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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Elucidating Anthracnose Resistance Mechanisms in Sorghum—A Review

Sorghum (Sorghum bicolor) is the fifth most cultivated cereal crop in the world, traditionally providing food, feed, and fodder, but more recently also fermentable sugars for the production of renewable fuels and chemicals. The hemibiotrophic fungal pathogen Colletotrichum sublineola, the causal agent of anthracnose disease in sorghum, is prevalent in the warm and humid climates where much of the sorghum is cultivated and poses a serious threat to sorghum production. The use of anthracnose-resistant sorghum germplasm is the most environmentally and economically sustainable way to protect sorghum against this pathogen. Even though multiple anthracnose resistance loci have been mapped in diverse sorghum germplasm in recent years, the diversity in C. sublineola pathotypes at the local and regional levels means that these resistance genes are not equally effective in different areas of cultivation. This review summarizes the genetic and cytological data underlying sorghum’s defense response and describes recent developments that will enable a better understanding of the interactions between sorghum and C. sublineola at the molecular level. This includes releases of the sorghum genome and the draft genome of C. sublineola, the use of next-generation sequencing technologies to identify gene expression networks activated in response to infection, and improvements in methodologies to validate resistance genes, notably virus-induced and transgenic gene silencing approaches.

Plant Sciences↗
DOE OSTI2025

Perfect spinfluid: A divergence-type approach

We present a new formulation of nondissipative relativistic spin hydrodynamics that incorporates spin degrees of freedom into the divergence-type theory framework. Due to the divergence-type structure, it is straightforward to enforce nonlinear causality and symmetric hyperbolicity of the equations of motion, ensuring local well-posedness of the initial-value problem and stability of the theory. Furthermore, in a specific realization based on spin kinetic theory, we prove that the equations of motion remain nonlinearly causal and symmetric-hyperbolic to all orders in the spin potential, provided a specific thermodynamic constraint is satisfied. Here, this framework can be applied for numerical simulations to study the dynamics of spin-polarized fluids, such as the quark-gluon plasma in heavy-ion collisions.

Chirality↗
DOE OSTI2022

Stochastic hydrodynamics and hydro-kinetics: Similarities and differences

The hydro-kinetic formalism has been used as a complementary approach to solving the Stochastic Differential Equations (SDE) corresponding to noisy hydrodynamics. The hydro-kinetic formalism consists of a deterministic set of relaxation type equations that tracks the evolution of 2-point correlation functions of stochastic hydrodynamic quantities. Hence they are comparatively easier to solve than the SDEs, which are computationally intensive and need to deal with arbitrarily large gradients. This work compares the two approaches for the propagation and diffusion of conserved charge fluctuations in the Bjorken hydrodynamic model. For white noise, the two approaches agree. For colored Catteneo noise, which is causal, the two approaches diverge. This is because white noise only induces two-point correlations, while Catteneo noise also induces higher-order correlations. Furthermore, this difference is quantified from the effects of causal evolution and influence from higher-order correlations induced by the Catteneo noise.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Cosmological consequences of first-order general-relativistic viscous fluid dynamics

In this work, we investigate the out-of-equilibrium dynamics of viscous fluids in a spatially flat Friedmann-LemaîtreRobertson-Walker cosmology using the most general causal and stable viscous energy-momentum tensor defined at first order in spacetime derivatives. In this new framework a pressureless viscous fluid having equilibrium energy density ρ can evolve to an asymptotic future solution in which the Hubble parameter approaches a constant while ρ → 0, even in the absence of a cosmological constant (i.e., Λ = 0). Thus, while viscous effects in this model drive an accelerated expansion of the universe, the equilibrium energy density itself vanishes, leaving behind only the acceleration. This behavior emerges as a consequence of causality in first-order theories of relativistic fluid dynamics and it is fully consistent with Einstein’s equations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Locality in collider tests of quantum mechanics with top quark pairs

Tests of quantum properties of fundamental particles in high energy colliders are starting to appear. Entanglement and Bell inequality violation in top and antitop quark system is of particular interest since top quarks are unstable particles that undergo a cascade decay. We argue for criteria for the spacelike separation between top and antitop quarks at their different decay stages. We considered causal separation at three different instances: at the top quark decay, at the 𝑊 boson decay, and at the lepton/jet contact with the macroscopic apparatus. We showed that the spacelike fraction of events is the smallest, when requiring that both top quarks and 𝑊 bosons decay within the spacelike interval. For high invariant masses, typically required for the Bell inequality violation, this is almost identical to just the top quark decay requirement. We also include an option for the angular correlation of the 𝑏 quarks from top quark decay to be used for the spin correlation measurement. We require that both top quark and 𝑏 hadron decays are spacelike separated. Again, we find that at high invariant masses it is almost identical to just the requirement of spacelike separation between top and antitop quarks. We provide numerical values for our proposed criteria. If such a criterion is satisfied, the system is guaranteed to not be in a causal connection.

