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At least 235 records · Page 13

The 6-minute walk test predicts mortality in a pulmonary nontuberculous mycobacteria-predominant bronchiectasis cohort

Background: Bronchiectasis is a chronic lung condition frequently associated with nontuberculous mycobacteria pulmonary (NTM) disease. Persons with these conditions are at increased risk of mortality. Patient reported outcome (PRO) instruments and the 6-minute walk test (6MWT) have been shown to predict mortality for several lung conditions, but these measures have not been fully evaluated for bronchiectasis and NTM. Methods: We conducted a retrospective cohort study among adult patients enrolled in a natural history study of bronchiectasis at the National Heart, Lung, and Blood Institute. Electronic medical records were queried for demographic, clinical, microbiologic, radiographic, and PRO instrument data: St. George’s Respiratory Questionnaire (SGRQ), Medical Research Council Dyspnea Scale, and the Pulmonary Symptom Severity Score (PSSS). The study baseline date was defined as the patient’s first visit after January 1st, 2015 with a SGRQ or 6MWT completed. Follow-up was defined as the interval between the study baseline visit and date of death or December 31st, 2019. Sex-stratified Cox proportional-hazards regression was conducted to identify predictors of mortality. Separate models were run for each PRO and 6MWT measure, controlling for age, body mass index (BMI), fibrocavitary disease status, and M. abscessus infection. Results: In multivariable Cox proportional-hazards regression models, the PSSS-severity (aHR 1.29, 95% CI 1.04–1.59), the 6MWT total distance walked (aHR 0.938, 95% CI 0.896–0.981) and distance saturation product (aHR 0.930, 95% CI 0.887–0.974) independently predicted mortality. In addition, BMI was significantly predictive of mortality in all models. Conclusions: The 6MWT and a PRO instrument capturing symptom severity are independently predictive of mortality in our cohort of bronchiectasis patients.

6-minute walk test↗

AmeriFlux US-xBR NEON Bartlett Experimental Forest (BART)

This is the AmeriFlux version of the carbon flux data for the site US-xBR NEON Bartlett Experimental Forest (BART). Site Description - The Bartlett Experimental Forest is an actively managed forest; managed portions (30%) reflect a range of forest patch sizes and structural distributions. The Bartlett forest has a history of logging dating from colonial times through the beginning of the 20th century. Approximately 70% of the land area has remained uncut since the early 1900s. Natural disturbances include late 19th century fire, beech scale-Nectria complex (beech bark disease) beginning in the 1940s, severe wind disturbance resulting from hurricanes in 1938 and 1954 and a damaging ice storm in 1998.

Network), NEON (National Ecological Observatory↗

AmeriFlux FLUXNET-1F US-xBR NEON Bartlett Experimental Forest (BART)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xBR NEON Bartlett Experimental Forest (BART). This is the FLUXNET version of the carbon flux data for the site US-xBR NEON Bartlett Experimental Forest (BART) produced by applying the standard ONEFlux (1F) software. Site Description - The Bartlett Experimental Forest is an actively managed forest; managed portions (30%) reflect a range of forest patch sizes and structural distributions. The Bartlett forest has a history of logging dating from colonial times through the beginning of the 20th century. Approximately 70% of the land area has remained uncut since the early 1900s. Natural disturbances include late 19th century fire, beech scale-Nectria complex (beech bark disease) beginning in the 1940s, severe wind disturbance resulting from hurricanes in 1938 and 1954 and a damaging ice storm in 1998.

