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At least 937 records · Page 52

Microscopic-macroscopic level densities for low excitation energies

Level density ρ(E,Q) is derived within the micro-macroscopic approximation (MMA) for a system of strongly interacting Fermi particles with the energy E and additional integrals of motion Q , in line with several topics of the universal and fruitful activity of A. S. Davydov. Within the extended Thomas Fermi and semiclassical periodic orbit theory beyond the Fermi-gas saddle-point method, we obtain ρ ∝ I ν (S)/S ν , where I ν (S) is the modified Bessel function of the entropy S . For small shell-structure contribution, one finds ν = κ/2 + 1, where κ is the number of additional integrals of motion. This integer number is a dimension of Q, Q = { N, Z , …} for the case of two-component atomic nuclei, where N and Z are the numbers of neutrons and protons, respectively. For much larger shell structure contributions, one obtains ν = κ /2 + 2. The MMA level density ρ reaches the well-known Fermi gas asymptote for large excitation energies and the finite micro-canonical combinatoric limit for low excitation energies. Further, the additional integrals of motion can also be the projection of the angular momentum of a nuclear system for nuclear rotations of deformed nuclei, number of excitons for collective dynamics, and so on. Fitting the MMA total level density ρ( E , Q) for a set of the integrals of motion Q = { N, Z }, to experimental data on a long nuclear isotope chain for low excitation energies, one obtains the results for the inverse level-density parameter K , which differs significantly from those of neutron resonances due to shell, isotopic asymmetry, and pairing effects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Bonding of NO2, NH3, and CH2NY to Models of a (10,0) Carbon Nanotube

We have studied the bonding of NO2, NH3, and CH2NH to a (10,O) carbon nanotube using the MP2 and ONIOM methods with extended basis sets. We find bond strengths of 3.5, 3.6. and 6.3 kcal/mol for NO2, NH3, and CH2NH, respectively, using the ONIOM method with the high accuracy part treated at the MP2/aug-CC-pVTZ level and the remainder of the CNT approximated at the UFF level and including an estimate of basis set superposition error using the counterpoise method.

Walch, Stephen P.↗

The retinoic acid signaling pathway regulates anterior/posterior patterning in the nerve cord and pharynx of amphioxus, a chordate lacking neural crest

Amphioxus, the closest living invertebrate relative of the vertebrates, has a notochord, segmental axial musculature, pharyngeal gill slits and dorsal hollow nerve cord, but lacks neural crest. In amphioxus, as in vertebrates, exogenous retinoic acid (RA) posteriorizes the embryo. The mouth and gill slits never form, AmphiPax1, which is normally downregulated where gill slits form, remains upregulated and AmphiHox1 expression shifts anteriorly in the nerve cord. To dissect the role of RA signaling in patterning chordate embryos, we have cloned the single retinoic acid receptor (AmphiRAR), retinoid X receptor (AmphiRXR) and an orphan receptor (AmphiTR2/4) from amphioxus. AmphiTR2/4 inhibits AmphiRAR-AmphiRXR-mediated transactivation in the presence of RA by competing for DR5 or IR7 retinoic acid response elements (RAREs). The 5' untranslated region of AmphiTR2/4 contains an IR7 element, suggesting possible auto- and RA-regulation. The patterns of AmphiTR2/4 and AmphiRAR expression during embryogenesis are largely complementary: AmphiTR2/4 is strongly expressed in the cerebral vesicle (homologous to the diencephalon plus anterior midbrain), while AmphiRAR expression is high in the equivalent of the hindbrain and spinal cord. Similarly, while AmphiTR2/4 is expressed most strongly in the anterior and posterior thirds of the endoderm, the highest AmphiRAR expression is in the middle third. Expression of AmphiRAR is upregulated by exogenous RA and completely downregulated by the RA antagonist BMS009. Moreover, BMS009 expands the pharynx posteriorly; the first three gill slit primordia are elongated and shifted posteriorly, but do not penetrate, and additional, non-penetrating gill slit primordia are induced. Thus, in an organism without neural crest, initiation and penetration of gill slits appear to be separate events mediated by distinct levels of RA signaling in the pharyngeal endoderm. Although these compounds have little effect on levels of AmphiTR2/4 expression, RA shifts pharyngeal expression of AmphiTR2/4 anteriorly, while BMS009 extends it posteriorly. Collectively, our results suggest a model for anteroposterior patterning of the amphioxus nerve cord and pharynx, which is probably applicable to vertebrates as well, in which a low anterior level of AmphiRAR (caused, at least in part, by competitive inhibition by AmphiTR2/4) is necessary for patterning the forebrain and formation of gill slits, the posterior extent of both being set by a sharp increase in the level of AmphiRAR. Supplemental data available on-line.

