Search NASA⌕ Search

SEARCH · Search NASA

Results for “higher order interaction”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Prolate-Oblate Asymmetric Shape Phase Transition in the Interacting Boson Model with SU(3) Higher-Order Interactions

Prolate-oblate shape phase transition is an interesting topic in nuclear structure, which is useful for understanding the intrinsic interactions between nucleons. Recently, the interacting boson model with SU(3) higher-order interactions was proposed, in which the prolate shape and the oblate shape are not described in a mirror symmetric way. This asymmetric description seems more realistic. The level evolutions, B(E2) values, and other important indicators showing the prolate-oblate asymmetric transitions are investigated in detail, and realistic structure evolutions from 180Hf to 200Hg are compared. A key finding is that the average deformation of the prolate shape is nearly twice the one of the oblate shape. These results, together with the successful description of the B(E2) anomaly in 168,170Os, 172Pt, the γ -soft properties of 196Pt, 82Kr, and the normal states of 110Cd, support the validity of the new model.

Wang, Tao↗
DOE OSTI2018

A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia

Technological advances are enabling us to collect multimodal datasets at an increasing depth and resolution while with decreasing labors. Understanding complex interactions among multimodal datasets, however, is challenging. Here in this study, we tested the interaction effect of multimodal datasets using a novel method called the kernel machine for detecting higher order interactions among biologically relevant multimodal data. Using a semiparametric method on a reproducing kernel Hilbert space, we formulated the proposed method as a standard mixed-effects linear model and derived a score-based variance component statistic to test higher order interactions between multimodal datasets. The method was evaluated using extensive numerical simulation and real data from the Mind Clinical Imaging Consortium with both schizophrenia patients and healthy controls. Our method identified 13-triplets that included 6 gene-derived SNPs, 10 ROIs, and 6 gene-specific DNA methylations that are correlated with the changes in hippocampal volume, suggesting that these triplets may be important for explaining schizophrenia-related neurodegeneration. The performance of the proposed method is compared with the following methods: test based on only first and first few principal components followed by multiple regression, and full principal component analysis regression, and the sequence kernel association test. With strong evidence (p-value ≤0.000001), the triplet (MAGI2, CRBLCrus1.L, FBXO28) is a significant biomarker for schizophrenia patients. This novel method can be applicable to the study of other disease processes, where multimodal data analysis is a common task.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2000

Co-conservation of rRNA tetraloop sequences and helix length suggests involvement of the tetraloops in higher-order interactions

Terminal loops containing four nucleotides (tetraloops) are common in structural RNAs, and they frequently conform to one of three sequence motifs, GNRA, UNCG, or CUUG. Here we compare available sequences and secondary structures for rRNAs from bacteria, and we show that helices capped by phylogenetically conserved GNRA loops display a strong tendency to be of conserved length. The simplest interpretation of this correlation is that the conserved GNRA loops are involved in higher-order interactions, intramolecular or intermolecular, resulting in a selective pressure for maintaining the lengths of these helices. A small number of conserved UNCG loops were also found to be associated with conserved length helices, consistent with the possibility that this type of tetraloop also takes part in higher-order interactions.

Non-NASA Center↗
DOE OSTI2026

Higher-order interaction effects among operating conditions and feedstocks shape reactor microbiomes and fatty acid production profiles

Arrested anaerobic digestion (AAD) offers a promising route for producing fatty acids (FAs) from organic residues, yet optimal conditions for selectively generating medium-chain fatty acids (MCFAs) remain poorly defined. Here, we systematically evaluated the main and interaction effects of pH (5, 7, 9), feedstock (food waste, manure), temperature (35 and 45 °C), and inoculum source on microbiome composition and FA production. Anaerobic digester sludge and a novel bison rumen inoculum were compared. Significant higher-order interactions among operating parameters governed FA profiles and microbiome structure. Butyric acid production was driven by a three-way interaction among pH, feedstock, and temperature (p < 0.001), with maximum concentrations achieved in food waste reactors at pH 5.0 and 35 °C (1.2 ± 0.1 g L −1 with sludge and 1.1 ± 0.3 g L −1 with rumen). MCFA production exhibited significant four-way interactions (p < 0.1 to p < 0.001). At 45 °C and pH 5.0, inoculum source tuned MCFA selectivity: sludge favored pentanoic acid (0.4 ± 0.1 g L −1 ), whereas rumen favored hexanoic and heptanoic acids (up to 0.4 ± 0.2 g L −1 ). Manure reactors produced < 0.2 g L −1 MCFAs under all conditions. Genera, including Megasphaera, Prevotella, and Lactobacillus, were associated with production of specific MCFAs. PICRUSt2-based pathway predictions were consistent with MCFA production patterns and suggested a potential role for lactic acid–driven chain elongation pathways. This study provides insights into how interacting operating conditions shape AAD microbiomes, their FA profiles, and advances the trajectory of research aimed at engineering robust and controllable microbiomes for waste valorization.

