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At least 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Analysis of individual cells identifies cell-to-cell variability following induction of cellular senescence

Senescent cells play important roles in both physiological and pathological processes, including cancer and aging. In all cases, however, senescent cells comprise only a small fraction of tissues. Senescent phenotypes have been studied largely in relatively homogeneous populations of cultured cells. In vivo, senescent cells are generally identified by a small number of markers, but whether and how these markers vary among individual cells is unknown. We therefore utilized a combination of single-cell isolation and a nanofluidic PCR platform to determine the contributions of individual cells to the overall gene expression profile of senescent human fibroblast populations. Individual senescent cells were surprisingly heterogeneous in their gene expression signatures. This cell-to-cell variability resulted in a loss of correlation among the expression of several senescence associated genes. Many genes encoding senescence-associated secretory phenotype (SASP) factors, a major contributor to the effects of senescent cells in vivo, showed marked variability with a subset of highly induced genes accounting for the increases observed at the population level. Inflammatory genes in clustered genomic loci showed a greater correlation with senescence compared to nonclustered loci, suggesting that these genes are coregulated by genomic location. Together, these data offer new insights into how genes are regulated in senescent cells and suggest that single markers are inadequate to identify senescent cells in vivo.

transcriptomics↗
DOE OSTI2021

Soil respiration spatial and temporal variability in China between 1961 and 2014

Soil respiration (Rs) plays an important role in terrestrial-atmospheric carbon exchange but remains one of the least studied components of the carbon cycle. How environmental changes influence Rs, and in turn, how Rs influences terrestrial carbon storage in China is unclear. Here, we estimated spatial patterns and temporal trends in Rs from 1961 to 2014 to determine the influence of the recent warming hiatus on the Rs temporal variability in China. We evaluated the relationship between Rs and a set of environmental factors and developed biome-specific Rs models that were parameterized based on 2,862 Rs records and 18 continuous variables (e.g., air temperature, precipitation and leaf area index). Based on the biome-specific Rs models and environmental information, we estimated the annual Rs as well as the change trend of Rs in China during the study period. The mean annual Rs from 1961 to 2014 was 3.50 (confidence interval +/- 0.87) Pg center dot C center dot year(-1). Rs in China increased at a rate of 0.008 Pg center dot C center dot year(-2) between 1982 and 1998 (warming period), but was static between 1999 and 2014 (warming hiatus). This reduction in Rs increase rate may have an important role in enhancing terrestrial carbon sequestration. These findings confirm that temporal heterogeneity in Rs could be influenced by regional environmental changes, and further help in improving the understanding of soil carbon dynamics in China.

Jian, Jinshi↗
DOE OSTI2022

Quantifying the effects of varietal types × management on the spatial variability of sorghum biomass across US environments

Abstract Regional‐scale estimations of sorghum biomass production allow identification of optimum genotype×environment×management (G×E×M) combinations for bioenergy generation. The objective of this study was to determine the degree of contributions of G, E, and M toward variability in sorghum biomass in the United States. Using the Agricultural Production Systems sIMulator in a grid computing platform, biomass was simulated for irrigated and rainfed conditions for 30 years across the United States for four sorghum varietal types (grain—GS, sudangrass—SS, photosensitive—PS, and photo‐insensitive—PI). Simulated biomass was assessed by environments clustered using the sum of intercepted solar radiation ( ir ), mean of temperature stress factor ( tp ) and water stress factor ( sw ). Simulated biomass ranged from 5.8 t ha −1 (GS‐rainfed) to 27.5 t ha −1 (PI‐irrigated). Under high‐temperature environments (mean annual temperature = 25°C), rainfed biomass between 40 and 80 days after planting (DAP) was strongly correlated with sw ( r = 0.64–0.86) and irrigated biomass with ir ( r = 0.68–0.81). Under low‐temperature environments (mean annual temperature = 18°C) after 40 DAP, tp and ir had greater effects than sw ( r = 0.55–0.82). Biomass variance was mainly explained by varietal type (50%–76%) in all environments×irrigation combinations, except in the high‐ and mid‐temperature environments under rainfed conditions where rainfall had the major effect (25%–45%). However, when mean temperature during the growing season decreased from 25°C (high environments) to 18°C (low environments), the contribution of mean temperature to biomass variance increased from 7% to 34% (rainfed) and from 4% to 36% (irrigated). Varietal type had the larger interactions with other factors independently of the environment and irrigation. We demonstrated a need to quantify (i) the main G×E×M drivers of biomass variability based on environmental stress factors and (ii) the variance contribution of these drivers on sorghum biomass. Our regional‐scale estimations are key inputs for future robust biomass projections of energy sorghum genotypes integrating G×E×M under climate change scenarios.