NASA Discipline Evolutionary Biology↗

Simultaneous global and local clustering in multiplex networks with covariate information

Understanding both global and layer-specific group structures is useful for uncovering complex patterns in networks with multiple interaction types. In this work, we introduce a new model, the hierarchical multiplex stochastic blockmodel, which simultaneously detects communities within individual layers of a multiplex network while inferring a global node clustering across the layers. A stochastic blockmodel is assumed in each layer, with probabilities of layer-level group memberships determined by a node’s global group assignment. Our model uses a Bayesian framework, employing a probit stick-breaking process to construct node-specific mixing proportions over a set of shared Griffiths–Engen–McCloseky distributions. These proportions determine layer-level community assignment, allowing for an unknown and varying number of groups across layers, while incorporating nodal covariate information to inform the global clustering. We propose a scalable variational inference procedure with parallelisable updates for application to large networks. Extensive simulation studies demonstrate our model’s ability to accurately recover both global and layer-level clusters in complicated settings, and applications to real data showcase the model’s effectiveness in uncovering interesting latent network structure.

community detection↗

A Demonstration of a Retrofit Architecture for Intelligent Control and Diagnostics of a Turbofan Engine

A retrofit architecture for intelligent turbofan engine control and diagnostics that changes the fan speed command to maintain thrust is proposed and its demonstration in a piloted flight simulator is described. The objective of the implementation is to increase the level of autonomy of the propulsion system, thereby reducing pilot workload in the presence of anomalies and engine degradation due to wear. The main functions of the architecture are to diagnose the cause of changes in the engine s operation, warning the pilot if necessary, and to adjust the outer loop control reference signal in response to the changes. This requires that the retrofit control architecture contain the capability to determine the changed relationship between fan speed and thrust, and the intelligence to recognize the cause of the change in order to correct it or warn the pilot. The proposed retrofit architecture is able to determine the fan speed setting through recognition of the degradation level of the engine, and it is able to identify specific faults and warn the pilot. In the flight simulator it was demonstrated that when degradation is introduced into an engine with standard fan speed control, the pilot needs to take corrective action to maintain heading. Utilizing the intelligent retrofit control architecture, the engine thrust is automatically adjusted to its expected value, eliminating yaw without pilot intervention.

Litt, Jonathan S.↗

Psychoacoustic Test to Determine Sound Quality Metric Indicators of Rotorcraft Noise Annoyance

Noise certification metrics such as Effective Perceived Noise Level and Sound Exposure Level are used to ensure that helicopters meet regulations, but these metrics may not be good indicators of annoyance since noise complaints against helicopters persist. Sound quality (SQ) metrics, specifically fluctuation strength, tonality, impulsiveness, roughness, and sharpness, are explored to determine their relationship with annoyance. A psychoacoustic test was conducted at the NASA Langley Research Center Exterior Effects Room to assess annoyance to helicopter-like sounds over a range of SQ metric values. The amplitude, phase, and frequency of the AS350 helicopter main and tail rotor blade passage signal harmonics were manipulated to produce 105 unique helicopter-like sounds with prescribed values of SQ metrics. All sounds were set to roughly the same loudness level. These sounds were played to 40 subjects who rated each sound for annoyance. Analyses given in this paper point to which SQ metrics are important to the helicopter noise annoyance response.

