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At least 1,801 records · Page 100

Advanced NASA Earth Science Mission Concept for Vegetation 3D Structure, Biomass and Disturbance

Carbon in forest canopies represents about 85% of the total carbon in the Earth's aboveground biomass (Olson et al., 1983). A major source of uncertainty in global carbon budgets derives from large errors in the current estimates of these carbon stocks (IPCC, 2001). The magnitudes and distributions of terrestrial carbon storage along with changes in sources and sinks for atmospheric C02 due to land use change remain the most significant uncertainties in Earth's carbon budget. These uncertainties severely limit accurate terrestrial carbon accounting; our ability to evaluate terrestrial carbon management schemes; and the veracity of atmospheric C02 projections in response to further fossil fuel combustion and other human activities. Measurements of vegetation three-dimensional (3D) structural characteristics over the Earth's land surface are needed to estimate biomass and carbon stocks and to quantify biomass recovery following disturbance. These measurements include vegetation height, the vertical profile of canopy elements (i.e., leaves, stems, branches), andlor the volume scattering of canopy elements. They are critical for reducing uncertainties in the global carbon budget. Disturbance by natural phenomena, such as fire or wind, as well as by human activities, such as forest harvest, and subsequent recovery, complicate the quantification of carbon storage and release. The resulting spatial and temporal heterogeneity of terrestrial biomass and carbon in vegetation make it very difficult to estimate terrestrial carbon stocks and quantify their dynamics. Vegetation height profiles and disturbance recovery patterns are also required to assess ecosystem health and characterize habitat. The three-dimensional structure of vegetation provides habitats for many species and is a control on biodiversity. Canopy height and structure influence habitat use and specialization, two fundamental processes that modify species richness and abundance across ecosystems. Accurate and consistent 3D measurements of forest structure at the landscape scale are needed for assessing impacts to animal habitats and biodiversity following disturbance.

Ranson, K. Jon↗

Rare Earth Element Measurements of Melilite and Fassaite in Allende Cai by Nanosims

The rare earth elements (REEs) are concentrated in CAIs by approx. 20 times the chondritic average [e.g., 1]. The REEs in CAIs are important to understand processes of CAI formation including the role of volatilization, condensation, and fractional crystallization [1,2]. REE measurements are a well established application of ion microprobes [e.g., 3]. However the spatial resolution of REE measurements by ion microprobe (approx.20 m) is not adequate to resolve heterogeneous distributions of REEs among/within minerals. We have developed methods for measuring REE with the NanoSIMS 50L at smaller spatial scales. Here we present our initial measurements of REEs in melilite and fassaite in an Allende Type-A CAI with the JSC NanoSIMS 50L. We found that the key parameters for accurate REE abundance measurements differ between the NanoSIMS and conventional SIMS, in particular the oxide-to-element ratios, the relative sensitivity factors, the energy distributions, and requisite energy offset. Our REE abundance measurements of the 100 ppm REE diopside glass standards yielded good reproducibility and accuracy, 0.5-2.5 % and 5-25 %, respectively. We determined abundances and spatial distributions of REEs in core and rim within single crystals of fassaite, and adjacent melilite with 5-10 m spatial resolution. The REE abundances in fassaite core and rim are 20-100 times CI abundance but show a large negative Eu anomaly, exhibiting a well-defined Group III pattern. This is consistent with previous work [4]. On the other hand, adjacent melilite shows modified Group II pattern with no strong depletions of Eu and Yb, and no Tm positive anomaly. REE abundances (2-10 x CI) were lower than that of fassaite. These patterns suggest that fassaite crystallized first followed by a crystallization of melilite from the residual melt. In future work, we will carry out a correlated study of O and Mg isotopes and REEs of the CAI in order to better understand the nature and timescales of its formation process and subsequent metamorphic history.

