliable operation of the plants. One prominent goal of the nuclear industry is to minimize the risk of human errors. To achieve this goal one has to ensure tasks are correctly and consistently executed. This is partly achieved by training and by a structured approach to task execution, which is provided by procedures and work instructions. Procedures are used in the nuclear industry to direct workers' actions in a proper sequence. The governing idea is to minimize the reliance on memory and choices made in the field. However, the procedure document may not contain sufficient information to successfully complete the task. Therefore, the worker might have to carry additional documents such as turnover sheets, operation experience, drawings, and other procedures to the work site. The nuclear industry is operated with paper procedures like paper catalogs of the past. A field worker may carry a large stack of documents needed to complete a task to the field. Even though the paper process has helped keep the industry safe for decades, there are limitations to using paper. Paper procedures are static (i.e., the content does not change after the document is printed), difficult to search, and rely heavily on the field worker’s situational awareness and ability to consistently meet the high expectation of human performance excellence. With computer-based procedures (CBPs) that stack of papers may be reduced to the size of a small tablet or even a smart phone. Instead of manually matching equipment identification numbers listed in the procedure with the number on the physical equipment the field worker can simply scan a barcode to ensure the correct valve is opened while simultaneously creating a record. Instead of navigating through a maze of cross-references, CBPs enable intelligent work path navigation which accounts for past decisions and observation, thereby enabling more efficient and safe task completion.

47 OTHER INSTRUMENTATION↗

Enabling Real-time Scattering Data Analysis with Scalable Optimization [Slides]

Diffraction experiments produce datasets with rich multidimensional physics information such as microstructure, equations of state, crystal structure, elastoplastic properties, and other key inputs to LANL mission-essential multiphysics models. This information is typically extracted through a process called Rietveld refinement, which involves selecting appropriate models of the instrument, crystal structure, and microstructure, identifying suitable starting values, and then fitting often hundreds of model parameters using a sequence of empirical parameter turnon/off sequences within a non-global gradient-based optimization. Extensive user expertise is required to properly setup a refinement, identify appropriate models, and select initial parameter values close to truth, such that the refinement will yield parameter values that are optimally predictive. This is a very tedious manual process performed far after the beamline campaign has ended. As facilities have become capable of generating larger volumes of data, the limitation in throughput due to Rietveld refinement has led to a dramatic increase in unanalyzed data as opposed to an intended increase in new science. In our FY22 TED, we demonstrated an integrated toolset providing near real-time automated Rietveld analysis. If this toolset can be optimized to provide automated Rietveld analysis in real-time, this could alleviate the bottleneck in unanalyzed diffraction data, aid in decision-making during experiments, and increase efficiency of the facility.

74 ATOMIC AND MOLECULAR PHYSICS↗

Development of SAM Code Capabilities for Safety Analysis of GCR Air-ingress Events

Air-ingress following a depressurized loss-of-forced-cooling (DLOFC) event is a challenging, multiphysics safety scenario for High-Temperature Gas-Cooled Reactors (HTGRs), involving coupled gas composition transport, buoyancy-driven flow redistribution, graphite oxidation, and structural heat-up. Despite its importance — air ingress is a key scenario identified in the PIRT process for the HTGRs — existing system-level safety codes have lacked the integrated capability to simulate the complete event sequence with high confidence. This report documents the development, validation, and demonstration of three new capabilities in the SAM code to address this gap: (1) a multi-component gas mixture flow model with binary diffusion to track the helium-air composition and its effect on system density and flow; (2) a 0-D graphite oxidation model based on the Roes correlation, including oxygen consumption and exothermic heat release; and (3) an isentropic critical flow model for accurate representation of primary system depressurization through a break. These capabilities are validated against two benchmark experiments. The NSTF heavy-gas ingress experiment validates the multi-component flow model: SAM correctly reproduces the rapid buoyancydriven flow stagnation and subsequent natural circulation recovery driven by composition-dependent density changes. The NACOK graphite oxidation experiment validates the oxidation model: SAM predicts a bottom-level graphite weight loss of 25%, in close agreement with the measured 24%, and reproduces the strong axial nonuniformity and block-geometry dependence of oxidation, at a level comparable to the SPECTRA and TINTE codes. The validated capabilities are then exercised together in an integrated, reactor-scale simulation of a DLOFC air-ingress transient in a simplified HTR-PM pebble-bed reactor. In a single calculation spanning approximately 8 days, SAM reproduces the complete accident sequence: rapid depressurization, densityand diffusion-driven air ingress over ˜15 hours, onset of buoyancy-driven natural circulation, exothermic graphite oxidation with a peak fuel temperature at ˜62 hours, and eventual passive cooldown. These results demonstrate that SAM now provides the nuclear community with a preliminarily validated, modern systemlevel tool for HTGR air-ingress safety analysis, filling a recognized capability gap. Future extensions to broaden species tracking, improve oxidation chemistry, and refine the reactor model are discussed.