Krishnamurthy, Siddhartha↗

A report on the USL NASA/RECON project. Part 1: The development of a transportable, university level, IS and R educational program

A project is described which has as its goal the production of a set of system-independent, discipline-independent, transportable college level courses to educate science and engineering students in the use of large-scale information storage and retrieval systems. This project is being conducted with the cooperation and sponsorship of NASA by R and D teams at the University of Southwest Louisiana and Southern University. Chapter 1 is an introduction, providing an overview and a listing of the management phases. Chapter 2 furnishes general information regarding accomplishments in areas under development. Chapter 3 deals with the development of the course materials by presenting a series of diagrams and keys to depict the progress and interrelationships of various tasks and sub-tasks. Chapter 4 presents plans for activities to be conducted to complete and deliver course materials. The final chapter is a summary of project objectives, methods, plans, and accomplishments.

Dominick, Wayne D.↗

Smoky Mountain Data Challenge 2020: An Open Call to Solve Data Problems in the Areas of Neutron Science, Material Science, Urban Modeling and Dynamics, Geophysics, and Biomedical Informatics

The 2020 Smoky Mountains Computational Sciences and Engineering Conference enlists research scientists from across Oak Ridge National Laboratory (ORNL) to be data sponsors and help create data analytics challenges for eminent data sets at the laboratory. This work describes the significance of each of the seven data sets and their as- sociated challenge questions. The challenge questions for each data set were required to cover multiple difficulty levels. An international call for participation was sent to students, and researchers asking them to form teams of up to four people to apply novel data analytics techniques to these data sets.

Parete-Koon, Suzanne↗

Graphics Processing Unit Assisted Thermographic Compositing

Objective: To develop a software application utilizing general purpose graphics processing units (GPUs) for the analysis of large sets of thermographic data. Background: Over the past few years, an increasing effort among scientists and engineers to utilize the GPU in a more general purpose fashion is allowing for supercomputer level results at individual workstations. As data sets grow, the methods to work them grow at an equal, and often great, pace. Certain common computations can take advantage of the massively parallel and optimized hardware constructs of the GPU to allow for throughput that was previously reserved for compute clusters. These common computations have high degrees of data parallelism, that is, they are the same computation applied to a large set of data where the result does not depend on other data elements. Signal (image) processing is one area were GPUs are being used to greatly increase the performance of certain algorithms and analysis techniques. Technical Methodology/Approach: Apply massively parallel algorithms and data structures to the specific analysis requirements presented when working with thermographic data sets.

Ragasa, Scott↗

Graphics Processing Unit Assisted Thermographic Compositing

Objective: To develop a software application utilizing general purpose graphics processing units (GPUs) for the analysis of large sets of thermographic data. Background: Over the past few years, an increasing effort among scientists and engineers to utilize the GPU in a more general purpose fashion is allowing for supercomputer level results at individual workstations. As data sets grow, the methods to work them grow at an equal, and often greater, pace. Certain common computations can take advantage of the massively parallel and optimized hardware constructs of the GPU to allow for throughput that was previously reserved for compute clusters. These common computations have high degrees of data parallelism, that is, they are the same computation applied to a large set of data where the result does not depend on other data elements. Signal (image) processing is one area were GPUs are being used to greatly increase the performance of certain algorithms and analysis techniques.

Ragasa, Scott↗

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

54 ENVIRONMENTAL SCIENCES↗

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

Laura Duncanson↗

Large-scale variations in observed Antarctic Sea ice extent and associated atmospheric circulation

The 1974 Antarctic large scale sea ice extent is studied from data from Nimbus 2 and 5 and temperature and sea level pressure fields from the Australian Meteorological Data Set. Electrically Scanning Microwave Radiometer data were three-day averaged and compared with 1000 mbar atmospheric pressure and sea level pressure data, also in three-day averages. Each three-day period was subjected to a Fourier analysis and included the mean latitude of the ice extent and the phases and percent variances in terms of the first six Fourier harmonics. Centers of low pressure were found to be generally east of regions which displayed rapid ice growth, and winds acted to extend the ice equatorward. An atmospheric response was also noted as caused by the changing ice cover.