Ojeda, Jonathan J.↗
DOE OSTI2018

Tree cover shows strong sensitivity to precipitation variability across the global tropics

Abstract Aim Vegetation is sensitive to mean annual precipitation (MAP), but the sensitivity of vegetation to precipitation variability (PV) is less clear. Tropical ecosystems are likely to experience increased PV in the future. Here we assessed the importance, magnitude and mechanism of PV effects on tree cover in the context of covarying environmental drivers such as fire, temperature and soil properties. Location Tropical land. Time period 2000–2010. Major taxa studied Trees. Methods We compiled climate, soil and remotely‐sensed tree cover data over tropical land. We then comprehensively assessed the contribution of PV at different time‐scales to tropical tree cover variations and estimated the sensitivity of tree cover to PV changes by conducting rolling‐window regression and variance decomposition analyses. We further adopted a mechanistic modelling approach to test whether water competition between trees and grasses can explain the observed effect of PV. Results We find that PV contributes 33–56% to the total explained spatial variation (65–79%) in tree cover. The contribution of PV depends on MAP and is highest under intermediate MAP (500–1,500 mm). Tree cover generally increases with rainy day frequency and wet season length but shows mixed responses to inter‐annual PV. Based on the estimated sensitivity, tropical tree cover can decrease by 3–5% overall and by up to 20% in Amazonia under a 20% decrease in rainy days. Mechanistic modelling analysis reproduced the continental differences in tree cover along an MAP gradient. Main conclusions Under intermediate rainfall regimes (500–1,500 mm), PV can be a more important determinant of tropical tree cover than conventionally proposed drivers such as MAP and fire. The effect of PV likely results from the sensitivity of tree–grass competition to the temporal distribution of water resources. These results show that climate variability can strongly shape the biosphere.

Xu, Xiangtao↗
DOE OSTI2020

Seasonal to Decadal Variability in Focused Groundwater and Contaminant Discharge along a Channelized Stream

Abstract Focused groundwater discharge to streams is problematic at contaminated sites because high fluxes can limit natural attenuation in the hyporheic zone. However, information on location, spatial evolution, and temporal persistence of springs in unlithified sediments over multiyear time scales is limited. We examine discharge at point (~1‐m) to reach (~300‐m) scales along a stream that intercepts trichloroethene and technetium‐99 plumes from a Superfund site. During 2011 to 2012, we seasonally monitored stream and spring flow and contaminant concentrations, along with probing streambed temperatures on a grid in winter and summer, building on prior monitoring during 1999 to 2002. Baseflow measured by both gauging and dye dilution generally increased with distance downstream, and stream and spring discharge varied seasonally, from minima in October to January to maxima in February to June. Thermal anomalies identified by probing occupied approximately 3% to 6% of the reach and typically coincided with visible springs or seeps. Locations of anomalies were similar to those identified in summer 2002, although some orifices disappeared and others emerged. Vertical groundwater fluxes calculated from probing tended to be less than net fluxes calculated from stream discharge, perhaps in part because the assumption of one‐dimensional, steady‐state flow in calculating point fluxes was simplistic. Maximum contaminant concentrations and fluxes decreased between 1999 to 2001 and 2011 to 2012 as a result of partial capture by an upgradient pump‐and‐treat system. Our findings confirm that springs in unlithified sediments can remain stationary within a few meters over decadal time scales, and seasonal variability in discharge can be greater than decadal variability.

Tripathi, Ganesh N.↗
DOE OSTI2021

Interannual variability of ecosystem iso/anisohydry is regulated by environmental dryness

Plants are characterized by the iso/anisohydry continuum depending on how they regulate leaf water potential (?L). However, how iso/anisohydry changes over time in response to year-to-year variations in environmental dryness and how such responses vary across different regions remains poorly characterized. We investigated how dryness, represented by aridity index, affects the interannual variability of ecosystem iso/anisohydry at the regional scale, estimated using satellite microwave vegetation optical depth (VOD) observations. This ecosystem-level analysis was further complemented with published field observations of ?L at the species level. We found different behaviors in the directionality and sensitivity of isohydricity (s) with respect to the interannual variation of dryness in different ecosystems. These behaviors can largely be differentiated by the average dryness of the ecosystem itself: in mesic ecosystems, s decreases in drier years, albeit at a higher rate; in xeric ecosystems, s increases in drier years, albeit at a lower rate. These results were supported by the species-level synthesis. Our study suggests that how plants adjust their water use across years – as revealed by their interannual variability in isohydricity – depends on the dryness of plants’ living environment. This finding advances our understanding of plant responses to drought at regional scales.

