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The combined force field-sampling problem in simulations of disordered amyloid-β peptides
Molecular dynamics simulations of intrinsically disordered proteins (IDPs) can provide high resolution structural ensembles if the force field is accurate enough and if the simulation sufficiently samples the conformational space of the IDP with the correct weighting of sub-populations. Here, we investigate the combined force field–sampling problem by testing a standard force field as well as newer fixed charge force fields, the latter specifically motivated for better description of unfolded states and IDPs, and comparing them with a standard temperature replica exchange (TREx) protocol and a non-equilibrium Temperature Cool Walking (TCW) sampling algorithm. The force field and sampling combinations are used to characterize the structural ensembles of the amyloid-beta peptides Aβ42 and Aβ43, which both should be random coils as shown recently by experimental nuclear magnetic resonance (NMR) and 2D Förster resonance energy transfer (FRET) experiments. The results illustrate the key importance of the sampling algorithm: while the standard force field using TREx is in poor agreement with the NMR J-coupling and nuclear Overhauser effect and 2D FRET data, when using the TCW method, the standard and optimized protein-water force field combinations are in very good agreement with the same experimental data since the TCW sampling method produces qualitatively different ensembles than TREx. Lastly, we also discuss the relative merit of the 2D FRET data when validating structural ensembles using the different force fields and sampling protocols investigated in this work for small IDPs such as the Aβ42 and Aβ43 peptides.
Particle Acceleration and Fractional Transport in Turbulent Reconnection
We consider a large-scale environment of turbulent reconnection that is fragmented into a number of randomly distributed unstable current sheets (UCSs), and we statistically analyze the acceleration of particles within this environment. We address two important cases of acceleration mechanisms when particles interact with the UCS: (a) electric field acceleration and (b) acceleration by reflection at contracting islands. Electrons and ions are accelerated very efficiently, attaining an energy distribution of power-law shape with an index 1–2, depending on the acceleration mechanism. The transport coefficients in energy space are estimated from test-particle simulation data, and we show that the classical Fokker–Planck (FP) equation fails to reproduce the simulation results when the transport coefficients are inserted into it and it is solved numerically. The cause for this failure is that the particles perform Levy flights in energy space, while the distributions of the energy increments exhibit power-law tails. We then use the fractional transport equation (FTE) derived by Isliker et al., whose parameters and the order of the fractional derivatives are inferred from the simulation data, and solving the FTE numerically, we show that the FTE successfully reproduces the kinetic energy distribution of the test particles. We discuss in detail the analysis of the simulation data and the criteria that allow one to judge the appropriateness of either an FTE or a classical FP equation as a transport model.
Magnetic exchange disorder in low-dimensional quantum magnets
Low-dimensional quantum magnetism is currently of great interest due to the fact that reduced dimensionality can support strong quantum fluctuations, which may lead to unusual phenomena and quantum-critical behavior. The effect of random exchange strengths in two-dimensional (2D) antiferromagnets is still not fully understood despite much effort. This project aims to rectify this by investigating the high-field properties of the 2D coordination polymer (QuinH) 2 Cu(Cl x Br 1-x ) 4 .2H 2 O. The exchange pathway is through Cu-Halide-Cu bonds, and by randomizing the proportion of chlorine and bromine atoms in the unit cell, disorder can be introduced into the system.
Tunable Stochasticity in an Artificial Spin Network
Metamaterials present the possibility of artificially generating advanced functionalities through engineering of their internal structure. Artificial spin networks, in which a large number of nanoscale magnetic elements are coupled together, are promising metamaterial candidates that enable the control of collective magnetic behavior through tuning of the local interaction between elements. In this work, the motion of magnetic domain-walls in an artificial spin network leads to a tunable stochastic response of the metamaterial, which can be tailored through an external magnetic field and local lattice modifications. This type of tunable stochastic network produces a controllable random response exploiting intrinsic stochasticity within magnetic domain-wall motion at the nanoscale. An iconic demonstration used to illustrate the control of randomness is the Galton board. In this system, multiple balls fall into an array of pegs to generate a bell-shaped curve that can be modified via the array spacing or the tilt of the board. A nanoscale recreation of this experiment using an artificial spin network is employed to demonstrate tunable stochasticity. Furthermore, this type of tunable stochastic network opens new paths toward post-Von Neumann computing architectures such as Bayesian sensing or random neural networks, in which stochasticity is harnessed to efficiently perform complex computational tasks.