Ito, M.↗

A High-resolution Model of Field-aligned Currents Through Empirical Orthogonal Functions Analysis (MFACE)

Ten years of CHAMP magnetic field measurements are integrated into MFACE, a model of field-aligned currents (FACs) using empirical orthogonal functions (EOFs). EOF1 gives the basic Region-1/Region-2 pattern varying mainly with the interplanetary magnetic field Bz component. EOF2 captures separately the cusp current signature and By-related variability. Compared to existing models, MFACE yields significantly better spatial resolution, reproduces typically observed FAC thickness and intensity, improves on the magnetic local time (MLT) distribution, and gives the seasonal dependence of FAC latitudes and the NBZ current signature. MFACE further reveals systematic dependences on By, including 1) Region-1/Region-2 topology modifications around noon; 2) imbalance between upward and downward maximum current density; 3) MLT location of the Harang discontinuity. Furthermore, our procedure allows quantifying response times of FACs to solar wind driving at the bow shock nose: we obtain 20 minutes and 35-40 minutes lags for the FAC density and latitude, respectively.

CHAMP↗

Reconstruction of Six-Dimensional Phase Space

A phase space is a mathematical representation of all possible physical states of a system. Particle beams at Fermilab exist within a six-dimensional (6D) phase space defined by three positional components, (x, y, z) and three momentum components, (px, py, pz). To reconstruct this space implies taking measurement data from detectors and mapping out particle behavior using computational methods. The beam detectors, however, are only able to detect spatial distribution among the events of the beam, therefore being limited to positional data. Also, due to the vast number of events in a particle beam, it is extremely difficult to analyze and differentiate every single one’s behavior. However, with Machine Learning (ML), which can distinguish between patterns and map out particle behavior more efficiently. We first used the particle beam software, G4beamline, to simulate a 10,000-event muon beam, adjusting parameters such as initial momentum magnitude (p¬0) and virtual detector position. Using ten virtual detectors, we analyzed p0 values such that minimum 9,990 events were analyzed by every detector. We then input the data from these beam simulations to a C++ program, that randomly selects 100 events, and creates a 2D histogram based on spatial distribution, detector position, and event intensity. This process is repeated 100 times to create 100 histograms per p0 value. These images were then input to a modified ResNet18 Convolutional Neural Network (CNN) for training, and to predict p0 from some unseen set of histograms. The model was accurate when trained on momentum increments of 5 MeV/c and provided with denser training samples around highly variable test values. These results displayed machine learning being able to accurately predict p0 from being trained on different particle behaviors.

Shirlee, Jermain [Fermilab]↗

Temporal and spatial mapping of surface albedo and atmospheric dust opacity on Mars

The Mariner 9 and Viking provided abundant evidence that eolian processes are active over much of the surface of Mars. Past studies have demonstrated that variations in regional albedo and wind-streak patterns are indicative of sediment transport through a region, while thermal inertia data (derived from the Viking Infrared Thermal Mapper (IRTM) dataset) are indicative of the degree of surface mantling by dust deposits. The visual and thermal data are therefore diagnostic of whether net erosion or deposition of dust-storm fallout is taking place currently and whether such processes have been active in a region over the long term. These previous investigations, however, have not attempted to correct for the effects of atmospheric dust loading on observations of the martian surface, so quantitative studies of current sediment transport rates have included large errors due to uncertainty in the magnitude of this 'atmospheric component' of the observations. We have developed a radiative transfer model that allows the atmospheric dust opacity to be determined from IRTM thermal observations. Corrections for the effects of atmospheric dust loading on observations of surface albedo can also be modeled. This approach to determining 'dust-corrected surface albedo' incorporates the atmospheric dust opacity, the single-scattering albedo and particle phase function of atmospheric dust, and the bidirectional reflectance of the surface, and it accounts for variable lighting and viewing geometry.

