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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cloud condensation nuclei characteristics at the Southern Great Plains site: role of particle size distribution and aerosol hygroscopicity

The activation ability of aerosols as cloud condensation nuclei (CCN) is crucial in climate and hydrological cycle studies, but their properties are not well known. We investigated the long-term measurements of atmospheric aerosol properties, CCN concentrations (N CCN ) at supersaturation (SS = 0.1%–1.0%), and hygroscopicity at the Department of Energy's Southern Great Plains (SGP) site to illustrate the dependence of N CCN on aerosol properties and transport pathways. Cluster analysis was applied to the back trajectories of air masses to investigate their respective source regions. The results showed that aged biomass burning aerosols from Central America were characterized by higher accumulation mode particles (N accu ; median value 805 cm -3 ) and relatively high aerosol hygroscopicity (κ; median value ~0.25) values that result in the higher CCN activation and relatively high N CCN (median value 258–1578 cm -3 at a SS of 0.1%–1.0%). Aerosols from the Gulf of Mexico were characterized by higher N accu (~35%), and N CCN (230–1721 cm -3 at a SS of 0.1%–1.0%) with the lowest κ (~0.17). In contrast, relatively high nucleation mode particles (N nucl ; ~20%) and low N CCN (128–1553 cm -3 at a SS of 0.1%–1.0%) with higher κ (~0.30) values were observed on the aerosols associated with a westerly wind. The results indicate particle size as the most critical factor influencing the ability of aerosols to activate, whereas the effect of chemical composition was secondary. Our CCN closure analysis suggests that chemical composition and mixing state information are more crucial at lower SS, whereas at higher SS, most particles become activated regardless of their chemical composition and size. This study affirms that soluble organic fraction information is required at higher SS for better N CCN prediction, but both the soluble organics fraction and mixing state are vital to reduce the N CCN prediction uncertainty at lower SS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Reconstruction with velocities

ABSTRACT Reconstruction is becoming a crucial procedure of galaxy clustering analysis for future spectroscopic redshift surveys to obtain subper cent level measurement of the baryon acoustic oscillation scale. Most reconstruction algorithms rely on an estimation of the displacement field from the observed galaxy distribution. However, the displacement reconstruction degrades near the survey boundary due to incomplete data and the boundary effects extend to ${\sim}100\, \mathrm{Mpc}/h$ within the interior of the survey volume. We study the possibility of using radial velocities measured from the cosmic microwave background observation through the kinematic Sunyaev–Zeldovich effect to improve performance near the boundary. We find that the boundary effect can be reduced to ${\sim}30-40\, \mathrm{Mpc}/h$ with the velocity information from Simons Observatory. This is especially helpful for dense low redshift surveys where the volume is relatively small and a large fraction of total volume is affected by the boundary.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Constraining IGM enrichment and metallicity with the C iv forest correlation function

ABSTRACT The distribution and abundance of metals in the diffuse intergalactic medium (IGM) have implications for galaxy formation and evolution models, and has been argued to be sensitive to the Universe’s reionization history. However, reduced sensitivity in the near-IR implies that probing IGM metals at z > 4 is currently out of reach with the traditional method of detecting individual absorbers. We present a new technique based on clustering analysis that enables the detection of these weak IGM absorbers. We investigate the two-point correlation function (2PCF) of the ${\rm C\, {\small IV}}$ forest as a probe of IGM metallicity and enrichment topology by simulating the z = 4.5 IGM with models of inhomogeneous metal distributions. The 2PCF of the ${\rm C\, {\small IV}}$ forest demonstrates a clear peak at a characteristic separation corresponding to the doublet separation of the ${\rm C\, {\small IV}}$ line.The peak amplitude scales quadratically with metallicity, while enrichment topology affects both the shape and amplitude of the 2PCF. For models consistent with the distribution of metals at z ∼ 3, we find that we can constrain [C/H] to within 0.2 dex, log$\, M_{\rm {min}}$ to within 0.4 dex, and R to within 15 per cent. We show that CGM absorbers can be reliably identified and masked, thus recovering the underlying IGM signal. The auto-correlation of the metal-line forest presents a compelling avenue to constrain the IGM metallicity and enrichment topology with high precision at z > 4, thereby pushing such measurements into the Epoch of Reionization.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: Single-probe measurements from DR12 galaxy clustering – towards an accurate model