Wu, Genghong↗
DOE OSTI2026

Evolutionary constraints and climate variability jointly shape starch–sugar balance in woody plants

Nonstructural carbohydrates (NSC) buffer plants against carbon imbalances, yet their partitioning between storage and soluble pools remains elusive at global scales. Here, we compiled a dataset of starch to soluble sugar ratio (St : Su) for 308 woody species across 220 sites world-wide and introduce a dimensionless index that integrates storage and demand while minimizing methodological artifacts. St : Su was strongly associated with growth, identifying it as a key axis of carbon allocation. Foliage consistently exhibited lower St : Su than lignified organs, reflecting a division between transient and conservative pools. Conifers accumulated more starch in foliage but less in stems relative to angiosperms, while leaf habits and mycorrhizal associations further modulated organ-specific strategies. Contrary to expectation, foliar and root St : Su varied little among biomes, but stems exhibited higher ratios in tropical rainforests than in boreal or arid regions, reflecting differences in species composition and adaptive storage under disturbance. Phylogeny constrained stem storage, whereas climatic variability, rather than mean conditions, dominated allocation in leaves and roots. These findings establish St : Su as a robust functional trait linking allocation strategies, growth, and resilience, which can be used to improve vegetation model prediction of forest productivity and mortality under climate variability.

Li, Weibin [Lanzhou Univ. (China)] (ORCID:00000001↗
DOE OSTI2018

Numerical Prediction of Cyclic Variability in a Spark Ignition Engine Using a Parallel Large Eddy Simulation Approach

Cycle-to-cycle variability (CCV) is detrimental to IC engine operation and can lead to partial burn, misfire, and knock. Predicting CCV numerically is extremely challenging due to two key reasons. First, high-fidelity methods such as large eddy simulation (LES) are required to accurately resolve the in-cylinder turbulent flow field both spatially and temporally. Second, CCV is experienced over long timescales and hence the simulations need to be performed for hundreds of consecutive cycles. Ameen et al. (2017, "Parallel Methodology to Capture Cyclic Variability in Motored Engines,"Int. J. Engine Res., 18(4), pp. 366-377.) developed a parallel perturbation model (PPM) approach to dissociate this long time-scale problem into several shorter time-scale problems. This strategy was demonstrated for motored engine and it was shown that the mean and variance of the in-cylinder flow field was captured reasonably well by this approach. In the present study, this PPM approach is extended to simulate the CCV in a fired port-fuel injected (PFI) spark ignition (SI) engine. The predictions from this approach are also shown to be similar to the consecutive LES cycles. It is shown that the parallel approach is able to predict the coefficient of variation (COV) of the in-cylinder pressure and burn raterelated parameters with sufficient accuracy, and is also able to predict the qualitative trends in CCV with changing operating conditions. It is shown that this new approach is able to give accurate predictions of the CCV in fired engines in less than one-tenth of the time required for the conventional approach of simulating consecutive engine cycles.

Ameen, Muhsin M.↗
DOE OSTI2018

Parameterization of Large Variability Using the Hyper-Dual Meta-Model

One major problem in the design of aerospace components is the nonlinear changes in the response due to a change in the geometry and material properties. Many of these components have small nominal values and any change can lead to a large variability. In order to characterize this large variability, traditional methods require either many simulation runs or the calculations of many higher order derivatives. Each of these paths requires a large amount of computational power to evaluate the response curve. In order to perform uncertainty quantification analysis, even more simulation runs are required. The hyper-dual meta-model is introduced and used to characterize the response curve with the use of basis functions. The information of the response is generated with the utilization of the hyper-dual step to determine the sensitivities at a few number of simulation runs to greatly enrich the response space. This study shows the accuracy of this method for two different systems with parameterizations at different stages in the design analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Pan-Pacific low-frequency modes of sea level and climate variability

Tide gauges provide a long observational record that can inform the nature of satellite-era basin-scale sea level trends. However, common signals must be extracted from geographically sparse records. Here, by applying low-frequency component analysis (LFCA) to tide gauge records and surface climate reconstructions, we isolate three coherent modes of Pacific Ocean variability that we ascribe to: a secular, greenhouse gas–driven climate change (LFC1); a nonlinear mode of variability with a reversal around 1980, potentially linked to aerosols (LFC2); and the Interdecadal Pacific Oscillation (LFC3). Although sea level trend patterns reflect the superimposed contribution of all modes, satellite-era trends are dominated by an increasing phase of LFC2: They are thus potentially unrepresentative of both longer-term historical patterns and those expected in the future.