Cavalieri, D. J.↗

Translating Vision into Design: A Method for Conceptual Design Development

One of the most challenging tasks for engineers is the definition of design solutions that will satisfy high-level strategic visions and objectives. Even more challenging is the need to demonstrate how a particular design solution supports the high-level vision. This paper describes a process and set of system engineering tools that have been used at the Johnson Space Center to analyze and decompose high-level objectives for future human missions into design requirements that can be used to develop alternative concepts for vehicles, habitats, and other systems. Analysis and design studies of alternative concepts and approaches are used to develop recommendations for strategic investments in research and technology that support the NASA Integrated Space Plan. In addition to a description of system engineering tools, this paper includes a discussion of collaborative design practices for human exploration mission architecture studies used at the Johnson Space Center.

Carpenter, Joyce E.↗

Single-Point Extrapolation to the Complete Basis Set Limit through Deep Learning

Machine learning (ML) offers an attractive method for making predictions about molecular systems while circumventing the need to run expensive electronic structure calculations. Once trained on ab initio data, the promise of ML is to deliver accurate predictions of molecular properties that were previously computationally infeasible. In this work, we develop and train a graph neural network model to correct the basis set incompleteness error (BSIE) between a small and large basis set at the RHF and B3LYP levels of theory. Our results show that, when compared to fitting to the total potential, an ML model fitted to correct the BSIE is better at generalizing to systems not seen during training. We test this ability by training on single molecules while evaluating on molecular complexes. We also show that ensemble models yield better behaved potentials in situations where the training data is insufficient. However, even when only fitting to the BSIE, acceptable performance is only achieved when the training data sufficiently resemble the systems one wants to make predictions on. As a result, the test error of the final model trained to predict the difference between the cc-pVDZ and cc-pV5Z potential is 0.184 kcal/mol for the B3LYP density functional, and the ensemble model accurately reproduces the large basis set interaction energy curves on the S66x8 dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Galvanic Vestibular Reduction Modifies Perception of Coriolis Cross-Coupling and Delays Motion Sickness Onset

INTRODUCTION: Alterations in vestibular sensory processing following G-transitions lead to head movement sensitivity and motion sickness upon return to Earth’s gravity. The purpose of this study was to evaluate whether a non-pharmaceutical tool using galvanic vestibular reduction (GVR) could suppress disorienting illusions and mitigate motion sickness. A similar approach using anodal (inhibitory) currents delivered to both ears has been shown to result in a selective reversible ablation of irregular vestibular afferents [1]. METHODS: Using a repeated measures counter-balanced design, motion sickness and perception were obtained in 26 subjects during Coriolis cross-coupling stimuli on a rotating chair across three GVR treatment interventions: throughout stimulus testing (prevention), following symptom onset (rescue), and placebo control. The GVR peak current was maintained at 2.5 mA across subjects and across prevention / rescue sessions. Subjects performed up to 10 sets of pitch head movements during constant rotation. For each set, head movement was cued every 10 seconds, alternating between pitch forward (chin resting to chest) and pitch backward (head upright) for a total of 7 forward and backward movements. During each head movement, subjects were asked to use a joystick to record the magnitude of their perceived rotation along three axes. During the 2-minute pause between sets, motion sickness symptom scoring was obtained using the Pensacola Diagnostic Index and subject discomfort (0-20) ratings. Performance on a sensorimotor and cognitive test battery was measured during a fourth session to map changes in GVR level with functional performance. RESULTS: Fourteen of the 26 subjects were not susceptible to the motion stressor (i.e., did not reach an endpoint in the control condition). While the time to endpoint, or number of head movements, did not significantly vary across the three GVR conditions in the remaining subjects, the symptom levels were significantly lower through the third set of head movements when GVR was on throughout the testing. Initiating GVR following symptom onset did not appear to alter the symptom progression nor time to motion sickness endpoint. Based on the joystick measures, GVR significantly modified the perceived roll and pitch sensation during head movements, reducing the amplitude of tilt in most subjects. It is important to note that comparable levels of GVR did not impair performance on a functional test battery including mobility, balance and cognitive tasks. DISCUSSION: Our findings suggest GVR may be useful in reducing disorienting roll and pitch illusions and delaying the onset of motion sickness. Further enhancements will be required to individualize the stimulation amplitude and optimize the waveform delivery. Adapting this non-pharmaceutical countermeasure approach to allow self-administered titration of current amplitude during recovery would enable transfer to post-flight treatment of motion sickness. [1] Minor L. B. and Goldberg J. M. (1991) J Neurosci 11, 1636-48. 109, 889-894.