Lee, S. W.↗

Temporal and spatial mapping of atmospheric dust opacity and surface albedo on Mars

The Mariner 9 and Viking missions provided abundant evidence that eolian processes are active over much of the surface of Mars. Past studies have demonstrated that variations in regional albedo and wind streak patterns are indicative of sediment transport through a region, while thermal inertia data (derived from the Viking Infrared Thermal Mapper (IRTM) datasets) are indicative of the degree of surface mantling by dust deposits. We are making use of the method developed by T. Z. Martin to determine dust opacity from IRTM thermal observations. We have developed a radiative transfer model that allows corrections for the effects of atmospheric dust loading on observations of surface albedo to be made. This approach to determining 'dust-corrected surface albedo' incorporates the atmospheric dust opacity, the single-scattering albedo and particle phase function of atmospheric dust, the bidirectional reflectance of the surface, and accounts for variable lighting and viewing geometry.

Lee, S. W.↗

On the Effect of Rigid Swept Surface Waves on Turbulent Drag

Passive turbulent drag reduction techniques are of interest as a cost effective means to improve air vehicle fuel consumption. In the past, rigid surface waves slanted at an angle from the streamwise direction were deemed ineffective to reduce skin friction drag due to the pressure drag that they generate. A recent analysis seeking similarities to the spanwise shear stress generated by spatial Stokes layers suggested that there may be a range of wavelength, amplitude, and orientation in which the wavy surface would reduce turbulent drag. The present work explores, by experiments and Direct Numerical Simulations (DNS), the effect of swept wavy surfaces on skin friction and pressure drag. Plates with shallow and deep wave patterns were rapid-prototyped and tested using a drag balance in the 7x11 inch Low-Speed Wind Tunnel at the NASA LaRC Research Center. The measured drag o set between the wavy plates and the reference at plate is found to be within the experimental repeatability limit. Oil vapor flow measurements indicate a mean spanwise flow over the deep waves. The turbulent flow in channels with at walls, swept wavy walls and spatial Stokes spanwise velocity forcing was simulated at a friction Reynolds number of two hundred. The time-averaged and dynamic turbulent flow characteristics of the three channel types are compared. The drag obtained for the channel with shallow waves is slightly larger than for the at channel, within the range of the experiments. In the case of the large waves, the simulation over predicts the drag. The shortcomings of the Stokes layer analogy model for the estimation of the spanwise shear stress and drag are discussed.

Denison, M.↗

Mathematical Investigation of Gamma Ray and Neutron Absorption Grid Patterns for Homeland Defense Related Fourier Imaging Systems

Terrorist suitcase nuclear devices typically using converted Soviet tactical nuclear warheads contain several kilograms of plutonium. This quantity of plutonium emits a significant number of gamma rays and neutrons as it undergoes radioactive decay. These gamma rays and neutrons normally penetrate ordinary matter to a significant distance. Unfortunately this penetrating quality of the radiation makes imaging with classical optics impractical. However, this radiation signature emitted by the nuclear source may be sufficient to be imaged from low-flying aerial platforms carrying Fourier imaging systems. The Fourier imaging system uses a pair of co-aligned absorption grids to measure a selected range of spatial frequencies from an object. These grids typically measure the spatial frequency in only one direction at a time. A grid pair that looks in all directions simultaneously would be an improvement over existing technology. A number of grid pairs governed by various parameters were investigated to solve this problem. By examining numerous configurations, it became apparent that an appropriate spiral pattern could be made to work. A set of equations was found to describe a grid pattern that produces straight fringes. Straight fringes represent a Fourier transform of a point source at infinity. An inverse Fourier transform of this fringe pattern would provide an accurate image (location and intensity) of a point source.

Boccio, Dona↗

Machine Learning Pattern Recognition Algorithm With Applications to Coherent Laser Combination

Herein we analyze a new kind of machine learning algorithm designed to feedback stabilize coherently combined lasers. This algorithm learns differential, rather than absolute, values of action in phase space, in order to facilitate learning on initially unstable systems. Experiments have shown that this approach can control small-scale spatial beam combination with high stability. In this paper we analyze the algorithm's performance and limitations in depth, showing that it can continuously learn during operation in order to track changes. Using simulation, we extend the application to temporal combination, and show that it scales to more complex instances by combining 81 beams.