Science & Technology - Other Topics↗
DOE OSTI2021

Decadal climate variability in the tropical Pacific: Characteristics, causes, predictability, and prospects

Decadal climate variability and change affects nearly every aspect of our world, including weather, agriculture, ecosystems, and the economy. Predicting its expression is thus of critical importance on multiple fronts. Power et al. review what is known about tropical Pacific decadal climate variability and change, the degree to which it can be simulated and predicted, and how we might improve our understanding of it. Here, more accurate projections will require longer and more detailed instrumental and paleoclimate records, improved climate models, and better data assimilation methods. —HJS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Predicting variable gene content in Escherichia coli using conserved genes

Having the ability to predict the protein-encoding gene content of an incomplete genome or metagenome-assembled genome is important for a variety of bioinformatic tasks. In this study, as a proof of concept, we built machine learning classifiers for predicting variable gene content in Escherichia coli genomes using only the nucleotide k-mers from a set of 100 conserved genes as features. Protein families were used to define orthologs, and a single classifier was built for predicting the presence or absence of each protein family occurring in 10%–90% of all E. coli genomes. The resulting set of 3,259 extreme gradient boosting classifiers had a per-genome average macro F1 score of 0.944 [0.943–0.945, 95% CI]. We show that the F1 scores are stable across multi-locus sequence types and that the trend can be recapitulated by sampling a smaller number of core genes or diverse input genomes. Surprisingly, the presence or absence of poorly annotated proteins, including “hypothetical proteins” was accurately predicted (F1 = 0.902 [0.898–0.906, 95% CI]). Models for proteins with horizontal gene transfer-related functions had slightly lower F1 scores but were still accurate (F1s = 0.895, 0.872, 0.824, and 0.841 for transposon, phage, plasmid, and antimicrobial resistance-related functions, respectively). Finally, using a holdout set of 419 diverse E. coli genomes that were isolated from freshwater environmental sources, we observed an average per-genome F1 score of 0.880 [0.876–0.883, 95% CI], demonstrating the extensibility of the models. Overall, this study provides a framework for predicting variable gene content using a limited amount of input sequence data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Light Scattering by Small Multilayer Particles: A Generalized Separation of Variables Method

A Rayleigh approximation is constructed for light scattering by small multilayer axisymmetric particles, in which their polarizability is determined by the generalized separation of variables method (SVM). In this method, scalar potentials, the gradients of which yield the electric-field strengths, are represented as expansions in spherical harmonics of the Laplace equation. Unknown coefficients of expansions are determined from the boundary conditions, which are reduced to infinite systems of linear algebraic equations (ISLAEs), since the separation of variables is incomplete. The T matrix of the electrostatic problem, principal element T{sub 11} of which is proportional to the particle polarizability, is determined. The necessary condition for the ISLAEs solvability for the SVM coincides with the condition of the correct application of the extended boundary conditions method (EBCM). However, numerical calculations in which finite-dimensional (i.e., reduced) systems are solved, yield different results in ranges of variation of parameters that are close to the boundary of the range of applicability. An analysis of the numerical calculations of the scattering and absorption cross sections for two-layer confocal spheroids, an exact solution for which can be obtained using spheroidal harmonics, shows that the SVM is preferable to the EBCM. It turned out that the proposed method yields workable results in a wider range of variation of parameters. Even outside the range of applicability, in which it should be regarded as a certain approximate solution, its use in a number of cases is quite acceptable. Additional calculations for three-layer nonconfocal spheroids, as well as for three-layer similar pseudospheroids and Pascal’s snails, which can be obtained from spheroids as a result of the inversion with respect to the coordinate origin and one of the foci, respectively, confirm these inferences. We note that, for certain values of the parameters, the shapes of the latter particles are nonconvex.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

A Study of Bound States of Systems of Helium and Lithium Using the Method of Discrete-Variable Representation

The systems of particles He{sub 2}, {sup 6}Li–He, {sup 7}Li–He, He{sub 3}, {sup 6}Li–He{sub 2}, and {sup 7}Li–He{sub 2}, the binding energies of which are small and the bound-state wave functions of which are widely distributed in space, are considered. Because the interaction potential is weak and rather localized compared to the characteristic sizes of wave functions of these systems, the problem of an accurate determination of binding energy and wave functions is complicated. Small changes in input parameters or an inaccuracy of calculations can lead to considerable deviations of calculated results from true values. An essential part of the study is the development and application of the discrete-variable representation method. This method is based on the determination of basis functions and the nodes and weights of a quadrature formula in such way that the values of a function are zero at all these nodes but one. With this representation the time required for calculating the Hamiltonianmatrix elements is reduced several times. The binding energies of several systems consisting of helium and lithium atoms were obtained using the method of discrete-variable representation. Thanks to the application of this approach, the calculation time was significantly reduced without loss in accuracy.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Selection of Spectral Variables and Improvement of the Accuracy of Calibration of Temperature by Projection onto Latent Structures Using the Fluorescence Spectra of Yb{sup 3+}:CaF{sub 2}