We analyze the broad-range shape of the monopole and quadrupole correlation functions of the BOSS Data Release 12 (DR12) CMASS and LOWZ galaxy sample to obtain constraints on the Hubble expansion rate H(z), the angular-diameter distance DA(z), the normalised growth rate f(z)σ 8 (z), and the physical matter density Ω m h 2 . In addition, we adopt wide and flat priors on all model parameters in order to ensure the results are those of a `single-probe' galaxy clustering analysis. We also marginalize over three nuisance terms that account for potential observational systematics affecting the measured monopole. However, such Monte Carlo Markov Chain analysis is computationally expensive for advanced theoretical models, thus we develop a new methodology to speed up our analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Transcript and metabolite network perturbations in lignin biosynthetic mutants of Arabidopsis

Abstract Lignin, one of the most abundant polymers in plants, is derived from the phenylpropanoid pathway, which also gives rise to an array of metabolites that are essential for plant fitness. Genetic engineering of lignification can cause drastic changes in transcription and metabolite accumulation with or without an accompanying development phenotype. To understand the impact of lignin perturbation, we analyzed transcriptome and metabolite data from the rapidly lignifying stem tissue in 13 selected phenylpropanoid mutants and wild-type Arabidopsis (Arabidopsis thaliana). Our dataset contains 20,974 expressed genes, of which over 26% had altered transcript levels in at least one mutant, and 18 targeted metabolites, all of which displayed altered accumulation in at least one mutant. We found that lignin biosynthesis and phenylalanine supply via the shikimate pathway are tightly co-regulated at the transcriptional level. The hierarchical clustering analysis of differentially expressed genes (DEGs) grouped the 13 mutants into 5 subgroups with similar profiles of mis-regulated genes. Functional analysis of the DEGs in these mutants and correlation between gene expression and metabolite accumulation revealed system-wide effects on transcripts involved in multiple biological processes.

Plant Sciences↗
DOE OSTI2019

A heuristic classification of woody plants based on contrasting shade and drought strategies

Woody plants vary in their adaptations to drought and shade. For a better prediction of vegetation responses to drought and shade within dynamic global vegetation models, it is critical to group species into functional types with similar adaptations. One of the key challenges is that the adaptations are generally determined by a large number of plant traits that may not be available for a large number of species. In this study, we present two heuristic woody plant groups that were separated using cluster analysis in a three-dimensional trait–environment space based on three key metrics for each species: mean xylem embolism resistance, shade tolerance and habitat aridity. The two heuristic groups separate these species into tolerators and avoiders. Furthermore, the tolerators either rely on their high embolism resistance to tolerate drought in arid habitats (e.g., Juniperus and Prunus ) or rely on high shade tolerance to withstand shaded conditions in wet habitats (e.g., Picea , Abies and Acer ). In contrast, all avoiders have low embolism resistance and low shade tolerance. In arid habitats, avoiders tend to minimize catastrophic embolism (e.g., most Pinus species) while in wet habitats, they may survive despite low shade tolerance (e.g., Betula , Populus , Alnus and Salix ). Because our approach links traits to the environmental conditions, we expect it could be a promising framework for predicting changes in species composition, and therefore ecosystem function, under changing environmental conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

MeshAndCollect: an automated multi-crystal data-collection workflow for synchrotron macromolecular crystallography beamlines