97 MATHEMATICS AND COMPUTING↗

Free-electron crystals for enhanced X-ray radiation

Abstract Bremsstrahlung—the spontaneous emission of broadband radiation from free electrons that are deflected by atomic nuclei—contributes to the majority of X-rays emitted from X-ray tubes and used in applications ranging from medical imaging to semiconductor chip inspection. Here, we show that the bremsstrahlung intensity can be enhanced significantly—by more than three orders of magnitude—through shaping the electron wavefunction to periodically overlap with atoms in crystalline materials. Furthermore, we show how to shape the bremsstrahlung X-ray emission pattern into arbitrary angular emission profiles for purposes such as unidirectionality and multi-directionality. Importantly, we find that these enhancements and shaped emission profiles cannot be attributed solely to the spatial overlap between the electron probability distribution and the atomic centers, as predicted by the paraxial and non-recoil theory for free electron light emission. Our work highlights an unprecedented regime of free electron light emission where electron waveshaping provides multi-dimensional control over practical radiation processes like bremsstrahlung. Our results pave the way towards greater versatility in table-top X-ray sources and improved fundamental understanding of quantum electron-light interactions.

47 OTHER INSTRUMENTATION↗

Diversity of visual inputs to Kenyon cells of the Drosophila mushroom body

The arthropod mushroom body is well-studied as an expansion layer representing olfactory stimuli and linking them to contingent events. However, 8% of mushroom body Kenyon cells in Drosophila melanogaster receive predominantly visual input, and their function remains unclear. Here, we identify inputs to visual Kenyon cells using the FlyWire adult whole-brain connectome. Input repertoires are similar across hemispheres and connectomes with certain inputs highly overrepresented. Many visual neurons presynaptic to Kenyon cells have large receptive fields, while interneuron inputs receive spatially restricted signals that may be tuned to specific visual features. Individual visual Kenyon cells randomly sample sparse inputs from combinations of visual channels, including multiple optic lobe neuropils. These connectivity patterns suggest that visual coding in the mushroom body, like olfactory coding, is sparse, distributed, and combinatorial. However, the specific input repertoire to the smaller population of visual Kenyon cells suggests a constrained encoding of visual stimuli.

59 BASIC BIOLOGICAL SCIENCES↗

An advanced workflow for single-particle imaging with the limited data at an X-ray free-electron laser

An improved analysis for single-particle imaging (SPI) experiments, using the limited data, is presented here. Results are based on a study of bacteriophage PR772 performed at the Atomic, Molecular and Optical Science instrument at the Linac Coherent Light Source as part of the SPI initiative. Existing methods were modified to cope with the shortcomings of the experimental data: inaccessibility of information from half of the detector and a small fraction of single hits. The general SPI analysis workflow was upgraded with the expectation-maximization based classification of diffraction patterns and mode decomposition on the final virus-structure determination step. The presented processing pipeline allowed us to determine the 3D structure of bacteriophage PR772 without symmetry constraints with a spatial resolution of 6.9 nm. The obtained resolution was limited by the scattering intensity during the experiment and the relatively small number of single hits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Addressing APC Data Sparsity in Predicting Occupancy and Delay of Transit Buses: A Multitask Learning Approach

Public transit is a vital mode of transportation in urban areas, and its efficiency is crucial for the daily commute of millions of people. To improve the reliability and predictability of transit systems, researchers have developed separate single-task learning models to predict the occupancy and delay of buses at the stop or route level. However, these models provide a narrow view of delay and occupancy at each stop and do not account for the correlation between the two. We propose a novel approach that leverages broader generalizable patterns governing delay and occupancy for improved prediction. We introduce a multitask learning toolchain that takes into account General Transit Feed Specification feeds, Automatic Passenger Counter data, and contextual temporal and spatial information. The toolchain predicts transit delay and occupancy at the stop level, improving the accuracy of the predictions of these two features of a trip given sparse and noisy data. We also show that our toolchain can adapt to fewer samples of new transit data once it has been trained on previous routes/trips as compared to state-of-the-art methods. Finally, we use actual data from Chattanooga, Tennessee, to validate our approach. We compare our approach against the state-of-the-art methods and we show that treating occupancy and delay as related problems improves the accuracy of the predictions. We show that our approach improves delay prediction significantly by as much as 4% in F1 scores while producing equivalent or better results for occupancy.