The efficiency of interval methods for selecting variables and the divisive method of interval optimization by a genetic algorithm is considered with the purpose to increase the accuracy of temperature calibration by projection onto latent structures. The fluorescence spectra of Yb{sup 3+}:CaF{sub 2} recorded in the 880–1120 nm band with a resolution of approximately 0.2 nm in the temperature range from 66 to 150°C in 2°C increments are used as an example. The best result for the root-mean-square error of temperature prediction in the test sample (0.45°C) was obtained by interval projection onto latent structures by a combination of moving windows. The use of methods for selecting spectral variables improved more than two times the accuracy of temperature calibration.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

GrammarViz 3.0: Interactive Discovery of Variable-Length Time Series Patterns

The problems of recurrent and anomalous pattern discovery in time series, e.g., motifs and discords, respectively, have received a lot of attention from researchers in the past decade. However, since the pattern search space is usually intractable, most existing detection algorithms require that the patterns have discriminative characteristics and have its length known in advance and provided as input, which is an unreasonable requirement for many real-world problems. In addition, patterns of similar structure, but of different lengths may co-exist in a time series. In order to address these issues, we have developed algorithms for variable-length time series pattern discovery that are based on symbolic discretization and grammar inference—two techniques whose combination enables the structured reduction of the search space and discovery of the candidate patterns in linear time. In this work, we present GrammarViz 3.0—a software package that provides implementations of proposed algorithms and graphical user interface for interactive variable-length time series pattern discovery. The current version of the software provides an alternative grammar inference algorithm that improves the time series motif discovery workflow, and introduces an experimental procedure for automated discretization parameter selection that builds upon the minimum cardinality maximum cover principle and aids the time series recurrent and anomalous pattern discovery.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Tencoder: tensor-product encoder-decoder architecture for predicting solutions of PDEs with variable boundary data

It is widely hoped that artificial intelligence will boost data-driven surrogate models in science and engineering. However, fundamental spatial aspects of AI surrogate models remain under-studied. We investigate the ability of neural-network surrogate models to predict solutions to PDEs under variable boundary values. We do not wish to retrain the model when the boundary values change but to make them inputs to the model and infer the solution of the PDE under those boundary conditions. Such a capability is essential to making AI-based surrogate models practically useful. While simple feedforward networks are used for one-dimensional (1D) Poisson equation, an encoder-decoder architecture with a tensor-product layer is developed for the two-dimensional Poisson equation posed on a rectangular domain. We show that it is indeed possible to infer solutions to PDEs from variable boundary data using neural networks in this relatively simple setting, and point to future directions.

Kashi, Aditya↗
DOE OSTI2023

Impedance Response Influenced by Variability in the Random Distribution of Physical Properties of Coated Materials in Two-Dimensional Space

Heterogeneous physical characteristics of a system featuring a single-layer film on a metallic surface have been explored via its impedance response. The Nyquist plot showed a distorted semicircle, indicative of the system's unique distribution characteristics. Utilizing a copula-based probability method, a two-dimensional deterministic impedance model was successfully integrated, accounting for spatial physical properties such as permittivity and electrical conductivity. This strategy enabled in-depth exploration and mechanistic quantification of a broad spectrum of properties. A quantitative understanding of impedance signal alterations, characterized by normally or log-normally correlated variables, was achieved through the variation in aspect ratio and characteristic frequency of the impedance spectra. Log-normally distributed electrical properties provided a superior representation of the distorted impedance spectra. As coefficient of variation (CV) values fluctuated, the aspect ratio and characteristic frequency showed heightened sensitivity to log-normal permittivity compared to log-normal electrical conductivity. Notably, a marked positive linear correlation between electrical properties resulted in an impedance response that approximated perfect semicircular spectra. The variability in the electrical properties' distribution was demonstrated by considering the correlation coefficient between electrical conductivity and the z-direction position. Furthermore, the highest aspect ratio of the impedance spectra was observed when the electrical conductivity was randomly distributed across the z-direction space.

36 MATERIALS SCIENCE↗