Yang, Gang↗

Multiscale dynamic experiments on fiber-reinforced composites with damage assessment using high-speed synchrotron X-ray phase-contrast imaging

We report fiber-reinforced composites (FRCs) have been widely used as protection materials to replace heavier metals. However, predictive capabilities for the impact-induced failure of FRCs have not been well-developed. In this work, we introduced an integrated technique to visualize the dynamic failure of FRCs, with the modified Kolsky bar loading and the high-speed synchrotron X-ray phase-contrast imaging (PCI). We summarize our experimental studies across the FRCs’ structural levels by using this integrated technique, including single-fiber tensile experiments, fiber/matrix debonding experiments, and single-edge notched bending experiments on composite laminates. It is revealed that the high-speed synchrotron X-ray PCI technique possesses sufficient spatial resolution to identify the failure behavior of a single fiber in the 10-μm scale level, as well as temporal resolution to identify the time sequence of internal dynamic damage evolution. The technique can penetrate through the opaque composite sample and provide real-time visualization of small-scale damaging mechanisms such as the embedded fiber’s sliding in the matrix and the fiber’s transverse debonding with the matrix. At an expanding scale, the technique can identify the crack initiation and track the cracking behavior inside a single ply or between different plies of a composite laminate. High-speed visualization inside the material by this integrated technique provides critical deformation and failure information to develop physical understanding of the damage inside composites under impact.

47 OTHER INSTRUMENTATION↗

Mapping Composition Evolution through Synthesis, Purification, and Depolymerization of Random Heteropolymers

Random heteropolymers (RHPs) consisting of three or more comonomers have been routinely used to synthesize functional materials. While increasing the monomer variety diversifies the side-chain chemistry, this substantially expands the sequence space and leads to ensemble-level sequence heterogeneity. Most studies have relied on monomer composition and simulated sequences to design RHPs, but the questions remain unanswered regarding heterogeneities within each RHP ensemble and how closely these simulated sequences reflect the experimental outcomes. Here, we quantitatively mapped out the evolution of monomer compositions in four-monomer-based RHPs throughout a design-synthesis-purification-depolymerization process. By adopting a Jaacks method, we first determined 12 reactivity ratios directly from quaternary methacrylate RAFT copolymerization experiments to account for the influences of competitive monomer addition and the reversible activation/deactivation equilibria. The reliability of in silico analysis was affirmed by a quantitative agreement (<4% difference) between the simulated RHP compositions and the experimental results. Furthermore, we mapped out the conformation distribution within each ensemble in different solvents as a function of monomer chemistry, composition, and segmental characteristics via high-throughput computation based on self-consistent field theory (SCFT). These comprehensive studies confirmed monomer composition as a viable design parameter to engineer RHP-based functional materials as long as the reactivity ratios are accurately determined and the livingness of RHP synthesis is ensured.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SUPPRESSION OF DIELECTRONIC RECOMBINATION DUE TO FINITE DENSITY EFFECTS

We have developed a general model for determining density-dependent effective dielectronic recombination (DR) rate coefficients in order to explore finite-density effects on the ionization balance of plasmas. Our model consists of multiplying by a suppression factor those highly-accurate total zero-density DR rate coefficients which have been produced from state-of-the-art theoretical calculations and which have been benchmarked by experiment. The suppression factor is based upon earlier detailed collision-radiative calculations which were made for a wide range of ions at various densities and temperatures, but used a simplified treatment of DR. A general suppression formula is then developed as a function of isoelectronic sequence, charge, density, and temperature. These density-dependent effective DR rate coefficients are then used in the plasma simulation code Cloudy to compute ionization balance curves for both collisionally ionized and photoionized plasmas at very low (n{sub e} = 1 cm{sup -3}) and finite (n{sub e} = 10{sup 10} cm{sup -3}) densities. We find that the denser case is significantly more ionized due to suppression of DR, warranting further studies of density effects on DR by detailed collisional-radiative calculations which utilize state-of-the-art partial DR rate coefficients. This is expected to impact the predictions of the ionization balance in denser cosmic gases such as those found in nova and supernova shells, accretion disks, and the broad emission line regions in active galactic nuclei.

