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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Tuning Bifunctional Oxygen Electrocatalysts by Changing the A-Site Rare-Earth Element in Perovskite Nickelates

Perovskite-structured (ABO 3 ) transition metal oxides are promising bifunctional electrocatalysts for efficient oxygen evolution reaction (OER) and oxygen reduction reaction (ORR). In this paper, we investigate a set of epitaxial rare earth nickelates (RNiO 3 ) thin films with controlled A-site isovalent substitution to correlate their structure and physical properties with ORR/OER activities. The ORR activity is shown to decrease monotonically with decreasing the A-site element ionic radius which lowers the conductivity of the RNiO 3 (R = La, La 0.5 Nd 0.5 , La 0.2 Nd 0.8 , Nd, Nd 0.5 Sm 0.5 , Sm, Gd) films, with LaNiO 3 being the most conductive and active. On the other hand, the OER activity initially increases upon substituting La with Nd and is maximal at La 0.2 Nd 0.8 NiO 3 , in which oxygen vacancies (VOs) start to form. Moreover, the OER activity remains comparable within error through Sm-doped NdNiO 3 . Beyond that, we cannot reliably measure activity due to the potential voltage drop across the film. The improved OER activity is ascribed to the partial reduction of Ni 3+ to Ni 2+ as a result of VOs, which increases the average occupancy of the e g antibonding orbital to more than one. Our work highlights the importance of tuning A-site elements as an effective strategy for balancing the ORR and OER activities of bifunctional electrocatalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Group Projected subspace pursuit for IDENTification of variable coefficient differential equations (GP-IDENT)

We propose an effective and robust algorithm for identifying partial differential equations (PDEs) with space-time varying coefficients from the noisy observation of a single solution trajectory. Identifying unknown differential equations from noisy data is a difficult task, and it is even more challenging with space and time varying coefficients in the PDE. The proposed algorithm, GP-IDENT, has three ingredients: (i) we use B-spline bases to express the unknown space and time varying coefficients, (ii) we propose Group Projected Subspace Pursuit (GPSP) to find a sequence of candidate PDEs with various levels of complexity, and (iii) we propose a new criterion for model selection using the Reduction in Residual (RR) to choose an optimal one among a pool of candidates. The new GPSP considers group projected subspaces which is more robust than existing methods in distinguishing correlated group features. We test GP-IDENT on a variety of PDEs and PDE systems, and compare it with the state-of-the-art parametric PDE identification algorithms under different settings to illustrate its outstanding performance. Furthermore, our experiments show that GP-IDENT is effective in identifying the correct terms from a large dictionary, and our model selection scheme is robust to noise.

Data-driven method↗
DOE OSTI2025

Planar laser-induced fluorescence system for spatiotemporal ion velocity distribution function measurements

In this work, we present a planar laser-induced fluorescence (PLIF) system for measuring two-dimensional (2D), spatiotemporally resolved ion velocity distribution functions (IVDFs). A continuous-wave tunable diode laser produces a laser sheet that irradiates the plasma, and the resulting fluorescence is captured by an intensified CCD (ICCD) camera. Fluorescence images recorded at varying laser wavelengths are converted into 2D IVDFs using the Doppler shift principle. The developed diagnostic is implemented in an electron beam generated E × B plasma with a bulk plasma density of $\sim\!\!{10^{10}}{\text{c}}{{\text{m}}^{ - 3}}$ . The developed diagnostic is validated against a conventional single-point LIF method using photomultiplier tube-based detection, while significantly reducing the total measurement time by the number of spatial positions measured. The time-resolving capability of this diagnostic is tested by oscillating the plasma between two nominal operating modes with different density profiles and triggering the ICCD camera by the externally driven plasma oscillation. The measured 2D IVDF maps reveal several signatures of ion dynamics in this plasma source, including radially outflowing ions across the electric field and anomalous ion heating at the periphery, consistent with recent kinetic simulations and theoretical studies. A possible correlation between these ion kinetic features and rotating spoke structures is discussed.