Zulqarnain, Ammar Bin↗

Techniques for generation of control and guidance signals derived from optical fields, part 2

The development is reported of a high resolution technique for the detection and identification of landmarks from spacecraft optical fields. By making use of nonlinear regression analysis, a method is presented whereby a sequence of synthetic images produced by a digital computer can be automatically adjusted to provide a least squares approximation to a real image. The convergence of the method is demonstrated by means of a computer simulation for both elliptical and rectangular patterns. Statistical simulation studies with elliptical and rectangular patterns show that the computational techniques developed are able to at least match human pattern recognition capabilities, even in the presence of large amounts of noise. Unlike most pattern recognition techniques, this ability is unaffected by arbitrary pattern rotation, translation, and scale change. Further development of the basic approach may eventually allow a spacecraft or robot vehicle to be provided with an ability to very accurately determine its spatial relationship to arbitrary known objects within its optical field of view.

Hemami, H.↗

Simulation of ocean SAR images via phase history generation

A method for simulating an ocean synthetic-aperture radar (SAR) image is illustrated for a simple internal wave current pattern. The method calculates both the amplitude image and the radar signal history. The simulation model used consists of six stages. In the first stage, the full wave spectrum in two spatial coordinates is calculated from the wind speed and direction using the action spectral density equation. In the second stage, the pixel size is selected and used as the basis for dividing the spectrum into large and small scale motions. Realizations for the large-scale ocean surface height and velocity are then calculated. In the third stage, the sensor wavelength and geometry are used to calculate the small scale statistics (radar cross section, coherence time, root-mean square (RMS), radial velocity and RMS slope). In the fourth stage, an autoregressive method is used to generate a realization of the surface reflectivity history that is consistent with the radial velocity and the radial velocity variance. In the fifth stage, the signal history is generated by summing the reflectivities at the proper times with the appropriate antenna weighting function for the SAR. As a consequence of this process, speckle is automatically included in the signal. In the final stage, the SAR image can be created by using any of the traditional ways to process the signal history, including variable focusing and multilook processing.

Bennett, John R.↗

Flat field response of the microchannel plate detectors used on the Extreme Ultraviolet Explorer

The results of the extreme ultraviolet (EUV) flat field calibrations of two of the flight detectors to be flown on the Extreme Ultraviolet Explorer Satellite (EUVE) are presented. Images of about 40 million detected events binned 512 by 512 are sufficient to show microchannel plate fixed pattern noise such as hexagonal microchannel multifiber bundle interfaces, 'dead' spots, edge distortion, and differential nonlinearity. Differences due to photocathode material and dependencies on EUV wavelength are also described. Over large spatial scales, the detector response is flat to better than 10 percent of the mean response, but, at spatial scales less than 1 mm, the variations from the mean can be as large as 20 percent.

Vallerga, J. V.↗

Intercomparison of hydrologic processes in global climate models

In this report, we address the intercomparison of precipitation (P), evaporation (E), and surface hydrologic forcing (P-E) for 23 Atmospheric Model Intercomparison Project (AMIP) general circulation models (GCM's) including relevant observations, over a variety of spatial and temporal scales. The intercomparison includes global and hemispheric means, latitudinal profiles, selected area means for the tropics and extratropics, ocean and land, respectively. In addition, we have computed anomaly pattern correlations among models and observations for different seasons, harmonic analysis for annual and semiannual cycles, and rain-rate frequency distribution. We also compare the joint influence of temperature and precipitation on local climate using the Koeppen climate classification scheme.

Lau, W. K.-M.↗

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