79 ASTRONOMY AND ASTROPHYSICS↗

Adaptation to Environmental Extremes Structures Functional Traits in Biological Soil Crust and Hypolithic Microbial Communities

Biological soil crusts (biocrusts) are widespread in drylands and deserts. At the microhabitat scale, they also host hypolithic communities that live under semitranslucent stones. Both environmental niches experience exposure to extreme conditions such as high UV radiation, desiccation, temperature fluctuations, and resource limitation. However, hypolithic communities are somewhat protected from extremes relative to biocrust communities. Conditions are otherwise similar, so comparing them can answer outstanding questions regarding adaptations to environmental extremes. Using metagenomic sequencing, we assessed the functional potential of dryland soil communities and identified the functional underpinnings of ecological niche differentiation in biocrusts versus hypoliths. We also determined the effect of the anchoring photoautotroph (moss or cyanobacteria). Genes and pathways differing in abundance between biocrusts and hypoliths indicate that biocrust communities adapt to the higher levels of UV radiation, desiccation, and temperature extremes through an increased ability to repair damaged DNA, sense and respond to environmental stimuli, and interact with other community members and the environment. Intracellular competition appears to be crucial to both communities, with biocrust communities using the Type VI Secretion System (T6SS) and hypoliths favoring a diversity of antibiotics. The dominant primary producer had a reduced effect on community functional potential compared with niche, but an abundance of genes related to monosaccharide, amino acid, and osmoprotectant uptake in moss-dominated communities indicates reliance on resources provided to heterotrophs by mosses. Our findings indicate that functional traits in dryland communities are driven by adaptations to extremes and we identify strategies that likely enable survival in dryland ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

Meld: A project for exploring how to meet DUNE's framework needs

Existing data-processing frameworks for HEP experiments are largely based on collider-physics concepts, which may be based on rigid, event-based data hierarchies. These data organizations are not always helpful for neutrino experiments, which must sometimes work around such restrictions by manually splitting apart events into constructs that are better suited for neutrino physics. The purpose of Meld is to explore more flexible data organizations by treating a frameworks job as: (1) A graph of data-product sequences connected by (2) User-defined functions that serve as operations to (3) Framework-provided higher-order functions.

Knoepfel, KyleJ. [Fermi National Accelerator Labor↗

Fermilab experience of post-annealing losses in SRF niobium cavities due to furnace contamination and the ways to its mitigation: a pathway to processing simplification and quality factor improvement

We investigate the effect of high temperature treatments followed by only high-pressure water rinse (HPR) of superconducting radio frequency (SRF) niobium cavities. The objective is to provide a cost effective alternative to the typical cavity processing sequence, by eliminating the material removal step post furnace treatment while preserving or improving the RF performance. The studies have been conducted in the temperature range 800-1000C for different conditions of the starting substrate: large grain and fine grain, electro-polished (EP) and centrifugal barrel polished (CBP) to mirror finish. An interesting effect of the grain size on the performances is found. Cavity results and samples characterization show that furnace contaminants cause poor cavity performance, and a practical solution is found to prevent surface contamination. Extraordinary values of residual resistances ~ 1 nOhm and below are then consistently achieved for the contamination-free cavities. These results lead to a more cost-effective processing and improved RF performance, and, in conjunction with CBP, open a potential pathway to acid-free processing.

43 PARTICLE ACCELERATORS↗

Multilevel Monte Carlo methods for the Grad-Shafranov free boundary problem

The equilibrium configuration of a plasma in an axially symmetric reactor is described mathematically by a free boundary problem associated with the celebrated Grad-Shafranov equation. The presence of uncertainty in the model parameters introduces the need to quantify the variability in the predictions. This is often done by computing a large number of model solutions on a computational grid for an ensemble of parameter values and then obtaining estimates for the statistical properties of solutions. In this study, we explore the savings that can be obtained using multilevel Monte Carlo methods, which reduce costs by performing the bulk of the computations on a sequence of spatial grids that are coarser than the one that would typically be used for a simple Monte Carlo simulation. We examine this approach using both a set of uniformly refined grids and a set of adaptively refined grids guided by a discrete error estimator. Numerical experiments show that multilevel methods dramatically reduce the cost of simulation, with cost reductions typically on the order of 60 or more and possibly as large as 200. Furthermore, adaptive griding results in more accurate computation of geometric quantities such as x-points associated with the model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Unique nucleotide sequence-guided assembly of repetitive DNA parts for synthetic biology applications