On thermalization in the SYK and supersymmetric SYK models
The eigenstate thermalization hypothesis is a compelling conjecture which strives to explain the apparent thermal behavior of generic observables in closed quantum systems. Although we are far from a complete analytic understanding, quantum chaos is often seen as a strong indication that the ansatz holds true. In this paper, we address the thermalization of energy eigenstates in the Sachdev-Ye-Kitaev model, a maximally chaotic model of strongly-interacting Majorana fermions. We numerically investigate eigenstate thermalization for specific few-body operators in the original SYK model as well as its N = 1 supersymmetric extension and find evidence that these models satisfy ETH. In conclusion, we discuss the implications of ETH for a gravitational dual and the quantum information-theoretic properties of SYK it suggests.
Spectral form factor in sparse SYK models
We investigate the spectral form factor of the sparse Sachdev-Ye-Kitaev model. We use numerical methods to establish that at intermediate times the connected part of the spectral form factor is the dominant one. These connected contributions arise from fluctuations around the disconnected geometry, not from a new saddle point. A similar effect was previously conjectured in SYK but required a value of N out of reach of current numerical simulations.
Experimental investigation of cross flow mixing in a randomly packed bed and streamwise vortex characteristics using particle image velocimetry and proper orthogonal decomposition analysis
The study of flow and heat transfer through porous media or randomly packed beds is important as these configurations are widely used in many engineering applications, for example, heat energy storage, chemical catalytic reactors, and nuclear reactors. The flow mixing characteristics in a cross-flow plane of a facility with randomly packed spheres at an aspect ratio of 6.3 were experimentally investigated. The velocity fields at several regions of the cross-flow plane located in the vicinity of the wall and in the pores between spheres were obtained by applying the matched-index-of-refraction and time-resolved particle image velocimetry (TR-PIV) techniques for Reynolds numbers ranging from 700 to 1700. The TR-PIV results revealed various flow patterns in the transverse plane of the packed spheres, including swirling flow structures aligned with the axial flow direction, a strong bypass flow near the enclosure wall, and a circulation region created when the bypass flow ejected into a large spatial gap. When the Reynolds number was increased, the peaks of root-mean-square fluctuating velocities, $u'_{rms}$ and $v'_{rms}$, were found to increase approximately at the same ratio as the increase in Reynolds number, and the magnitude of the Reynolds stress increased considerably. In addition, the characteristics of flow mixing in different flow regions were investigated via the two-point cross-correlation of fluctuating velocities. Using Taylor’s hypothesis, the vorticity iso-surfaces were constructed. Thus, constructed iso-surfaces showed that shear layers generated from the bypass flow gaps were stretched, broken into smaller flow structures, and then evolved as vortex pairs when entering the neighboring gaps. The results obtained by applying proper orthogonal decomposition (POD) analysis to the velocity fields showed that the statistically dominant flow structures had approximately the same size and shape as those depicted by Taylor’s hypothesis. Vortex characteristics, such as populations, spatial distributions, and strengths, for various spatial regions and Reynolds numbers were obtained by a combination of POD analysis and vortex identification.
Investigating microstructure evolution in block copolymer membranes
Block copolymer self-assembly in conjunction with nonsolvent-induced phase separation (SNIPS) has been increasingly leveraged to fabricate integral-asymmetric membranes. The large number of formulation and processing parameters associated with SNIPS, however, has prevented the reliable construction of high performance membranes. In this study, we apply dynamical self-consistent field theory to model the SNIPS process and investigate the effect of various parameters on the membrane morphology: solvent selectivity, nonsolvent selectivity, initial film composition, and glass transition composition. We examine how solvent selectivity and concentration of polymers in the film impact the structure of micelles that connect to form the membrane matrix. In particular, we find that preserving the order in the surface layer and forming a connection between the supporting and surface layer are nontrivial and sensitive to each parameter studied. Furthermore, the effect of each parameter is discussed, and suggestions are made for successfully fabricating viable block copolymer membranes.