Entanglement in field theory↗
DOE OSTI2025

Subregion-subalgebra duality: Emergence of space and time in holography

In holographic duality, a higher dimensional quantum gravity system emerges from a lower dimensional conformal field theory (CFT) with a large number of degrees of freedom. We propose a formulation of duality for a general causally complete bulk spacetime region, called subregion-subalgebra duality, which provides a framework to describe how geometric notions in the gravity system, such as spacetime subregions, different notions of times, and causal structure, emerge from the dual CFT. Subregion-subalgebra duality generalizes and brings new insights into subregion-subregion duality (or equivalently entanglement wedge reconstruction). It provides a mathematically precise definition of subregion-subregion duality and gives an independent definition of entanglement wedges without using entropy. Geometric properties of entanglement wedges, including those that play a crucial role in interpreting the bulk as a quantum error correcting code, can be understood from the duality as the geometrization of the superadditivity of certain algebras. Using general boundary subalgebras rather than those associated with geometric subregions makes it possible to find duals for general bulk spacetime regions, including those not touching the boundary. Applying subregion-subalgebra duality to a boundary state describing a single-sided black hole also provides a precise way to define mirror operators. Published by the American Physical Society 2025

Leutheusser, Sam (ORCID:0000000339228128)↗
DOE OSTI2023

Experimental Limit on Nonlinear State-Dependent Terms in Quantum Theory

Linear time evolution is one of the fundamental postulates of quantum theory. Past theoretical attempts to introduce nonlinearity into quantum evolution have violated causality. However, a recent theory has introduced nonlinear state-dependent terms in quantum field theory, preserving causality [D. E. Kaplan and S. Rajendran, Phys. Rev. D 105, 055002 (2022)]. We report the results of an experiment that searches for such terms. Our approach, inspired by the Everett many-worlds interpretation of quantum theory, correlates a binary macroscopic classical voltage with the outcome of a projective measurement of a quantum bit, prepared in a coherent superposition state. Measurement results are recorded in a bit string, which is used to control a voltage switch. Presence of a nonzero voltage reading in cases of no applied voltage is the experimental signature of a nonlinear state-dependent shift of the electromagnetic field operator. We implement blinded measurement and data analysis with three control bit strings. Control of systematic effects is realized by producing one of the control bit strings with a classical random-bit generator. The other two bit strings are generated by measurements performed on a superconducting qubit in an IBM Quantum processor and on a N 15 nuclear spin in a nitrogen-vacancy center in diamond. Our measurements find no evidence for electromagnetic quantum state-dependent nonlinearity. We set a bound on the parameter that quantifies this nonlinearity | ε γ | < 4.7 × 10 - 11 , at 90% confidence level.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Footprints of the QCD Crossover on Cosmological Gravitational Waves at Pulsar Timing Arrays

Pulsar timing arrays (PTAs) have reported evidence for a stochastic gravitational wave (GW) background at nanohertz frequencies, possibly originating in the early Universe. We show that the spectral shape of the low-frequency (causality) tail of GW signals sourced at temperatures around T ≳ 1 GeV is distinctively affected by confinement of strong interactions (QCD), due to the corresponding sharp decrease in the number of relativistic species, and significantly deviates from ∼ f 3 commonly adopted in the literature. Bayesian analyses in the NANOGrav 15 years and the previous international PTA datasets reveal a significant improvement in the fit with respect to cubic power-law spectra, previously employed for the causality tail. While no conclusion on the nature of the signal can be drawn at the moment, our results show that the inclusion of standard model effects on cosmological GWs can have a decisive impact on model selection. Published by the American Physical Society 2024

Franciolini, Gabriele (ORCID:0000000268929145)↗
DOE OSTI2021

VAINE: Visualization and AI for Natural Experiments

Natural experiments are observational studies where the assignment of treatment conditions to different populations occur by chance ``in the wild''. Researchers from fields such as economics, healthcare, and the social sciences leverage natural experiments to conduct hypothesis testing and causal effect estimation for treatment and outcome variables that would otherwise be costly, infeasible, or unethical. In this paper, we introduce VAINE (Visualization and AI for Natural Experiments), a visual analytics tool for identifying and understanding natural experiments from observational data. We then demonstrate how VAINE can be used to validate causal relationships, estimate average treatment effects, and identify statistical phenomena such as Simpson’s paradox through two use cases.