09 BIOMASS FUELS↗
DOE OSTI2021

Landau-Lifshitz-Bloch equation for ferrimagnets with higher-order interaction

In this work, we present a micromagnetic formulation for modeling the magnetization dynamics and thermal equilibrium in ferrimagnetic materials at low and elevated temperatures. The formulation is based on a mean-field approximation (MFA). In this formulation, the ferrimagnet is described micromagnetically by two coupled sublattices with corresponding interactions, including inter- and intrasublattice micromagnetic exchange as well as four-spin interactions described as an intersublattice molecular field with a cubic dependence of the magnetization. The MFA is used to derive a Landau-Lifshitz-Bloch type equation for ferrimagnetic material, including cases with a ferromagnetic-antiferromagnetic phase transitions. For validation, the results obtained via the presented model are compared with recent experimental data for phase transitions in FeRh.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1986

Higher-order structure of rRNA

A comparative search for phylogenetically covarying basepair replacements within potential helices has been the only reliable method to determine the correct secondary structure of the 3 rRNAs, 5S, 16S, and 23S. The analysis of 16S from a wide phylogenetic spectrum, that includes various branches of the eubacteria, archaebacteria, eucaryotes, in addition to the mitochondria and chloroplast, is beginning to reveal the constraints on the secondary structures of these rRNAs. Based on the success of this analysis, and the assumption that higher order structure will also be phylogenetically conserved, a comparative search was initiated for positions that show co-variation not involved in secondary structure helices. From a list of potential higher order interactions within 16S rRNA, two higher-order interactions are presented. The first of these interactions involves positions 570 and 866. Based on the extent of phylogenetic covariation between these positions while maintaining Watson-Crick pairing, this higher-order interaction is considered proven. The other interaction involves a minimum of six positions between the 1400 and 1500 regions of the 16S rRNA. Although these patterns of covariation are not as striking as the 570/866 interaction, the fact that they all exist in an anti-parallel fashion and that experimental methods previously implicated these two regions of the molecule in tRNA function suggests that these interactions be given serious consideration.

Gutell, R. R.↗
DOE OSTI2024

Learning epistatic polygenic phenotypes with Boolean interactions

Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1 , a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1993

Random interactions in higher order neural networks

Recurrent networks of polynomial threshold elements with random symmetric interactions are studied. Precise asymptotic estimates are derived for the expected number of fixed points as a function of the margin of stability. In particular, it is shown that there is a critical range of margins of stability (depending on the degree of polynomial interaction) such that the expected number of fixed points with margins below the critical range grows exponentially with the number of nodes in the network, while the expected number of fixed points with margins above the critical range decreases exponentially with the number of nodes in the network. The random energy model is also briefly examined and links with higher order neural networks and higher order spin glass models made explicit.

Baldi, Pierre↗
DOE OSTI2021

MyD88 TIR domain higher-order assembly interactions revealed by microcrystal electron diffraction and serial femtosecond crystallography

MyD88 and MAL are Toll-like receptor (TLR) adaptors that signal to induce pro-inflammatory cytokine production. We previously observed that the TIR domain of MAL (MAL TIR ) forms filaments in vitro and induces formation of crystalline higher-order assemblies of the MyD88 TIR domain (MyD88 TIR ). These crystals are too small for conventional X-ray crystallography, but are ideally suited to structure determination by microcrystal electron diffraction (MicroED) and serial femtosecond crystallography (SFX). Here, we present MicroED and SFX structures of the MyD88 TIR assembly, which reveal a two-stranded higher-order assembly arrangement of TIR domains analogous to that seen previously for MAL TIR . We demonstrate via mutagenesis that the MyD88 TIR assembly interfaces are critical for TLR4 signaling in vivo, and we show that MAL promotes unidirectional assembly of MyD88 TIR . Collectively, our studies provide structural and mechanistic insight into TLR signal transduction and allow a direct comparison of the MicroED and SFX techniques.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Structural basis of amino acid surveillance by higher-order tRNA-mRNA interactions