First-principles modeling of plasmons in aluminum under ambient and extreme conditions
The theoretical understanding of plasmon behavior is crucial for an accurate interpretation of inelastic scattering diagnostics in many experiments. In this work, we highlight the utility of linear response time-dependent density functional theory (LR-TDDFT) as a first-principles framework for consistently modeling plasmon properties. We provide a comprehensive analysis of plasmons in aluminum from ambient to warm dense matter conditions and assess typical properties such as the dynamical structure factor, the plasmon dispersion, and the plasmon lifetime. We compare our results with scattering measurements and with other TDDFT results as well as models such as the random phase approximation, the Mermin approach, and the dielectric function obtained using static local field corrections of the uniform electron gas parametrized from path-integral Monte Carlo simulations. We conclude that results for the plasmon dispersion and lifetime are inconsistent between experiment and theories and that the common practice of extracting and studying plasmon dispersion relations is an insufficient procedure to capture the complicated physics contained in the dynamic structure factor in its full breadth.
A new open‐path eddy covariance method for nitrous oxide and other trace gases that minimizes temperature corrections
Abstract Low‐power, open‐path gas sensors enable eddy covariance (EC) flux measurements in remote areas without line power. However, open‐path flux measurements are sensitive to fluctuations in air temperature, pressure, and humidity. Laser‐based, open‐path sensors with the needed sensitivity for trace gases like methane (CH 4 ) and nitrous oxide (N 2 O) are impacted by additional spectroscopic effects. Corrections for these effects, especially those related to temperature fluctuations, often exceed the flux of gases, leading to large uncertainties in the associated fluxes. For example, the density and spectroscopic corrections arising from temperature fluctuations can be one or two orders of magnitude greater than background N 2 O fluxes. Consequently, measuring background fluxes with laser‐based, open‐path sensors is extremely challenging, particularly for N 2 O and gases with similar high‐precision requirements. We demonstrate a new laser‐based, open‐path N 2 O sensor and a general approach applicable to other gases that minimizes temperature‐related corrections for EC flux measurements. The method identifies absorption lines with spectroscopic effects in the opposite direction of density effects from temperature and, thus, density and spectroscopic effects nearly cancel one another. The new open‐path N 2 O sensor was tested at a corn ( Zea mays L.) field in Southwestern Michigan, United States. The sensor had an optimal precision of 0.1 ppbv at 10 Hz and power consumption of 50 W. Field trials showed that temperature‐related corrections were 6% of density corrections, reducing EC random errors by 20‐fold compared to previously examined lines. Measured open‐path N 2 O EC fluxes showed excellent agreement with those made with static chambers ( m = 1.0 ± 0.3; r 2 = .96). More generally, we identified absorption lines for CO 2 and CH 4 flux measurements that can reduce the temperature‐related corrections by 10–100 times compared to existing open‐path sensors. The proposed method provides a new direction for future open‐path sensors, facilitating the expansion of accurate EC flux measurements.
Single-energy computed tomography-based pulmonary perfusion imaging: Proof-of-principle in a canine model
Purpose: Radiotherapy (RT) that selectively avoids irradiating highly functional lung regions may reduce pulmonary toxicity, which is substantial in lung cancer RT. Single-energy computed tomography (CT) pulmonary perfusion imaging has several advantages (e.g., higher resolution) over other modalities and has great potential for widespread clinical implementation, particularly in RT. The purpose of this study was to establish proof-of-principle for single-energy CT perfusion imaging. Methods: Single-energy CT perfusion imaging is based on the following: (1) acquisition of end-inspiratory breath-hold CT scans before and after intravenous injection of iodinated contrast agents, (2) deformable image registration (DIR) for spatial mapping of those two CT image data sets, and (3) subtraction of the precontrast image data set from the postcontrast image data set, yielding a map of regional Hounsfield unit (HU) enhancement, a surrogate for regional perfusion. In a protocol approved by the institutional animal care and use committee, the authors acquired CT scans in the prone position for a total of 14 anesthetized canines (seven canines with normal lungs and seven canines with diseased lungs). The elastix algorithm was used for DIR. The accuracy of DIR was evaluated based on the target registration error (TRE) of 50 anatomic pulmonary landmarks per subject for 10 randomly selected subjects as well as on singularities (i.e., regions where the displacement vector field is not bijective). Prior to perfusion computation, HUs of the precontrast end-inspiratory image were corrected for variation in the lung inflation level between the precontrast and postcontrast end-inspiratory CT scans, using a model built from two additional precontrast CT scans at end-expiration and midinspiration. The authors also assessed spatial heterogeneity and gravitationally directed gradients of regional perfusion for normal lung subjects and diseased lung subjects using a two-sample two-tailed t-test. Results: The mean TRE (and standard deviation) was 0.6 ± 0.7 mm (smaller than the voxel dimension) for DIR between pre contrast and postcontrast end-inspiratory CT image data sets. No singularities were observed in the displacement vector fields. The mean HU enhancement (and standard deviation) was 37.3 ± 10.5 HU for normal lung subjects and 30.7 ± 13.5 HU for diseased lung subjects. Spatial heterogeneity of regional perfusion was found to be higher for diseased lung subjects than for normal lung subjects, i.e., a mean coefficient of variation of 2.06 vs 1.59 (p = 0.07). The average gravitationally directed gradient was strong and significant (R{sup 2} = 0.99, p < 0.01) for normal lung dogs, whereas it was moderate and nonsignificant (R{sup 2} = 0.61, p = 0.12) for diseased lung dogs. Conclusions: This canine study demonstrated the accuracy of DIR with subvoxel TREs on average, higher spatial heterogeneity of regional perfusion for diseased lung subjects than for normal lung subjects, and a strong gravitationally directed gradient for normal lung subjects, providing proof-of-principle for single-energy CT pulmonary perfusion imaging. Further studies such as comparison with other perfusion imaging modalities will be necessary to validate the physiological significance.