Network), NEON (National Ecological Observatory↗

Long-term, large-scale experiment reveals the effects of seed limitation, climate, and anthropogenic disturbance on restoration of plant communities in a biodiversity hotspot

Ecological restoration is essential for maintaining biodiversity in the face of dynamic, global changes in climate, human land use, and disturbance regimes. Effective restoration requires understanding bottlenecks in plant community recovery that exist today, while recognizing that these bottlenecks may relate to complex histories of environmental change. Such understanding has been a challenge because few long-term, well-replicated experiments exist to decipher the demographic processes influencing recovery for numerous species against the backdrop of multiyear variation in climate and management. Here we address this challenge through a long-term and geographically expansive experiment in longleaf pine savannas, an imperiled ecosystem and biodiversity hotspot in the southeastern United States. Using 48 sites at three locations spanning 480 km, the 8-y experiment manipulated initial seed arrival for 24 herbaceous plant species and presence of competitors to evaluate the impacts of climate variability and management actions (e.g., prescribed burning) on plant establishment and persistence. Adding seeds increased plant establishment of many species. Cool and wet climatic conditions, low tree density, and reduced litter depth also promoted establishment. Once established, most species persisted for the duration of the 8-y experiment. Plant traits were most predictive when tightly coupled to the process of establishment. Our results illustrate how seed additions can restore plant diversity and how interannual climatic variation affects the dynamics of plant communities across a large region. The significant effects of temperature and precipitation inform how future climate may affect restoration and conservation via large-scale changes in the fundamental processes of establishment and persistence.

60 APPLIED LIFE SCIENCES↗

An uncertainty-focused database approach to extract spatiotemporal trends from qualitative and discontinuous lake-status histories

Changes in lake status are often interpreted as palaeoclimate indicators due to their dependence on precipitation and evaporation. The Global Lake Status Database (GLSDB) has since long provided a standardised synopsis of qualitative lake status over the last 30,000 14C years. Potential sources of uncertainty however are not recorded in the GLSDB. Here we present an updated and improved relational-database framework that incorporates uncertainty in both chronology and the interpretation of palaeoenvironmental data. The database uses peer-reviewed palaeolimnological studies to produce a consensus on qualitative lake-status histories, whose chronologies are revised and standardized through the recalibration of radiocarbon dates and the application of Bayesian age-depth modelling for stratigraphic archives. Quantitative information on absolute water-level elevation is preserved if available from geomorphological sources. We also propose a new probabilistic analytical framework that accounts for these uncertainties to reconstruct synoptic, integrated environmental signals. The process is based on a Monte Carlo algorithm that iteratively samples individual lake-status histories within the limits of their uncertainties to produce many possible scenarios. We then use Recursively-Subtracted Empirical Orthogonal Function analysis to extract dominant patterns of lake-status variability from these scenarios. As a proof of concept, we apply this framework to 67 sites in eastern and southern Africa whose lake-status histories cover part of the late Pleistocene and/or Holocene. We show that, despite the sometimes large temporal and interpretation uncertainties, and the inclusion of highly discontinuous lake-status time series, identifying the major known millennial-scale climatic phases during the last 20,000 years is possible. Our framework was also able to identify an antiphased response between the lake basins in eastern and interior southern Africa to these changes. Here, we propose that our new database and methodology framework serves as a template for efficient lake-status data synthesis, encourages the incorporation of lake-status data in palaeoclimate syntheses, and expands the possibilities for the use of such data in the evaluation of climate models.

58 GEOSCIENCES↗

LeaPP: Learning Pathways to Polymorphs through Machine Learning Analysis of Atomic Trajectories

Understanding the mechanisms underlying crystal nucleation and growth is crucial for many technological applications. Due to the short length and time scales involved, crystal nucleation is often studied using molecular simulations. Most existing approaches to extract the nucleation mechanism from simulations focus on the analysis of static snapshots of the configurations, potentially overlooking subtle local fluctuations and the history of the particles involved in the formation of solid nuclei. Here, in this work, we propose a novel methodology called LeaPP that categorizes nucleation trajectories based on the temporal information of their constituent particles. We leverage the time evolution of the local environment of the crystallizing particles to encapsulate the relationship between the structure and dynamics and distinguish between different evolving particle paths. Identification of the distinct particle paths further enables characterizing the nucleation trajectories into different pathways. Collectively, LeaPP provides a more nuanced understanding of nucleation through an unsupervised approach with lesser dependence on traditional order parameters. Furthermore, the pathways identified by LeaPP are predictive of the resulting polymorph. We demonstrate LeaPP on three different systems─Lennard-Jones-like particles, Ni 3 Al, and water on surfaces. The general methodology underlying LeaPP─considering the time evolution of the building blocks─applies to a wide range of self-assembly problems.