Guo, Grace↗
DOE OSTI2020

Sustainable Development Tool Using Meta‐Analysis and DPSIR Framework — Application to Savannah River Basin, U.S.

Abstract The Savannah River Basin (SRB), a highly stressed southeastern river in United States is a conservation priority for State, Federal government, and nongovernment organizations. A four‐stage sustainable development tool was developed in this study using meta‐analysis and the drivers–pressures–state–impacts–responses (DPSIR) framework. Through the synthesis of ~150 references in the SRB this study addressed three research questions: (1) What were the drivers, pressures, state, impacts, and responses (components of DRSIR framework) in SRB (2) Can these components be grouped together from various studies in SRB (3) Can causal chain/loops be developed, and will they be useful for policy and decision making? First in the Stage 1, the state of the SRB was represented (S component of DPSIR), in Stage 2, the drivers–pressures–impacts–responses (DPIR components of DPSIR) were represented, in the third stage (Stage 3) the common units characterizing each DPSIR component were identified. Finally, in Stage 4, the causal chains/loops were developed and organized into scientific research at a level appropriate for building better understanding about SRB and helping stakeholders and policy makers in managing basin sustainability challenges. Although the tool was applied to SRB, the methodology is applicable to other river basins and ecosystems.

Pagan, Janeesa↗
DOE OSTI2023

Salinity–induced limits to mangrove canopy height

Aim: Mangrove canopy height is a key metric to assess tidal forests' resilience in the face of climate change. In terrestrial forests, tree height is primarily determined by water availability, plant hydraulic design, and disturbance regime. However, the role of water stress remains elusive in tidal environments, where saturated soils are prevalent, and salinity can substantially affect the soil water potential. Location: Global. Time Period: The canopy height dataset provides a global snapshot of the maximum mangrove height geographical distribution for the year 2000. Climate and environmental variables extend over the period 1970–2018. Major Taxa Studied: Mangroves. Methods: We use global observations of maximum canopy height, species richness, air temperature, and seawater salinity—a proxy of soil water salt concentration—to explore the causal link between salinity and mangrove stature. Results: Our findings suggest that salt stress limits mangrove height. High salinity favours more salt-tolerant species, narrowing the spectrum of viable traits. Highly salt-tolerant mangroves have evolved to cope with high salt concentrations in the soil, but this adaptation comes at a cost. They typically have lower rates of photosynthesis and growth, resulting in reduced productivity and smaller stature compared to more salt-sensitive mangrove species. This suggests a causal link between salinity, biodiversity, and tree height, where high salinity selects for more salt-tolerant species that tend to be less productive and shorter. Conclusions: We hypothesize that the salinity-induced limit to mangrove canopy height is the direct result of a reduction of primary productivity, an increment in the risk of xylem cavitation, and an indirect consequence of the decrease in biodiversity. As sea-level rise enhances coastal salinisation, failure to account for these effects can lead to incorrect estimates of future carbon stocks in Tropical coastal ecosystems and endanger preservation efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A noncoding single-nucleotide polymorphism at 8q24 drives IDH1 -mutant glioma formation

Establishing causal links between inherited polymorphisms and cancer risk is challenging. Here, we focus on the single-nucleotide polymorphism rs55705857, which confers a sixfold greater risk of isocitrate dehydrogenase (IDH)–mutant low-grade glioma (LGG). Here, we reveal that rs55705857 itself is the causal variant and is associated with molecular pathways that drive LGG. Mechanistically, we show that rs55705857 resides within a brain-specific enhancer, where the risk allele disrupts OCT2/4 binding, allowing increased interaction with the Myc promoter and increased Myc expression. Mutating the orthologous mouse rs55705857 locus accelerated tumor development in an Idh1 R132H -driven LGG mouse model from 472 to 172 days and increased penetrance from 30% to 75%. Our work reveals mechanisms of the heritable predisposition to lethal glioma in ~40% of LGG patients.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program