E×B plasma↗
NASA NTRS1978

Large eddy simulation of incompressible turbulent channel flow

The three-dimensional, time-dependent primitive equations of motion were numerically integrated for the case of turbulent channel flow. A partially implicit numerical method was developed. An important feature of this scheme is that the equation of continuity is solved directly. The residual field motions were simulated through an eddy viscosity model, while the large-scale field was obtained directly from the solution of the governing equations. An important portion of the initial velocity field was obtained from the solution of the linearized Navier-Stokes equations. The pseudospectral method was used for numerical differentiation in the horizontal directions, and second-order finite-difference schemes were used in the direction normal to the walls. The large eddy simulation technique is capable of reproducing some of the important features of wall-bounded turbulent flows. The resolvable portions of the root-mean square wall pressure fluctuations, pressure velocity-gradient correlations, and velocity pressure-gradient correlations are documented.

Moin, P.↗
NASA NTRS2004

Kernel PLS Estimation of Single-trial Event-related Potentials

Nonlinear kernel partial least squaes (KPLS) regressior, is a novel smoothing approach to nonparametric regression curve fitting. We have developed a KPLS approach to the estimation of single-trial event related potentials (ERPs). For improved accuracy of estimation, we also developed a local KPLS method for situations in which there exists prior knowledge about the approximate latency of individual ERP components. To assess the utility of the KPLS approach, we compared non-local KPLS and local KPLS smoothing with other nonparametric signal processing and smoothing methods. In particular, we examined wavelet denoising, smoothing splines, and localized smoothing splines. We applied these methods to the estimation of simulated mixtures of human ERPs and ongoing electroencephalogram (EEG) activity using a dipole simulator (BESA). In this scenario we considered ongoing EEG to represent spatially and temporally correlated noise added to the ERPs. This simulation provided a reasonable but simplified model of real-world ERP measurements. For estimation of the simulated single-trial ERPs, local KPLS provided a level of accuracy that was comparable with or better than the other methods. We also applied the local KPLS method to the estimation of human ERPs recorded in an experiment on co,onitive fatigue. For these data, the local KPLS method provided a clear improvement in visualization of single-trial ERPs as well as their averages. The local KPLS method may serve as a new alternative to the estimation of single-trial ERPs and improvement of ERP averages.

Rosipal, Roman↗
NASA NTRS2020

EARLINET evaluation of the CATS Level 2 aerosol backscatter coefficient product

We present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the Cloud-Aerosol Transport System (CATS) aboard the International Space Station (ISS; Rodier et al., 2015). The study employs correlative CATS and EARLINET backscatter measurements within a 50 km distance between the ground station and the ISS overpass and as close in time as possible, typically with the starting time or stopping time of the EARLINET performed measurement time window within 90 min of the ISS overpass, for the period from February 2015 to September 2016. The results demonstrate the good agreement of the CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig, Germany; Évora, Portugal; and Dushanbe, Tajikistan, are analyzed here to demonstrate the performance of the CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions, CATS is in good agreement with EARLINET, independent of daytime and nighttime conditions. CATS low negative biases are observed, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds; these are biases which may lead to systematic deviations and slight underestimations of the total aerosol optical depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, occasionally leads to non-representative, unrealistic, and cloud-contaminated aerosol profiles. Regarding solar illumination conditions, low negative biases in CATS backscatter coefficient profiles, of the order of 6.1 %, indicate the good nighttime performance of CATS. During daytime, a reduced signal-to-noise ratio by solar background illumination prevents retrievals of weakly scattering atmospheric layers that would otherwise be detectable during nighttime, leading to higher negative biases, of the order of 22.3 %.

Emmanouil Proestakis↗
DOE OSTI2021

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Suicide is a leading cause of death worldwide, and non-fatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium. The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via mtCOJO, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders and other known risk factors. Results: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with non-psychiatric traits remained largely unchanged. Conclusions: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Adapting an Electron Microscopy Microheater for Correlated and Time-Resolved Ambient Pressure X-ray Photoelectron Spectroscopy