The fully automated collection and merging of partial data sets from a series of cryocooled crystals of biological macromolecules contained on the same support is presented, as are the results of test experiments carried out on various systems. Here, an automated procedure is described to identify the positions of many cryocooled crystals mounted on the same sample holder, to rapidly predict and rank their relative diffraction strengths and to collect partial X-ray diffraction data sets from as many of the crystals as desired. Subsequent hierarchical cluster analysis then allows the best combination of partial data sets, optimizing the quality of the final data set obtained. The results of applying the method developed to various systems and scenarios including the compilation of a complete data set from tiny crystals of the membrane protein bacteriorhodopsin and the collection of data sets for successful structure determination using the single-wavelength anomalous dispersion technique are also presented.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Climate, food and humans predict communities of mammals in the United States

Abstract Aim The assembly of species into communities and ecoregions is the result of interacting factors that affect plant and animal distribution and abundance at biogeographic scales. Here, we empirically derive ecoregions for mammals to test whether human disturbance has become more important than climate and habitat resources in structuring communities. Location Conterminous United States. Time Period 2010–2021. Major Taxa Studied Twenty‐five species of mammals. Methods We analysed data from 25 mammal species recorded by camera traps at 6645 locations across the conterminous United States in a joint modelling framework to estimate relative abundance of each species. We then used a clustering analysis to describe 8 broad and 16 narrow mammal communities. Results Climate was the most important predictor of mammal abundance overall, while human population density and agriculture were less important, with mixed effects across species. Seed production by forests also predicted mammal abundance, especially hard‐mast tree species. The mammal community maps are similar to those of plants, with an east–west split driven by different dominant species of deer and squirrels. Communities vary along gradients of temperature in the east and precipitation in the west. Most fine‐scale mammal community boundaries aligned with established plant ecoregions and were distinguished by the presence of regional specialists or shifts in relative abundance of widespread species. Maps of potential ecosystem services provided by these communities suggest high herbivory in the Rocky Mountains and eastern forests, high invertebrate predation in the subtropical south and greater predation pressure on large vertebrates in the west. Main Conclusions Our results highlight the importance of climate to modern mammals and suggest that climate change will have strong impacts on these communities. Our new empirical approach to recognizing ecoregions has potential to be applied to expanded communities of mammals or other taxa.

Kays, Roland↗
DOE OSTI2015

Dynamics of excited instantons in the system of forced Gursey nonlinear differential equations

The Gursey model is a 4D conformally invariant pure fermionic model with a nonlinear spinor self-coupled term. Gursey proposed his model as a possible basis for a unitary description of elementary particles following the “Heisenberg dream.” In this paper, we consider the system of Gursey nonlinear differential equations (GNDEs) formed by using the Heisenberg ansatz. We use it to understand how the behavior of spinor-type Gursey instantons can be affected by excitations. For this, the regular and chaotic numerical solutions of forced GNDEs are investigated by constructing their Poincaré sections in phase space. A hierarchical cluster analysis method for investigating the forced GNDEs is also presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Low-dose radiation affects cardiac physiology: gene networks and molecular signaling in cardiomyocytes

There are 160,000 cancer patients worldwide treated with particle radiotherapy (RT). With the advent of proton, and high (H) charge (Z) and energy (E) HZE ionizing particle RT, the cardiovascular diseases risk estimates are uncertain. In addition, future deep space exploratory-type missions will expose humans to unknown but low doses of particle irradiation (IR). Here, we examined molecular responses using transcriptome profiling in left ventricular murine cardiomyocytes isolated from mice that were exposed to 90 cGy, 1 GeV proton ( 1 H) and 15 cGy, 1 GeV/nucleon iron ( 56 Fe) over 28 days after exposure. Unsupervised clustering analysis of gene expression segregated samples according to the IR response and time after exposure, with 56 Fe-IR showing the greatest level of gene modulation. 1 H-IR showed little differential transcript modulation. Network analysis categorized the major differentially expressed genes into cell cycle, oxidative responses, and transcriptional regulation functional groups. Transcriptional networks identified key nodes regulating expression. Validation of the signal transduction network by protein analysis and gel shift assay showed that particle IR clearly regulates a long-lived signaling mechanism for ERK1/2, p38 MAPK signaling and identified NFATc4, GATA4, STAT3, and NF-κB as regulators of the response at specific time points. These data suggest that the molecular responses and gene expression to 56 Fe-IR in cardiomyocytes are unique and long-lasting. Our study may have significant implications for the efforts of National Aeronautics and Space Administration to develop heart disease risk estimates for astronauts and for patients receiving conventional and particle RT via identification of specific HZE-IR molecular markers.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Identification of the Hydrogeochemical Processes in Groundwater Using Classic Integrated Geochemical Methods and Geostatistical Techniques, in Amol-Babol Plain, Iran