36 MATERIALS SCIENCE↗

In planta single-molecule imaging and holographic force spectroscopy to study real-time, multimodal turnover dynamics of polysaccharides and associated carbohydrate metabolites

Cellular production of polysaccharides from simple sugar molecules serves critical roles in a variety of metabolic processes essential to the survival of every living organism. In the context of photosynthetically fixed carbon, cell wall polysaccharides synthesis is particularly of interest for increased biomass accumulation for human food, animal feed, and bioenergy related applications. Despite a long history of research in plant cell biology, our understanding of in planta cell wall biosynthesis and its regulation is far from complete due to lack of a comprehensive microscopy toolkit that encompass the multiple spatial and temporal scales in which cell wall polysaccharides fibrils are synthesized and assembled into intricate cell wall networks. In this project, a multidisciplinary team of scientists from Rutgers University, Vanderbilt University, and Oak Ridge National Laboratory carried out innovative multimodal, multiscale microscopy studies of cell wall synthesis using single-molecule force-spectroscopy, super-resolution fluorescence microscopy, and in vivo live cell imaging. Our novel multimodal and holistic imaging approach revealed plant cell wall polysaccharides synthesis processes in unprecedented detail across multiple spatiotemporal scales, from a single-molecule to a single-cell. Besides, the team has made technical and scientific innovations across multiple research fields—microscopy, bioengineering, single-molecule biophysics, and plant biology, etc.—to accomplish the goals. The results from this project will greatly advance the mechanistic and holistic understanding of in planta cell wall synthesis, which will accelerate the development of better transgenic crops for bioenergy applications. Moreover, the new toolbox, combining powerful advanced microscopy assays with cell/protein engineering, will have broader impacts on molecular and cellular biology fields by paving the way for studying cellular processes occurring across multiple physical scales with multimodal microscopy methodologies.

59 BASIC BIOLOGICAL SCIENCES↗

Video, photos capture first full-scale H-bomb test 70 years ago

This collection of images was curated by the National Security Research Center in recognition of the 70 th anniversary of the nuclear test codenamed “Mike” of Operation Ivy. The NSRC is the Lab’s classified library, which also houses unclassified artifacts from the Lab’s history. The NSRC has archived photos of nuclear tests from over the years to preserve our history.

99 GENERAL AND MISCELLANEOUS↗

Seasonal calibration of the end-cretaceous Chicxulub impact event

The end-Cretaceous Chicxulub impact triggered Earth’s last mass-extinction, extinguishing ~ 75% of species diversity and facilitating a global ecological shift to mammal-dominated biomes. Temporal details of the impact event on a fine scale (hour-to-day), important to understanding the early trajectory of mass-extinction, have largely eluded previous studies. This study employs histological and histo-isotopic analyses of fossil fish that were coeval with a unique impact-triggered mass-death assemblage from the Cretaceous-Paleogene (KPg) boundary in North Dakota (USA). Patterns of growth history, including periodicity of δ 18 O and δ 13 C and growth band morphology, plus corroborating data from fish ontogeny and seasonal insect behavior, reveal that the impact occurred during boreal Spring/Summer, shortly after the spawning season for fish and most continental taxa. The severity and taxonomic symmetry of response to global natural hazards are influenced by the season during which they occur, suggesting that post-impact perturbations could have exerted a selective force that was exacerbated by seasonal timing. Data from this study can also provide vital hindsight into patterns of extant biotic response to global-scale hazards that are relevant to both current and future biomes.