Cosmological gamma-ray burst model
A cosmological gamma-ray burst model that reproduces the observed gamma-ray spectra was developed. This model, which is an outgrowth of work on synchrotron emission from cosmological sources, creates the observed spectra from a power law spectrum through Compton attenuation in dense molecular clouds. It restricts the burst source to the centers of galaxies, and it is easily tested through comparisons with time dependent burst spectra. Dr. Brainerd continued development of a Monte Carlo code that tracks the random walk of a gamma-ray through a plasma in a strong magnetic field and used this code to show that a two temperature plasma in a strong magnetic field can suppress soft x-ray emission.
Universal Signal Conditioning Amplifier
The Technological Research and Development Authority (TRDA) and NASA-KSC entered into a cooperative agreement in March of 1994 to achieve the utilization and commercialization of a technology development for benefiting both the Space Program and U.S. industry on a "dual-use basis". The technology involved in this transfer is a new, unique Universal Conditioning Amplifier (USCA) used in connection with various types of transducers. The project was initiated in partnership with I-Net Corporation, Lockheed Martin Telemetry & Instrumentation (formerly Loral Test and Information Systems) and Brevard Community College. The project consists of designing, miniaturizing, manufacturing, and testing an existing prototype of USCA that was developed for NASA-KSC by the I-Net Corporation. The USCA is a rugged and field-installable self (or remotely)- programmable amplifier that works in combination with a tag random access memory (RAM) attached to various types of transducers. This summary report comprises performance evaluations, TRDA partnership tasks, a project summary, project milestones and results.
Geospatial Method for Computing Supplemental Multi-Decadal U.S. Coastal Land-Use and Land-Cover Classification Products, Using Landsat Data and C-CAP Products
This paper discusses the development and implementation of a geospatial data processing method and multi-decadal Landsat time series for computing general coastal U.S. land-use and land-cover (LULC) classifications and change products consisting of seven classes (water, barren, upland herbaceous, non-woody wetland, woody upland, woody wetland, and urban). Use of this approach extends the observational period of the NOAA-generated Coastal Change and Analysis Program (C-CAP) products by almost two decades, assuming the availability of one cloud free Landsat scene from any season for each targeted year. The Mobile Bay region in Alabama was used as a study area to develop, demonstrate, and validate the method that was applied to derive LULC products for nine dates at approximate five year intervals across a 34-year time span, using single dates of data for each classification in which forests were either leaf-on, leaf-off, or mixed senescent conditions. Classifications were computed and refined using decision rules in conjunction with unsupervised classification of Landsat data and C-CAP value-added products. Each classification's overall accuracy was assessed by comparing stratified random locations to available reference data, including higher spatial resolution satellite and aerial imagery, field survey data, and raw Landsat RGBs. Overall classification accuracies ranged from 83 to 91% with overall Kappa statistics ranging from 0.78 to 0.89. The accuracies are comparable to those from similar, generalized LULC products derived from C-CAP data. The Landsat MSS-based LULC product accuracies are similar to those from Landsat TM or ETM+ data. Accurate classifications were computed for all nine dates, yielding effective results regardless of season. This classification method yielded products that were used to compute LULC change products via additive GIS overlay techniques.