G N Pradhan↗

WeakIdent: Weak formulation for identifying differential equation using narrow-fit and trimming

Data-driven identification of differential equations is an interesting but challenging problem, especially when the given data are corrupted by noise. When the governing differential equation is a linear combination of various differential terms, the identification problem can be formulated as solving a linear system, with the feature matrix consisting of linear and nonlinear terms multiplied by a coefficient vector. This product is equal to the time derivative term, and thus generates dynamical behaviors. The goal is to identify the correct terms that form the equation to capture the dynamics of the given data. We propose a general and robust framework to recover differential equations using a weak formulation with two new mechanisms, narrow-fit and trimming, for both ordinary and partial differential equations (ODEs and PDEs). The weak formulation facilitates an efficient and robust way to handle noise, and two new mechanisms, narrow-fit and trimming, improve the coefficient support and value recoveries respectively. For each sparsity level, Subspace Pursuit is utilized to find an initial set of support from the large dictionary. Then, we focus on highly dynamic regions (rows of the feature matrix), and error normalize the feature matrix in the narrow-fit step. The support is further updated via trimming the terms that contribute the least. Finally, the support set of features with the smallest Cross-Validation error is chosen as the result. A comprehensive set of numerical experiments are presented for both systems of ODEs and PDEs with various noise levels. The proposed method gives a robust recovery of the coefficients, and a significant denoising effect which can handle up to 100% noise-to-signal ratio for some equations. We compare the proposed method with several state-of-the-art algorithms for the recovery of differential equations.

97 MATHEMATICS AND COMPUTING↗

Neocytolysis on descent from altitude: a newly recognized mechanism for the control of red cell mass

BACKGROUND: Studies of space-flight anemia have uncovered a physiologic process, neocytolysis, by which young red blood cells are selectively hemolyzed, allowing rapid adaptation when red cell mass is excessive for a new environment. OBJECTIVES: 1) To confirm that neocytolysis occurs in another situation of acute plethora-when high-altitude dwellers with polycythemia descend to sea level; and 2) to clarify the role of erythropoietin suppression. DESIGN: Prospective observational and interventional study. SETTING: Cerro de Pasco (4380 m) and Lima (sea level), Peru. PARTICIPANTS: Nine volunteers with polycythemia. INTERVENTIONS: Volunteers were transported to sea level; three received low-dose erythropoietin. MEASUREMENTS: Changes in red cell mass, hematocrit, hemoglobin concentration, reticulocyte count, ferritin level, serum erythropoietin, and enrichment of administered(13)C in heme. RESULTS: In six participants, red cell mass decreased by 7% to 10% within a few days of descent; this decrease was mirrored by a rapid increase in serum ferritin level. Reticulocyte production did not decrease, a finding that establishes a hemolytic mechanism.(13)C changes in circulating heme were consistent with hemolysis of young cells. Erythropoietin was suppressed, and administration of exogenous erythropoietin prevented the changes in red cell mass, serum ferritin level, and(13)C-heme. CONCLUSIONS: Neocytolysis and the role of erythropoietin are confirmed in persons with polycythemia who descend from high altitude. This may have implications that extend beyond space and altitude medicine to renal disease and other situations of erythropoietin suppression, hemolysis, and polycythemia.

Non-NASA Center↗