One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third (n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

GNATFinder

SAND2023-05510O GNATFinder is a software tool for extracting graphical neural activity threads (GNATs) from spiking neural networks. GNATFinder efficiently extracts GNATs from spiking neural network data. A GNAT is a graph that represents the causal relationships between individual spikes in a spiking network using a combination of the network connectivity structure and the timing of individual spikes. The software allows for identifying similar, repeating threads that often reappear in a dataset. Using quadtree data structures to recursively subdivide the time interval over which spikes were produced by the spiking network, GNATFinder allows for efficient pairwise comparisons of spike times to determine the degree of causal relatedness among all pairs of spikes in a dataset. 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.

SciDAC↗
DOE OSTI2025

CRISPR-CARB/nocap

Network Optimization and Causal Analysis of Perturb-seq (NOCAP) is a software package for causal inference of gene regulation networks using data from perturb-seq.

George, August↗
DOE OSTI2024

Simplified Approximations of Direct Cumulus Entrainment and Detrainment

Abstract In recent years, direct calculations of simulated cumulus entrainment and detrainment have facilitated new physical insights into these highly elusive but critically important processes. However, these calculations require substantial computational resources that may limit their widespread usage. To facilitate such calculations, two simplified approximations of direct cumulus entrainment and detrainment are examined herein. The first approximation, termed the “semidirect” method, follows a standard bulk approach but makes more realistic assumptions about the sources of entrained and detrained air near the cloud edges. In contrast, the second approximation (the “projection” method) uses the governing equations of motion to project whether grid points near the cloud edge will entrain or detrain as the mean cloud ascends by one grid point. Verification exercises using large-eddy simulations reveal that both methods generally agree better with corresponding direct entrainment/detrainment estimates than the traditional bulk formulation, with the projection method outperforming the semidirect method. The two methods can be used in a synergistic fashion, with the semidirect method helping to optimize the projection method, to suit a wide range of applications. Because the latter incorporates the essential dynamics of entrainment and detrainment at the local scale, it can be used to gain physical insight into the causal mechanisms regulating these complex processes.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

A systematic decision-making methodology to formalize the selection of degree of realism in screening analysis of probabilistic risk assessment

In the nuclear power domain, Probabilistic Risk Assessment (PRA) is used to inform decision-making for Nuclear Power Plants (NPPs). Recently, there has been an increase in the utilization of modeling and simulation (M&S) to support the estimation of PRA inputs. Risk analysts should carefully select the PRA items that require M&S and their degree of realism (DoR) with consideration of the required resources. To support this selection, this article formulates a systematic decision-making approach for the DoR selection. The DoR selection is made based on two predictive decision-making attributes: the predicted differences in safety risk estimate (ΔSaRi) and the cost of analysis (ΔCAN). This research also develops and quantifies causal models to estimate ΔSaRi and ΔCAN. The causal model-based prediction of ΔSaRi and ΔCAN helps reduce the trial-and-error nature of the DoR selection in the PRA screening analysis and provides insights for DoR selection and the gradual refinements of PRA realism. This approach is demonstrated for a case study on fire PRA of NPPs, where an adequate DoR is selected from two fire models: an engineering correlation and a zone model.

Alkhatib, Sari [Department of Nuclear, Plasma, and↗
DOE OSTI2024

Decision-making based on Markov decision process in integrated artificial reasoning framework—Part I: Theory

This paper presents a decision-making framework based on an integrated artificial reasoning framework and Markov decision process (MDP). The integrated artificial reasoning framework provides a physics-based approach that converts system information into state transition models, and the analysis result will be represented by the transition probabilities that can be used with an MDP to find a traceable and explainable optimal pathway. A dynamic Bayesian network (DBN) is well suited for representing the structure of an MDP. The causality information among process variables (or among subsystems) is mathematically represented in a DBN by the conditional probabilities of the node’s states provided different probabilities of the parent node’s states. To define node states in a physically understandable manner, we used multilevel flow modeling (MFM). An MFM follows the fundamental energy and mass conservation laws and supports the selection of process variables that represent the system of interest so that causal relations among process variables are properly captured. An MFM-based DBN supports developing state transition models in an MDP to capture the effect of process variables of system having physical relations. The operators of the target system can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from component degradation or random failures. We analyzed a simplified exemplary system to illustrate an optimal operational policy using the suggested approach.

Markov decision process↗