Environmental transmission electron microscopy (ETEM) can follow structural and chemical changes in nanomaterials under reaction conditions, including at temperatures up to 1300 °C and pressures up to ~20 mbar. However, ETEM studies are limited to localized areas of a sample and can benefit from correlative studies of a similar sample on larger length scales. Here, in this work, we describe the customization of a commercial microheater holder used in ETEM to anode-based ambient pressure X-ray photoelectron spectroscopy (APXPS), where chemical and electronic structure information is averaged over several hundred square micrometers. To benchmark heating capabilities in the APXPS instrument, core level binding energies were followed during surface chemical reactions of a Pd film, including CO adsorption–desorption, Pd oxidation, and PdO reduction. The fast heating feature of the microheaters advanced XPS experimental capabilities, including the collection of subsecond time-resolved spectra of the Pd 3d 5/2 peak during the reduction of an oxidized Pd film. The potential to use these heaters in a closed gas cell was also demonstrated by oxidizing Pd in a partial pressure of air locally dosed to the sample surface. General tips and considerations for the application of commercial ETEM heaters to any XPS system with a focused X-ray beam are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences

Fueled by breakthrough technology developments, the biological, biomedical, and behavioral sciences are now collecting more data than ever before. There is a critical need for time- and cost-efficient strategies to analyze and interpret these data to advance human health. The recent rise of machine learning as a powerful technique to integrate multimodality, multifidelity data, and reveal correlations between intertwined phenomena presents a special opportunityin this regard. However, classical machine learning techniques often ignore the fundamental laws of physics and result in ill-posed problems or non-physical solutions. Multiscale modeling is a successful strategy to integrate multiscale, multiphysics data and uncover mechanisms that explain the emergence of function. However, multiscale modeling alone often fails to efficiently combine large data sets from different sources and different levels of resolution. Here we demonstrate that machine learning and multiscale modeling can naturally complement each other to create robust predictive models that integrate the underlying physics to manage ill-posed problems and explore massive design spaces. We critically review the current literature, highlight applications and opportunities, address open questions, and discuss potential challenges and limitations in four overarching topical areas: ordinary differential equations, partial differential equations, data-driven approaches, and theory-driven approaches. Towards these goals, we leverage expertise in applied mathematics, computer science, computational biology, biophysics, biomechanics, engineering mechanics, experimentation, and medicine. Our multidisciplinary perspective suggests that integrating machine learning and multiscale modeling can provide new insights into disease mechanisms, help identify new targets and treatment strategies, and inform decision making for the benefit of human health.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1984

Real Surface Effects in Elastohydrodynamic Lubrication

Following a general discussion of real effects in EHL, consideration is given in detail to the role played by stochastic roughness superimposed on the nominal solid boundaries. Particular attention is given to the full-film EHL regime where incipient asperity contact bears a negligible fraction of the load. Flow, from which an averaged Reynolds equation can be formed, is nonetheless modified by the amplitude and texture of the roughness patterns. In describing these effects by means of certain well-defined flow factors, it is found that only two extra parameters are needed - the rms surface height and the ratio of the correlation lengths in the two principal roughness directions. In a lowest order perturbation expansion of these flow factors in powers of the ratio of rms roughness to nominal film thickness, no other properties of the roughness appear. In most cases of practical interest, the factors describing Poiseuille flow are separable into the sum of two single-surface flow factors which means that a combination of a single equivalent rough surface versus an ideal smooth surface can always be found. For flow entrained by slip velocity the factors separate instead into a difference of single-surface factors and it becomes significant which of the two surfaces carries the equivalent roughness. Results are discussed of some applications of the averaged Reynolds equation based on the flow factor method to the EHL line contact problem. Finally, the partial EHL regime is considered where comparable load fractions are carried by the hydrodynamic film and by incipient mechanical contact. An extension of the method into this regime by combining it with asperity contact models appears most encouraging.