Hydrogeochemical investigations had been carried out at the Amol-Babol Plain in the north of Iran. Geochemical processes and factors controlling the groundwater chemistry are identified based on the combination of classic geochemical methods with geographic information system (GIS) and geostatistical techniques. The results of the ionic ratios and Gibbs plots show that water rock interaction mechanisms, followed by cation exchange, and dissolution of carbonate and silicate minerals have influenced the groundwater chemistry in the study area. The hydrogeochemical characteristics of groundwater show a shift from low mineralized Ca-HCO 3 , Ca-Na-HCO 3 , and Ca-Cl water types to high mineralized Na-Cl water type. Three classes, namely, C 1 , C 2 , and C 3, have been classified using cluster analysis. The spatial distribution maps of Na + /Cl - , Mg 2+ /Ca 2+ , and Cl - /HCO 3 - ratios and electrical conductivity values indicate that the carbonate and weathering of silicate minerals played a significant role in the groundwater chemistry on the southern and western sides of the plain. However, salinization process had increased due to the influence of the evaporation-precipitation process towards the north-eastern side of the study area.

58 GEOSCIENCES↗
DOE OSTI2024

GeoCricket

SAND2025-12229O Geospatial Critical Infrastructure and Census Data Stockpile Tool (GeoCricket) is a set of functions that collect critical infrastructure and census data for use in the Resilient Node Cluster Analysis Tool (ReNCAT) and Quantum Geographic Information System Social Burden Calculator. It can also act to inform other place-based work. The code queries public-facing Representational State Transfer (REST) servers to collect geospatial data related to a specific area. It then exports that data as standard geographic information system file types or as a .csv file. 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.

Haines, John↗
DOE OSTI2017

A Dynamical and Statistical Characterization of U.S. Extreme Precipitation Events and Their Associated Large-Scale Meteorological Patterns

Abstract Regional patterns of extreme precipitation events occurring over the continental United States are identified via hierarchical cluster analysis of observed daily precipitation for the period 1950–2005. Six canonical extreme precipitation patterns (EPPs) are isolated for the boreal warm season and five for the cool season. The large-scale meteorological pattern (LMP) inducing each EPP is identified and used to create a “base function” for evaluating a climate model’s potential for accurately representing the different patterns of precipitation extremes. A parallel analysis of the Community Climate System Model, version 4 (CCSM4), reveals that the CCSM4 successfully captures the main U.S. EPPs for both the warm and cool seasons, albeit with varying degrees of accuracy. The model’s skill in simulating each EPP tends to be positively correlated with its capability in representing the associated LMP. Model bias in the occurrence frequency of a governing LMP is directly related to the frequency bias in the corresponding EPP. In addition, however, discrepancies are found between the CCSM4’s representation of LMPs and EPPs over regions such as the western United States and Midwest, where topographic precipitation influences and organized convection are prominent, respectively. In these cases, the model representation of finer-scale physical processes appears to be at least equally important compared to the LMPs in driving the occurrence of extreme precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Understanding Observed Precipitation Change and the New Climate Normal from the Perspective of Daily Weather Types in the Southeast United States