Amino acid availability in Gram-positive bacteria is monitored by T-box riboswitches. T-boxes directly bind tRNAs, assess their aminoacylation state, and regulate the transcription or translation of downstream genes to maintain nutritional homeostasis. Here in this paper, we report cocrystal and cryo-EM structures of Geobacillus kaustophilus and Bacillus subtilis T-box–tRNA complexes, detailing their multivalent, exquisitely selective interactions. The T-box forms a U-shaped molecular vise that clamps the tRNA, captures its 3' end using an elaborate ‘discriminator’ structure, and interrogates its aminoacylation state using a steric filter fashioned from a wobble base pair. In the absence of aminoacylation, T-boxes clutch tRNAs and form a continuously stacked central spine, permitting transcriptional readthrough or translation initiation. A modeled aminoacyl disrupts tRNA-T-box stacking, severing the central spine and blocking gene expression. Our data establish a universal mechanism of amino acid sensing on tRNAs and gene regulation by T-box riboswitches and exemplify how higher-order RNA-RNA interactions achieve multivalency and specificity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Statistical Multiobjective Optimization of Thiospinel CoNi 2 S 4 Nanocrystal Synthesis via Design of Experiments

Thiospinels, such as CoNi 2 S 4 , are showing promise for numerous applications, including as catalysts for the hydrogen evolution reaction, hydrodesulfurization, and oxygen evolution and reduction reactions; however, CoNi 2 S 4 has not been synthesized as small, colloidal nanocrystals with high surface-area-to-volume ratios. Traditional optimization methods to control nanocrystal attributes such as size typically rely upon one variable at a time (OVAT) methods that are not only time and labor intensive but also lack the ability to identify higher-order interactions between experimental variables that affect target outcomes. Herein, we demonstrate that a statistical design of experiments (DoE) approach can optimize the synthesis of CoNi 2 S 4 nanocrystals, allowing for control over the responses of nanocrystal size, size distribution, and isolated yield. After implementing a 2 5–2 fractional factorial design, the statistical screening of five different experimental variables identified temperature, Co:Ni precursor ratio, Co:thiol ratio, and their higher-order interactions as the most critical factors in influencing the aforementioned responses. Second-order design with a Doehlert matrix yielded polynomial functions used to predict the reaction parameters needed to individually optimize all three responses. A multiobjective optimization, allowing for the simultaneous optimization of size, size distribution, and isolated yield, predicted the synthetic conditions needed to achieve a minimum nanocrystal size of 6.1 nm, a minimum polydispersity (σ/$\bar{d}$) of 10%, and a maximum isolated yield of 99%, with a desirability of 96%. The resulting model was experimentally verified by performing reactions under the specified conditions. Furthermore, our work illustrates the advantage of multivariate experimental design as a powerful tool for accelerating control and optimization in nanocrystal syntheses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1995

Analysis of uncertainty in force balance calibration

In order to reduce errors encountered in the measurement and identification of loads using force balances, a third-order forward polynomial relation between loads and output voltages is proposed. This full third-order model represents an alternative to the second-order model currently in use at NASA Langley Research Center (LaRC) and many other installations worldwide. The new model requires the identification of 84 coefficients (including the 28 used presently) for each of the six outputs. The existing LaRC calibration loading sequence is insufficient for identification of many of these 504 coefficients because critical three-load combinations are absent. Accordingly, a new loading sequence that permits the identification of all 504 coefficients has been developed and is described fully. It is apparent from numerical tests that the new third-order model is clearly superior to second-order models in the presence of small amounts of random measurement noise, assuming that there are indeed higher-order interactions between loads. As the amount of noise increases, however, a third-order model becomes less attractive due to its ability to match the noise itself more faithfully than a second-order model. Numerical results suggest that the transition occurs when the magnitude of random noise becomes of the same order as that of the physical higher-order interactions.