John H Tripp↗
DOE OSTI2020

Improved band gaps and structural properties from Wannier–Fermi–Löwdin self-interaction corrections for periodic systems

The accurate prediction of band gaps and structural properties in periodic systems continues to be one of the central goals of electronic structure theory. However, band gaps obtained from popular exchange–correlation (XC) functionals (such as LDA and PBE) are severely underestimated partly due to the spurious self-interaction error (SIE) inherent to these functionals. In this work, we present a new formulation and implementation of Wannier function-derived Fermi–Löwdin (WFL) orbitals for correcting the SIE in periodic systems. Since our approach utilizes a variational minimization of the self-interaction energy with respect to the Wannier charge centers (WCC), it is computationally more efficient than the HSE hybrid functional and other self-interaction corrections that require a large number of transformation matrix elements. Here, calculations on several (17 in total) prototypical molecular solids, semiconductors, and wide-bandgap materials show that our WFL self-interaction correction approach gives better band gaps and bulk moduli compared to semilocal functionals, largely due to the partial removal of self-interaction errors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Efficient Loads Surrogates for Waked Turbines in an Array

Accurately and efficiently predicting wind turbine structural loading is a crucial step in wind farm design. Without considering structural loading, wind farm optimization could negatively impact turbine fatigue and ultimate loads, especially for waked and partially waked turbines, which could result in higher maintenance costs and reduced turbine lifetime. However, predicting turbine loads throughout an array is a costly step, as these quantities require time-accurate results across long time histories, which is often intractable for large array optimization. Therefore, surrogate models that link array spacing to load outputs are often used, but the surrogates are then unique to the inflow conditions and array configurations in the training library. This work develops surrogate models for many wind turbine load outputs based solely on rotor plane velocity measurements, with no required input about array configuration or freestream inflow parameters. Surrogate models were constructed for many turbine quantities of interest (QoI), considering mean, standard deviation, ultimate, and fatigue loads. In general, most QoI statistics were accurately captured, as measured by predicted vs. actual correlation coefficient, confirming the suitability of the approach. Temporal mean values of the QoI required only temporal mean measurements of the rotor plane inflow velocity. However, accurate prediction of temporal standard deviation, ultimate, and fatigue values of QoI also required temporal standard deviations of the rotor plane velocity field. Poor surrogate performance was observed when too many correlated inputs were used, such as multiple velocity components. If the fewest inflow parameters are used to construct the surrogates, the average correlation coefficient value for all output QoI statistics is 0.89. Surrogates for standard deviations and damage equivalent loads (DELs) of turbine QoIs generally had lower accuracy and tower-base and shaft load channels posed the most difficult to capture accurately. The results suggest that these surrogates could be easily paired with analytic wake models, which are frequently used for pre-construction wind farm array optimization, to account for turbine loading in addition to power production. By including the optimal inflow conditions, the surrogate accuracy can improve to an average correlation coefficient value for all output QoI statistics of 0.92. This work has established the ability to build accurate surrogates for mean, standard deviation, ultimate load, and DEL turbine QoI values based on the rotor plane inflow velocity, and identified which inflow conditions lead to greater surrogate accuracy.

17 WIND ENERGY↗
NASA NTRS2023

Partially Erupted Prominence Material as a Diagnostic of Coronal Mass Ejection Trajectory

Coronal mass ejections (CMEs) are energetic releases of large-scale magnetic structures from the Sun. CMEs can have impacts on spacecraft and at Earth. This trajectory is typically assumed to be radial, but often the CME moves outward with some spatial off set from the source region where the eruption initially occurred. A CME is frequently accompanied by a prominence eruption, a movement of cool, dense material up into the corona that can be ejected or fall back down. We investigate eruptions in which some portion of the prominence material falls back to the Sun along field lines which have reconfigured in the eruption, rather than draining back to the source or escaping with the CME. Using a method called persistence mapping, 304 ˚A images from the Solar Dynamics Observatory (SDO), and coronagraph images from the Solar and Heliospheric Observatory (SOHO), we measure and compare the offsets in latitude of 20 CMEs and their respective prominences with respect to the source region. The 20 events were chosen to sample over the first 10 years of the SDO mission. We find that the offsets are correlated. We find no difference between eruptions offset towards the equator or the poles, suggesting that the offset is a result of local changes in the eruptive field, rather than of the Sun’s global magnetic field structure. These findings help us contextualize individual eruptions and highlight changes in the local magnetic field associated with the prominence eruption.