Abstract Observed precipitation changes in the Southeast United States (SEUS) are spatially heterogeneous. Most of the inland SEUS and eastern Gulf Coast become drier, and the East Coast north of Charleston, South Carolina, and southern Florida become wetter from the old 30-yr period of 1961–90 to the recent period of 1991–2020. The observed climate change is examined from the perspective of daily weather types (WTs). A k -means clustering analysis has been conducted using daily 850-hPa circulation for 1948–2021. The obtained 10 WTs peak in different seasons, respectively. The frequencies and precipitation intensity of the WTs have been analyzed. A winter WT characterized by a western Appalachian trough (WAT) and a summer WT featuring North Atlantic subtropical high (NASH) have a rising trend of annual frequency from 1948 to 2021. An Appalachian high in the autumn has a decreasing frequency but becomes drier and stronger. Some precipitation intensity change and small location shift have also been observed. The drying up on the eastern Gulf Coast and the inland area of the SEUS is mainly caused by the weakened southwesterly low-level jet (LLJ) on the western flank of the NASH that reduces rain in the spring, the less frequent but stronger and drier Appalachian high in the summer and autumn, and the weaker and more western located Plains trough (PT) in the winter, spring, and autumn. The precipitation increase in the East Coast and southern Florida is majorly due to more frequent, stronger, and rainier troughs along the western Appalachian as well as the East Coast.

Qian, Jian-Hua↗
DOE OSTI2026

Characterizing Spatial and Temporal Variability of California’s Coastal Upwelling Using a Satellite-Derived CUTI Index

Ocean upwelling off California is a wind-driven coastal process with complex interactions between spatial wind patterns and sea surface temperatures. Large-scale spatial and temporal upwelling characterizations are traditionally based on numerical models, while quantifying upwelling with direct observations is not straightforward. To complement model-based upwelling characterizations, here we use satellite estimates of winds, sea surface temperatures, and ocean currents along the California coast to calculate the coastal upwelling transport index (CUTI), originally calculated from a numerical ocean model. The CUTI framework accounts for both Ekman and geostrophic offshore-directed ocean transport, the latter of which is often neglected in satellite-based upwelling assessments. The approach yields the CUTI over a 30-yr period at a daily temporal and 0.25° spatial resolution to analyze upwelling patterns, with focus on potential Morro Bay and Humboldt wind energy areas. Morro Bay (CUTI median of 0.63 m 2 s −1 ) exhibits stronger, more consistent upwelling throughout the year, whereas Humboldt (CUTI median of 0.45 m 2 s −1 ) exhibits a pronounced seasonal cycle with strongest upwelling in the summer and occasional downwelling in winter. The cluster analysis of 1993–2022 satellite maps of CUTI identifies four characteristic spatial upwelling patterns along the coast, corresponding to distinct spatial distributions of sea surface temperature anomalies, Ekman transport, and geostrophic ocean water transport. This dataset provides an observation-based foundation for characterizing natural coastal upwelling off the California coast, showing good agreement with the original model CUTI while being based on satellite data and offering increased spatial resolution.

16 TIDAL AND WAVE POWER↗
DOE OSTI2019

Study of serious adverse drug reactions using FDA-approved drug labeling and MedDRA