Bursal, Faruk H.↗
DOE OSTI2018

Magnetic Properties of a Nano-graphene Monolayer with Higher-Order Exchange Interaction Coupling

Using the Monte Carlo simulation, we have studied the phase diagrams and the hysteresis behaviors of a single layer Ising nanographene with next-nearest neighbors coupling J{sub 2} and four-spin interaction J{sub 4} in the presence of a crystal field D and applied magnetic field h. It can emphasize that, for appropriate system parameters, the nanographene can exhibit a new phenomenon manifested in the emergence of an antiferromagnetic phase sandwiched between two ferromagnetic ones. Concerning the hysteresis behavior, the system can present a multiple hysteresis loops.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1977

Stability of higher-order Bragg interactions in active periodic media

The stability of waves in unbounded, longitudinally periodic media is studied for index and gain coupling. Time-independent periodic media are found to support both stable and absolutely unstable waves. The wave characteristics depend upon average gain or loss, coupling type, and Bragg order. The extended coupled waves equations provide explicit values of threshold, frequency, and temporal growth rate for instabilities at all Bragg resonances through the dispersion relation. Applications to multiharmonic periodicities and complex couplings are briefly discussed with particular note taken of possible reductions of the stability thresholds and removal of threshold degeneracies. Comparisons are made to the longitudinally bounded case of distributed feedback lasers.

Jaggard, D. L.↗
DOE OSTI2020

Neurotransmitter networks in mouse prefrontal cortex are reconfigured by isoflurane anesthesia

This study quantified eight, small molecule neurotransmitters collected simultaneously from prefrontal cortex of C57BL/6J mouse (n=23) during wakefulness and during isoflurane anesthesia (1.3%). Using isoflurane anesthesia as an independent variable enabled evaluation of the hypothesis that isoflurane anesthesia differentially alters concentrations of multiple neurotransmitters and their interactions. Machine learning was applied to reveal higher order interactions among neurotransmitters. Using a between-subjects design, microdialysis was performed during wakefulness and during anesthesia. Concentrations (nM) of acetylcholine, adenosine, dopamine, GABA, glutamate, histamine, norepinephrine, and serotonin in the dialysis samples are reported (mean ± SD). Relative to wakefulness, acetylcholine concentration was lower during isoflurane anesthesia (1.254 ± 1.118 versus 0.401 ± 0.134, P=0.009), and concentrations of adenosine (29.456 ± 29.756 versus 101.321 ± 38.603, P<0.001), dopamine (0.0578 ± 0.0384 versus 0.113 ± 0.084, P=0.036), and norepinephrine (0.126 ± 0.080 versus 0.219 ± 0.066, P=0.010) were higher during anesthesia. Isoflurane reconfigured neurotransmitter interactions in prefrontal cortex, and the state of isoflurane anesthesia was reliably predicted by prefrontal cortex concentrations of adenosine, norepinephrine, and acetylcholine. A novel finding to emerge from machine learning analyses is that neurotransmitter concentration profiles in mouse prefrontal cortex undergo functional reconfiguration during isoflurane anesthesia. Adenosine, norepinephrine, and acetylcholine showed high feature importance, supporting the interpretation that interactions among these three transmitters may play a key role in modulating levels of cortical and behavioral arousal.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Realization of three- and four-body interactions between momentum states in a cavity

Spin Hamiltonians in condensed matter and quantum sensing typically utilize pairwise or two-body interactions between constituents in the material or ensemble. However, there is growing interest in exploring more general n-body interactions for n > 2. In this study, we realized an effective n = 3-body Hamiltonian interaction using an ensemble of laser-cooled atoms in a high-finesse optical cavity with the pseudospin 1/2 encoded by two atomic momentum states. We applied two dressing tones that induce the atoms to exchange photons via the cavity to realize a virtual six-photon process; lower-order interactions destructively interfered. We also observed signatures of a n = 4-body interaction mediated by a virtual eight-photon process. Our approach may be extensible to three-body interactions in multilevel systems or to even higher-order interactions.

Luo, Chengyi [University of Colorado, Boulder, CO ↗