Recombination-based DNA construction methods, such as Gibson assembly, have made it possible to easily and simultaneously assemble multiple DNA parts, and they hold promise for the development and optimization of metabolic pathways and functional genetic circuits. Over time, however, these pathways and circuits have become more complex, and the increasing need for standardization and insulation of genetic parts has resulted in sequence redundancies-for example, repeated terminator and insulator sequences-that complicate recombination-based assembly. We and others have recently developed DNA assembly methods, which we refer to collectively as unique nucleotide sequence (UNS)-guided assembly, in which individual DNA parts are flanked with UNSs to facilitate the ordered, recombination-based assembly of repetitive sequences. Here we present a detailed protocol for UNS-guided assembly that enables researchers to convert multiple DNA parts into sequenced, correctly assembled constructs, or into high-quality combinatorial libraries in only 2-3 d. If the DNA parts must be generated from scratch, an additional 2-5 d are necessary. This protocol requires no specialized equipment and can easily be implemented by a student with experience in basic cloning techniques.

Torella, JP↗

Compression rate effects on the Bi-III stability field in dynamic diamond anvil cell XFEL studies of bismuth

This study aims to resolve conflicting observations of bismuth’s high-pressure phase transitions across static, intermediate, and shock compression regimes. We probed its high-pressure structural sequence using the dynamic diamond anvil cell with and time-resolved X-ray diffraction with microsecond resolution at an X-ray free-electron laser. At room temperature and pressures up to 20 gigapascals, bismuth evolves through the same structural sequence previously identified under static compression. However, the transformation behavior differs in important ways under dynamic loading. In particular, the transition from the incommensurate intermediate-pressure phase to the high symmetry high pressure phase begins at pressures about 2 to 4 gigapascals lower than in static experiments, and the onset of this transformation depends on the compression rate. As a result, the stability field of the intermediate-pressure phase is reduced under rapid compression. Our results suggest that at sufficiently fast loading rates the intermediate phase may be bypassed entirely, consistent with previous shock-compression observations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Complexation behavior of oppositely charged polyelectrolytes: Effect of charge distribution

Complexation behavior of oppositely charged polyelectrolytes in a solution is investigated using a combination of computer simulations and experiments, focusing on the influence of polyelectrolyte charge distributions along the chains on the structure of the polyelectrolyte complexes. The simulations are performed using Monte Carlo with the replica-exchange algorithm for three model systems where each system is composed of a mixture of two types of oppositely charged model polyelectrolyte chains (EGEG){sub 5}/(KGKG){sub 5}, (EEGG){sub 5}/(KKGG){sub 5}, and (EEGG){sub 5}/(KGKG){sub 5}, in a solution including explicit solvent molecules. Among the three model systems, only the charge distributions along the chains are not identical. Thermodynamic quantities are calculated as a function of temperature (or ionic strength), and the microscopic structures of complexes are examined. It is found that the three systems have different transition temperatures, and form complexes with different sizes, structures, and densities at a given temperature. Complex microscopic structures with an alternating arrangement of one monolayer of E/K monomers and one monolayer of G monomers, with one bilayer of E and K monomers and one bilayer of G monomers, and with a mixture of monolayer and bilayer of E/K monomers in a box shape and a trilayer of G monomers inside the box are obtained for the three mixture systems, respectively. The experiments are carried out for three systems where each is composed of a mixture of two types of oppositely charged peptide chains. Each peptide chain is composed of Lysine (K) and glycine (G) or glutamate (E) and G, in solution, and the chain length and amino acid sequences, and hence the charge distribution, are precisely controlled, and all of them are identical with those for the corresponding model chain. The complexation behavior and complex structures are characterized through laser light scattering and atomic force microscopy measurements. The order of the apparent weight-averaged molar mass and the order of density of complexes observed from the three experimental systems are qualitatively in agreement with those predicted from the simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hedgehog–FGF signaling axis patterns anterior mesoderm during gastrulation