Background Adverse Drug Reactions (ADRs) are of great public health concern. FDA-approved drug labeling summarizes ADRs of a drug product mainly in three sections, i.e., Boxed Warning (BW), Warnings and Precautions (WP), and Adverse Reactions (AR), where the severity of ADRs are intended to decrease in the order of BW > WP > AR. Several reported studies have extracted ADRs from labeling documents, but most, if not all, did not discriminate the severity of the ADRs by the different labeling sections. Such a practice could overstate or underestimate the impact of certain ADRs to the public health. In this study, we applied the Medical Dictionary for Regulatory Activities (MedDRA) to drug labeling and systematically analyzed and compared the ADRs from the three labeling sections with a specific emphasis on analyzing serious ADRs presented in BW, which is of most drug safety concern. Results This study investigated New Drug Application (NDA) labeling documents for 1164 single-ingredient drugs using Oracle Text search to extract MedDRA terms. We found that only a small portion of MedDRA Preferred Terms (PTs), 3819 out of 21,920 or 17.42%, were observed in a whole set of documents. In detail, 466/3819 (12.0%) PTs were in BW, 2023/3819 (53.0%) were in WP, and 2961/3819 (77.5%) were in AR sections. We also found a higher overlap of top 20 occurring BW PTs with WP sections compared to AR sections. Within the MedDRA System Organ Class levels, serious ADRs (sADRs) from BW were prevalent in Nervous System disorders and Vascular disorders. A Hierarchical Cluster Analysis (HCA) revealed that drugs within the same therapeutic category shared the same ADR patterns in BW (e.g., nervous system drug class is highly associated with drug abuse terms such as dependence, substance abuse, and respiratory depression). Conclusions This study demonstrated that combining MedDRA standard terminologies with data mining techniques facilitated computer-aided ADR analysis of drug labeling. We also highlighted the importance of labeling sections that differ in seriousness and application in drug safety. Using sADRs primarily related to BW sections, we illustrated a prototype approach for computer-aided ADR monitoring and studies which can be applied to other public health documents.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Combined EDS and EBSD dataset from TiB2 ceramic material

This is supplemental information to a paper to be submitted, tentatively titled Cluster analysis of combined EDS and EBSD data to solve ambiguous phase identifications. Data was acquired from a TiB2 ceramic provided by Missouri University of Science and Technology. Simultaneous EDS and EBSD were acquired on a Tescan MIRA3 GMH field-emission SEM equipped with Oxford Instruments Symmetry CMOS-based EBSD detector and Oxford Instruments UltimMax 170 mm2 silicon-drift detector EDS. Data was acquired using Oxford Instruments AZtec 4.0 software. Data was acquired at 20 keV, 70° tilt, and ≈1 nA probe current. An 80×60 pixel, 40×30 μm map (500 nm pixel pitch) was acquired. EBSD indexing was performed using TiB2, space group 191 P6/mmm, and TiC, space group 225 Fm \bar{3}m, crystal cards.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Comparative genomics of geographically distant Fusarium fujikuroi isolates revealed two distinct pathotypes correlating with secondary metabolite profiles

Fusarium fujikuroi causes bakanae (“foolish seedling”) disease of rice which is characterized by hyper-elongation of seedlings resulting from production of gibberellic acids (GAs) by the fungus. This plant pathogen is also known for production of harmful mycotoxins, such as fusarins, fusaric acid, apicidin F and beauvericin. Recently, we generated the first de novo genome sequence of F. fujikuroi strain IMI 58289 combined with extensive transcriptional, epigenetic, proteomic and chemical product analyses. GA production was shown to provide a selective advantage during infection of the preferred host plant rice. Here, we provide genome sequences of eight additional F. fujikuroi isolates from distant geographic regions. The isolates differ in the size of chromosomes, most likely due to variability of subtelomeric regions, the type of asexual spores (microconidia and/or macroconidia), and the number and expression of secondary metabolite gene clusters. Whilst most of the isolates caused the typical bakanae symptoms, one isolate, B14, caused stunting and early withering of infected seedlings. In contrast to the other isolates, B14 produced no GAs but high amounts of fumonisins during infection on rice. Furthermore, it differed from the other isolates by the presence of three additional polyketide synthase (PKS) genes (PKS40, PKS43, PKS51) and the absence of the F. fujikuroi-specific apicidin F (NRPS31) gene cluster. Analysis of additional field isolates confirmed the strong correlation between the pathotype (bakanae or stunting/withering), and the ability to produce either GAs or fumonisins. Deletion of the fumonisin and fusaric acid-specific PKS genes in B14 reduced the stunting/withering symptoms, whereas deletion of the PKS51 gene resulted in elevated symptom development. Phylogenetic analyses revealed two subclades of F. fujikuroi strains according to their pathotype and secondary metabolite profiles.

59 BASIC BIOLOGICAL SCIENCES↗