Role of Small-Scale Impulsive Events in Heating the X-Ray Bright Points of the Quiet Sun
Small-scale impulsive events, known as nanoflares, are thought to be one of the prime candidates that can keep the solar corona hot at its multimillion-Kelvin temperature. Individual nanoflares are difficult to detect with the current generation of instruments; however, their presence can be inferred through indirect techniques such as Differential Emission Measure (DEM) analysis. Here, we employ this technique to investigate the possibility of nanoflare heating of the quiet corona during the minimum of solar cycle 24. We estimate the DEM of disk-integrated quiet Sun and X-ray bright points (XBP) using the observations from XSM on board the Chandrayaan-2 orbiter and AIA on board the Solar Dynamic Observatory. XBPs are found to be the dominant contributor to disk-integrated X-rays, with a radiative flux of ∼2 × 10 5 erg cm −2 s −1 . XBPs consist of small-scale loops associated with bipolar magnetic fields. We simulate such XBP loops using the EBTEL hydrodynamic code. The lengths and magnetic field strengths of these loops are obtained through a potential field extrapolation of the photospheric magnetogram. Each loop is assumed to be heated by random nanoflares having an energy that depends on the loop properties. The composite nanoflare energy distribution for all the loops has a power-law slope close to −2.5. The simulation output is then used to obtain the integrated DEM. It agrees remarkably well with the observed DEM at temperatures above 1 MK, suggesting that the nanoflare distribution, as predicted by our model, can explain the XBP heating.
Intermountain West Wildland Fires: Mapping Tree Mortality and Burn Patches using NASA Earth Observations to Determine Fire Risk and Inform Fire Management Practices
Within the intermountain west, monitoring fuel loads is a major concern for wildland fire management efforts. To address this concern, we partnered with the U.S. Forest Service to inform the agency which forested areas should be prioritized for prescribed burning and fuel reduction near human communities in the Bridger-Teton National Forest, Wyoming. We created burn maps, fuel load maps, and a tutorial document to identify forest impact trends and provide the partner with the tools to replicate project methods for expansion to other wildfire crisis strategy sites. These end products were made using two NASA Earth observations: Landsat 8 Operational Land Imager and Shuttle Radar Topography Mission. Based on our random forest analysis, our maps identified 998 acres within the Wildland Urban Interface that are predicted to have high fuel loading and high burn severity within the Bridger-Teton National Forest. Forested areas closer to heavily populated areas such as Jackson, Kelly, Moran, New Forks Lake, and Star Valley Ranch should be prioritized for fuel reduction. However, our random forest model analysis was limited to using vegetation and topographical indices with no field data for model validation. Therefore, future studies should use field data for model validation to improve model accuracy and additionally incorporate Global Ecosystem Dynamics Investigation data into models to create better predictions of forested areas with high fuel load and high burn severity.
Centrifuge Study of Pilot Tolerance to Acceleration and the Effects of Acceleration on Pilot Performance
A research program the general objective of which was to measure the effects of various sustained accelerations on the control performance of pilots, was carried out on the Aviation Medical Acceleration Laboratory centrifuge, U.S. Naval Air Development Center, Johnsville, PA. The experimental setup consisted of a flight simulator with the centrifuge in the control loop. The pilot performed his control tasks while being subjected to acceleration fields such as might be encountered by a forward-facing pilot flying an atmosphere entry vehicle. The study was divided into three phases. In one phase of the program, the pilots were subjected to a variety of sustained linear acceleration forces while controlling vehicles with several different sets of longitudinal dynamics. Here, a randomly moving target was displayed to the pilot on a cathode-ray tube. For each combination of acceleration field and vehicle dynamics, pilot tracking accuracy was measured and pilot opinion of the stability and control characteristics was recorded. Thus, information was obtained on the combined effects of complexity of control task and magnitude and direction of acceleration forces on pilot performance. These tests showed that the pilot's tracking performance deteriorated markedly at accelerations greater than about 4g when controlling a lightly damped vehicle. The tentative conclusion was also reached that regardless of the airframe dynamics involved, the pilot feels that in order to have the same level of control over the vehicle, an increase in the vehicle dynamic stability was required with increases in the magnitudes of the acceleration impressed upon the pilot. In another phase, boundaries of human tolerance of acceleration were established for acceleration fields such as might be encountered by a pilot flying an orbital vehicle. A special pilot restraint system was developed to increase human tolerance to longitudinal decelerations. The results of the tests showed that human tolerance of longitudinal deceleration forces was considerably improved through use of the special restraint system.