B A Hovis-Afflerbach↗
DOE OSTI2023

Partial fillings of the bosonic $E$ 8 quantum Hall state

Here, we study bosonic topological phases constructed from electrons. In addition to a bulk excitation energy gap, these bosonic phases also have a fermion energy gap, below which all local excitations in the bulk and on the edge are even combinations of electrons. We focus on chiral phases, in which all low-energy edge excitations move in the same direction, that arise from the short-range entangled $E_8$ quantum Hall state, the bosonic analog of the filled lowest Landau level of electrons. The $E_8$ edge-state theory features an $E_8$ Kac-Moody symmetry that can be decomposed into ${\cal G}_A \times {\cal G}_B$ subalgebras, such as $SU(3) \times E_6$, $SO(M) \times SO(16-M)$, and $G_2 \times F_4$. (Here, $\{SO(M) \}$, $\{SU(N)\}$, and $\{E_8, G_2, F_4 \}$ denote orthogonal, unitary, and exceptional Lie algebras.) Using these symmetry decompositions, we construct exactly solvable coupled-wire model Hamiltonians for families of long-range entangled ${\cal G}_A$ or ${\cal G}_B$ bosonic fractional quantum Hall states that "partially fill" the $E_8$ state and are pairwise related by a generalized particle-hole symmetry. These long-range entangled states feature either Abelian or non-Abelian topological order. Some support the emergence of non-local Dirac and Majorana fermions, Ising anyons, metaplectic anyons, Fibonacci anyons, as well as deconfined $\mathbb{Z}_2$ gauge fluxes and charges.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Magnetic dichroism in the Kondo insulator SmB 6

Samarium hexaboride (${\mathrm{SmB}}_{6}$) is a purported topological Kondo insulator, with theory predicting that the experimentally observed metallic surface states manifest from a topologically nontrivial insulating bulk band structure. The insulating bulk itself is driven by strong correlations, and both bulk and surface are known to host compelling magnetic and electronic phenomena. We employed here x-ray absorption spectroscopy and x-ray magnetic circular dichroism at the Sm ${M}_{4,5}$ edges to probe the surface and bulk magnetic properties of ${\mathrm{Sm}}^{2+}$ and ${\mathrm{Sm}}^{3+}$ within ${\mathrm{SmB}}_{6}$. We observed an unexpected antialignment to the applied field of the ${\mathrm{Sm}}^{3+}$ magnetic dipole moment below $T=75$ K and of the total orbital moment of samarium below 30 K. The total bulk magnetization at 2 K is, however, positive and driven by ${\mathrm{Sm}}^{2+}$ Van Vleck susceptibility as well as 1% paramagnetic impurities with ${{\mu}}_{\mathrm{eff}}=5.2(1){{\mu}}_{\mathrm{B}}$. This indicates the diamagneticlike ${\mathrm{Sm}}^{3+}$ magnetism is only a portion of the net magnetization, partially offsetting the response of paramagnetic impurities known within the bulk.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Valorisation of Wasted Immature Tomato to Innovative Fermented Functional Foods

In this study, the lactic fermentation of immature tomatoes as a tool for food ingredient production was evaluated as a circular economy-oriented alternative for valorising industrial tomatoes that are unsuitable for processing and which have wasted away in large quantities in the field. Two lactic acid bacteria (LAB) were assessed as starter cultures in an immature tomato pulp fermentation to produce functional food ingredients with probiotic potential. The first trial evaluated the probiotic character of Lactiplantibacillus plantarum (LAB97, isolated from immature tomato microbiota) and Weissella paramesenteroides (C1090, from the INIAV collection) through in vitro gastrointestinal digestion simulation. The results showed that LAB97 and C1090 met the probiotic potential viability criterion by maintaining 6 log10 CFU/mL counts after in vitro simulation. The second trial assessed the LAB starters’ fermentative ability. Partially decontaminated (110 °C/2 min) immature tomato pulp was used to prepare the individually inoculated samples (Id: LAB97 and C1090). Non-inoculated samples, both with and without thermal treatment (Id: CTR-TT and CTR-NTT, respectively), were prepared as the controls. Fermentation was undertaken (25 °C, 100 rpm) for 14 days. Throughout storage (0, 24, 48, 72 h, 7, and 14 days), all the samples were tested for LAB and Y&M counts, titratable acidity (TA), solid soluble content (SSC), total phenolic content (TPC), antioxidant capacity (AOx), as well as for organic acids and phenolic profiles, and CIELab colour and sensory evaluation (14th day). The LAB growth reached ca. 9 log10 CFU/mL for all samples after 72 h. The LAB97 samples had an earlier and higher acidification rate than the remaining ones, and they were highly correlated to lactic acid increments. The inoculated samples showed a faster and higher decrease rate in their SSC levels when compared to the controls. A nearly two-fold increase (p < 0.05) during the fermentation, over time, was observed in all samples’ AOx and TPC (p < 0.05, r = 0.93; similar pattern). The LAB97 samples obtained the best sensory acceptance for flavour and overall appreciation scores when compared to the others. In conclusion, the L. plantarum LAB97 starter culture was selected as a novel probiotic candidate to obtain a potential probiotic ingredient from immature tomato fruits.