Significance Anterior–posterior axis patterning is a fascinating but poorly understood developmental process. Single-cell sequencing was utilized to interrogate patterning abnormalities in a mesoderm-specific Hedgehog (Hh) pathway mutant, which revealed selective anterior mesoderm defects. We found that Hh signaling was required for fibroblast growth factor (FGF) pathway activity in nascent mesoderm during gastrulation. Mouse genetics, cell biology, and genomic experiments indicate that FGF signaling acts downstream of Hh signaling in nascent mesoderm for anterior mesoderm morphogenesis. This work demonstrates the utility of applying single-cell technologies to resolve complex developmental phenotypes. Here, it revealed a role for Hh signaling from the node in organizing anterior mesoderm morphogenesis, independent of its role in left–right determination, by promoting FGF signaling in gastrulating mesoderm.

Guzzetta, Alexander↗

Bino variations: Effective field theory methods for dark matter direct detection

We apply effective field theory methods to compute bino-nucleon scattering, in the case where tree-level interactions are suppressed and the leading contribution is at loop order via heavy flavor squarks or sleptons. We find that leading log corrections to fixed-order calculations can increase the bino mass reach of direct detection experiments by a factor of 2 in some models. These effects are particularly large for the bino-sbottom coannihilation region, where bino dark matter as heavy as 5–10 TeV may be detected by near future experiments. For the case of stop- and selectron-loop mediated scattering, an experiment reaching the neutrino background will probe thermal binos as heavy as 500 and 300 GeV, respectively. We present three key examples that illustrate in detail the framework for determining weak scale coefficients, and for mapping onto a low-energy theory at hadronic scales, through a sequence of effective theories and renormalization group evolution. For the case of a squark degenerate with the bino, we extend the framework to include a squark degree of freedom at low energies using heavy particle effective theory, thus accounting for large logarithms through a “heavy-light current.” Finally, benchmark predictions for scattering cross sections are evaluated, including complete leading order matching onto quark and gluon operators, and a systematic treatment of perturbative and hadronic uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗

Randomized Algorithms for Symmetric Nonnegative Matrix Factorization

Symmetric Nonnegative Matrix Factorization (SymNMF) is a technique in data analysis and machine learning that approximates a matrix with a product of a nonnegative, low-rank matrix and it transpose. To design faster and more scalable algorithms for SymNMF we develop two randomized algorithms for its computation. The first method uses randomized matrix sketching to compute an initial low-rank approximation to the input matrix and proceeds to uses this as a low-rank input to rapidly compute a SymNMF. The second methods uses randomized leverage score sampling to approximately solve constrained least squares problems. Many successful methods for SymNMF rely on (approximately) solving sequences of constrained least squares problems. Here, we prove theoretically that leverage score sampling can approximately solve constrained least squares problems to e-accuracy. Finally we demonstrate both methods work in practice by applying them to graph clustering tasks on large real world data sets. These experiments show that our methods approximately maintain solution quality and achieve significant speed ups for both large dense and large sparse problems.

97 MATHEMATICS AND COMPUTING↗

Ranking Biological Features in Soil-Based Microbial Multi-Omics Data with Integration Modeling

Distinguishing the most important features (e.g. proteins, metabolites, etc.) per group (e.g. control and treatment) is a critical challenge in feature-rich multi-omics experiments, especially in soil data. Traditional feature identification and ranking approaches, such as differential expression, are based on single omics and thus not directly translatable to multi-omics experiments. Here, 5 multi-omics integration models (DIABLO, JACA, MOFA, MultiMLP, and SLIDE) that were not explicitly built for soil data applications were tested using a soil-based multi-omics experiment. The data were obtained from an experimental setup of an autoclaved soil system inoculated with 8 bacteria and using chitin as the carbon source and including samples collected at 0- (control), 4-, 8-, and 12-weeks post-inoculation. The omics data included metaproteomics, 16S rRNA sequencing, and LC-MS/MS metabolomics (in positive and negative mode). Each multi-omics integration model was implemented, and top features were compared to differential univariate statistics per omic type, demonstrating that integration approaches cut the potential number of top features from 2957 identified by differential statistics to 13-224 (a 99.6% to 92.4% reduction). Interestingly, most top features across integration models were not shared; though, scaling and averaging ranks across models shared similar patterns. This work highlights the usefulness of multi-omics integration models in soil-based microbial studies and the power of using multiple integration models together to interpret results.

54 ENVIRONMENTAL SCIENCES↗