54 ENVIRONMENTAL SCIENCES↗

Upscaling Reactive Transport and Clogging in Shale Microcracks by Deep Learning

Fracture networks in shales exhibit multiscale features. A rock system may contain a few main fractures and thousands of microcracks, whose length and aperture are orders of magnitude smaller than the former. It is computationally prohibitive to resolve all the fractures explicitly for such multiscale fracture networks. One traditional approach is to model the small-scale features (e.g., microcracks in shales) as an effective medium. Although this fracture-matrix conceptualization significantly reduces the problem complexity, there are classes of physical processes that cannot be accurately upscaled by effective medium approximations, e.g., microcrack clogging during mineral reactions. Here, we employ deep learning in place of effective medium theory to upscale physical processes in small-scale features. Specifically, we consider reactive transport in a fracture-microcrack network where microcracks can be clogged by precipitation. A deep learning multiscale algorithm is developed, in which the microcracks are upscaled as a wall boundary condition of the main fractures. The wall boundary condition is constructed by recurrent neural networks, which take concentration histories as input and predict the solute transport from main fractures to microcracks. The deep learning multiscale algorithm is firstly employed in specific scenarios, then a general model is developed which can work under various conditions. The new approach is validated against fully resolved simulations and an analytical solution, providing a reliable and efficient solution for problems that cannot be upscaled by effective medium models.

58 GEOSCIENCES↗

Anticipating how rain-on-snow events will change through the 21st century: lessons from the 1997 new year’s flood event

The California-Nevada 1997 New Year’s flood was an atmospheric river (AR)-driven rain-on-snow (RoS) event and remains the costliest in their history. The joint occurrence of saturated soils, rainfall, and snowmelt generated inundation throughout northern California-Nevada. Although AR RoS events are projected to occur more frequently with climate change, the warming sensitivity of their flood drivers across scales remains understudied. We leverage the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) to recreate the 1997 New Year’s flood with horizontal grid spacings of 3.5 km across California, with forecast lead times of up to 4 days, and across six warming levels ranging from pre-industrial conditions to +3.5° C. We describe the sensitivity of the flood drivers to warming including AR duration and intensity, precipitation phase, intensity and efficiency, snowpack mass and energy changes, and runoff efficiency. Our findings indicate current levels of climate change negligibly influence the flood drivers. At warming levels ≥ 1.7° C, AR hazard potential increases, snowpack nonlinearly decreases, antecedent soil moisture decreases (except where the snowline retreats), and runoff decreases (except in the southern Sierra Nevada where antecedent snowpack persists). Storm total precipitation increases, but at rates below warming-induced increases in saturation-specific humidity. Warming intensifies short-duration, high-intensity rainfall, particularly where snowfall-to-rainfall transitions occur. This study highlights the nonlinear tradeoffs in 21st-century RoS flood hazards with warming and provides water management and infrastructure investment adaptation considerations.

54 ENVIRONMENTAL SCIENCES↗

Enhancement of Nanostructured Ferritic Alloy 14YWT Properties via Heat Treatment for Post-Consolidation Processing

The nanostructured ferritic alloy 14YWT is a promising candidate for in-core use in generation IV nuclear reactors, due to a dense dispersion of insoluble, ultrafine-scale Y-Ti-O nano-oxides, which provide a high degree of irradiation tolerance and thermal stability. This work investigates the effects of heat treatment on the workability of 14YWT, along with the effect of processing history on abnormal grain structures and radial microstructural uniformity. In this study, a 14YWT rod consolidated at 850 °C was heat treated in argon at 1100 °C, 1150 °C, 1200 °C, or 1250 °C for 1 or 8 hours and changes in mechanical properties and microstructure were examined using microhardness and electron backscattered diffraction (EBSD). Two distinct types of large abnormal grains were observed, each with unique processing origins, including one with high and the other with low strain energy. Consolidation via direct extrusion resulted in radial microstructural gradients, where the center of the rod was softer with larger grain sizes and lower strain energies. These gradients persisted and intensified throughout heat treatment. Based upon this work, the recommended heat treatment for increased workability with minimal microstructural change is 1150 °C for 1 hours.