Pereira, Nelson (ORCID:0000000345745615)↗
DOE OSTI2025

Cosmohedra

It has been a long-standing challenge to find a geometric object underlying the cosmological wavefunction for Tr(ϕ 3 ) theory, generalizing associahedra and surfacehedra for scattering amplitudes. In this note, we describe a new class of polytopes — “cosmohedra” — that provide a natural solution to this problem. The faces of associahedra capture the combinatorics of non-overlapping chords of the momentum polygon, reflecting all partial factorizations of amplitudes. Cosmohedra are far richer — instead of non-overlapping chords, their faces capture the “russian doll” structure of non-overlapping subpolygons that determine the wavefunction. We show that cosmohedra are intimately related to associahedra, obtained by “blowing up” faces of the associahedron in a simple way. We give a full combinatorial description of cosmohedron faces and their factorization properties, and provide an explicit realization in terms of facet inequalities that further “shave” the facet inequalities of the associahedron. We also discuss a novel way for computing the wavefunction from cosmohedron geometry that extends the usual connection with polytope canonical forms. We illustrate cosmohedra with examples at tree-level and one loop; the close connection to surfacehedra suggests the generalization to all loop orders. Moving beyond the wavefunction, we briefly describe “cosmological correlahedra” for full correlators, which are one higher-dimensional polytopes, interpolating between associahedra and cosmohedra on opposite facets in an extra direction associated with the total energy. We speculate on how the existence of cosmohedra might suggest a “stringy” formulation for the cosmological wavefunction/correlators, generalizing the way in which the Minkowski sum decomposition of associahedra naturally extend particle to string amplitudes.

Scattering Amplitudes↗
NASA NTRS2000

Color M-mode Doppler flow propagation velocity is a preload insensitive index of left ventricular relaxation: animal and human validation

OBJECTIVES: To determine the effect of preload in color M-mode Doppler flow propagation velocity (v(p)). BACKGROUND: The interpretation of Doppler filling patterns is limited by confounding effects of left ventricular (LV) relaxation and preload. Color M-mode v(p) has been proposed as a new index of LV relaxation. METHODS: We studied four dogs before and during inferior caval (IVC) occlusion at five different inotropic stages and 14 patients before and during partial cardiopulmonary bypass. Left ventricular (LV) end-diastolic volumes (LV-EDV), the time constant of isovolumic relaxation (tau), left atrial (LA) pre-A and LV end-diastolic pressures (LV-EDP) were measured. Peak velocity during early filling (E) and v(p) were extracted by digital analysis of color M-mode Doppler images. RESULTS: In both animals and humans, LV-EDV and LV-EDP decreased significantly from baseline to IVC occlusion (both p < 0.001). Peak early filling (E) velocity decreased in animals from 56 +/- 21 to 42 +/- 17 cm/s (p < 0.001) without change in v(p) (from 35 +/- 15 to 35 +/- 16, p = 0.99). Results were similar in humans (from 69 +/- 15 to 53 +/- 22 cm/s, p < 0.001, and 37 +/- 12 to 34 +/- 16, p = 0.30). In both species, there was a strong correlation between LV relaxation (tau) and v(p) (r = 0.78, p < 0.001, r = 0.86, p < 0.001). CONCLUSIONS: Our results indicate that color M-mode Doppler v(p) is not affected by preload alterations and confirms that LV relaxation is its main physiologic determinant in both animals during varying lusitropic conditions and in humans with heart disease.

Non-NASA Center↗