36 MATERIALS SCIENCE↗

Gas metallicity distributions in SDSS-IV MaNGA galaxies: what drives gradients and local trends?

ABSTRACT The gas metallicity distributions across individual galaxies and across galaxy samples can teach us much about how galaxies evolve. Massive galaxies typically possess negative metallicity gradients, and mass and metallicity are tightly correlated on local scales over a wide range of galaxy masses; however, the precise origins of such trends remain elusive. Here, we employ data from SDSS-IV MaNGA to explore how gas metallicity depends on the local stellar mass density and on galactocentric radius within individual galaxies. We also consider how the strengths of these dependencies vary across the galaxy mass-size plane. We find that radius is more predictive of local metallicity than stellar mass density in extended lower-mass galaxies, while we find density and radius to be almost equally predictive in higher-mass and more compact galaxies. Consistent with previous work, we find a mild connection between metallicity gradients and large-scale environment; however, this is insufficient to explain variations in gas metallicity behaviour across the mass-size plane. We argue our results to be consistent with a scenario in which extended galaxies have experienced smooth gas accretion histories, producing negative metallicity gradients over time. We further argue that more compact and more massive systems have experienced increased merging activity that disrupts this process, leading to flatter metallicity gradients and more dominant density-metallicity correlations within individual galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Automatic Image Point Matching

Sparse Image Point Matching (SIPM) is a foundational technology for photo triangulation, structure from motion (SfM), Simultaneous Location and Mapping (SLAM), and data fusion. The goal of the matching is to automatically generate sets of image coordinates that identify the same feature across images. Ideally, the process should be robust to lighting, scale, perspective, and modality changes. The scope of the image matching topic in the field of remote sensing (RS) is enormous because of the variety of collection platforms, modalities, sensor types, applications, and subjects. In this work, we report the history of and assess the state of the art of visible-spectrum (panchromatic and color) image matching of the Earth’s surface. Work specific to large-format images (LFI) (e.g., metric aerial cameras and Earth-observing satellites) will be highlighted. However, the state of the art in this century will mostly be traced through machine vision research and benchmarks because research specific to LFI is rare.

97 MATHEMATICS AND COMPUTING↗

Editorial: Editors’ showcase: fuels and chemicals

Throughout its history, industrial microbiology has answered many challenges; food and beverage, antibiotics, pharmaceuticals, nutraceuticals, biomaterials, fuels, and chemicals, often with billions of dollars of impact on markets and society. But these efforts pale in comparison to the challenge of planetary-scale carbon management, which must balance the circularity of a carbon economy with the sequestration of excess environmental carbon. Biorefineries, integrating carbon capture with diverse bioproduct markets, offer our best route to stabilizing an unbalanced global carbon cycle while powering a robust and equitable bioeconomy.

09 BIOMASS FUELS↗

Active Galactic Nuclei Feedback in SDSS-IV MaNGA: AGNs Have Suppressed Central Star Formation Rates

Despite the importance of feedback from active galactic nuclei (AGNs) in models of galaxy evolution, observational constraints on the influence of AGN feedback on star formation remain weak. To this end, we have compared the star formation trends of 279 low-redshift AGN galaxies with 558 inactive control galaxies using integral field unit spectroscopy from the Sloan Digital Sky Survey-IV Mapping Nearby Galaxies at Apache Point Observatory survey. With a Gaussian-process-based methodology, we reconstruct nonparametric star formation histories in spatially resolved spaxels covering the face of each galaxy. Based on the galaxy-wide star formation rates (SFRs) alone, we find no obvious signatures of AGN feedback. However, the AGN galaxies have significantly suppressed central (kiloparsec-scale) SFRs, lying up to a factor of 2 below those of the control galaxies, providing direct observational evidence of AGN feedback suppressing star formation. The suppression of central SFRs in the AGN galaxies began in the central regions ~6 Gyr ago (redshift z ~ 0.7), taking place over a few gigayears. A small subset of the AGN galaxies were rapidly driven to quiescence shortly before being observed (in the last 500 Myr), potentially indicating instances of AGN-driven feedback. More frequently, however, star formation continues in the AGN galaxies, with suppression primarily in the central regions. This is suggestive of a picture in which integrated (gigayear-timescale) AGN feedback can significantly affect central star formation, but may be inefficient in driving galaxy-wide quenching in low-redshift galaxies, instead leaving them in the green valley.

79 ASTRONOMY AND ASTROPHYSICS↗

WBS 1.2.3.405 - Life Cycle Assessment of Storage Technologies

Recent commitments by the Biden administration have established targets to achieve a net-zero energy system by 2050. Meeting these targets will spur a rapid transition to clean energy technologies and a commensurate need to develop and deploy energy storage technologies at scale. Pumped Storage Hydro (PSH) is expected to be part of this solution because its ability to provide grid flexibility and stability and enable the dispatching of disparate variable renewable energy technologies. Despite PSH being a mature technology with a history of deployment dating back several decades, there is very little information on the greenhouse gas (GHG) implications of PSH as compared to other storage technologies. The objective of this project is to perform a full lifecycle assessment (LCA) of new PSH projects in the U.S. This LCA includes all project phases (resource extraction, construction, operation, maintenance, end-of-life). The functional unit for this study is 1 kWh electricity delivered by system to grid substation connection point and the estimated lifetime for our base case is 80 years. Data used in this study are based on over 30 potential PSH projects that are in preliminary planning phases and are represent a wide range of potential closed-loop PSH systems in terms of location, technology, and capacity. The project approach, data sources, and modeling assumptions have been informed by a technical review committee of stakeholders that include experts from academia, national and international government, industry, and utilities. The GHGs and energy return on investment (EROI) from PSH will be compared to other storage technologies (e.g., stationary battery storage). Results from this project will improve the PSH community's understanding of the environmental impacts and sustainability of new PSH projects and how PSH compares to other storage technologies. The approach used in this project relies on open-source programming. The analysis framework (source code and data) and will be made publicly available at the end of the project. In addition to reporting results for the base case, we will perform rigorous sensitivity analysis to identify the major drivers, understand impacts of different configurations, and future energy markets. Results from this project will be published in a suitable journal.

ENERGY PLANNING, POLICY, AND ECONOMY,HYDRO ENERGY↗

On the correlation between plastic strain and misorientation in polycrystalline body-centered-cubic microstructures with an emphasis on the grain size, loading history, and crystallographic orientation

In this work, the correlation between plastic strain and crystallographic misorientation, grain size, grain orientation, distance from grain boundary, and loading history were investigated experimentally and numerically for body-centered-cubic (BCC) polycrystalline microstructures based on a misorientation deviation (MD) approach. Nine monotonic tensile experiments were performed on two BCC titanium alloys inside a scanning electron microscope (SEM). The influence of reference orientation was explored both at the grain scale and at the mesoscale using electron backscattered diffraction (EBSD). The correlation between global plastic strain and the MD was quantified. The tendency for orientation change was quantified as a function of plastic strain and grain orientation for three crystallographic orientations (i.e., [100], [110], and [111]) with respect to tensile direction. The subpopulation of small grains exhibited a lower level of misorientation dispersion compared with larger grains, and this discrepancy became more pronounced at higher strains. An empirical equation was proposed to estimate the level of misorientation dispersion for individual grains as a function of grain size and global plastic strain level. Two interrupted in-situ SEM experiments were performed, and this resulted in a significantly increased misorientation compared with uninterrupted tests performed to similar plastic strain levels.

36 MATERIALS SCIENCE↗