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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Changes in gravity inhibit lymphocyte locomotion through type I collagen

Immunity relies on the circulation of lymphocytes through many different tissues including blood vessels, lymphatic channels, and lymphoid organs. The ability of lymphocytes to traverse the interstitium in both nonlymphoid and lymphoid tissues can be determined in vitro by assaying their capacity to locomote through Type I collagen. In an attempt to characterize potential causes of microgravity-induced immunosuppression, we investigated the effects of simulated microgravity on human lymphocyte function in vitro using a specialized rotating-wall vessel culture system developed at the Johnson Space Center. This very low shear culture system randomizes gravitational vectors and provides an in vitro approximation of microgravity. In the randomized gravity of the rotating-wall vessel culture system, peripheral blood lymphocytes did not locomote through Type I collagen, whereas static cultures supported normal movement. Although cells remained viable during the entire culture period, peripheral blood lymphocytes transferred to unit gravity (static culture) after 6 h in the rotating-wall vessel culture system were slow to recover and locomote into collagen matrix. After 72 h in the rotating-wall vessel culture system and an additional 72 h in static culture, peripheral blood lymphocytes did not recover their ability to locomote. Loss of locomotory activity in rotating-wall vessel cultures appears to be related to changes in the activation state of the lymphocytes and the expression of adhesion molecules. Culture in the rotating-wall vessel system blunted the ability of peripheral blood lymphocytes to respond to polyclonal activation with phytohemagglutinin. Locomotory response remained intact when peripheral blood lymphocytes were activated by anti-CD3 antibody and interleukin-2 prior to introduction into the rotating-wall vessel culture system. Thus, in addition to the systemic stress factors that may affect immunity, isolated lymphocytes respond to gravitational changes by ceasing locomotion through model interstitium. These in vitro investigations suggest that microgravity induces non-stress-related changes in cell function that may be critical to immunity. Preliminary analysis of locomotion in true microgravity revealed a substantial inhibition of cellular movement in Type I collagen. Thus, the rotating-wall vessel culture system provides a model for analyzing the microgravity-induced inhibition of lymphocyte locomotion and the investigation of the mechanisms related to lymphocyte movement.

Weightlessness↗
NASA NTRS2020

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-ofthe-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Hesham ElAbd↗
NASA NTRS2020

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Deep-learning↗
NASA NTRS1982

Thunderstorm electric field modelling

Calculation of eletric field vectors within and near an isolated thundercloud (which has a given volume charge distribution) is envisaged. The maximum field strength within the thundercloud is calculated. The effects of screening layers, both above and below the thundercloud may be investigated, as well time-dependent potential problem. The study can lead to a better understanding of the charge distributions in a thundercloud, which in turn may shed some light on the actual mechanism of charging of a thundercloud.

Tan, A.↗
NASA NTRS1985

Far-infrared observations of the exciting stars of Herbig-Haro objects. III - Circumstellar disks

Far-infrared observations of the exciting stars of Herbig-Haro objects are presented that (1) show these stars to be of low luminosity; (2) indicate that it is not usual for these objects themselves to be visible at far-infrared wavelengths; and (3) demonstrate the existence of spatially resolved, physically large, potentially disklike structures. These latter structures are resolved perpendicular to the directions of flow from the stars, but not parallel to the flows. In addition to these general properties, two new HH-exciting stars were discovered by searching along the extrapolated proper motion vectors for these HHs; and the jetlike object 'DG Tau B' was also detected.

Cohen, M.↗
NASA NTRS1989

Enhancements to the IBM version of COSMIC/NASTRAN

Major improvements were made to the IBM version of COSMIC/NASTRAN by RPK Corporation under contract to IBM Corporation. These improvements will become part of COSMIC's IBM version and will be available in the second quarter of 1989. The first improvement is the inclusion of code to take advantage of IBM's new Vector Facility (VF) on its 3090 machines. The remaining improvements are modifications that will benefit all users as a result of the extended addressing capability provided by the MVS/XA operating system. These improvements include the availability of an in-memory data base that potentially eliminates the need for I/O to the PRIxx disk files. Another improvement is the elimination of multiple load modules that have to be loaded for every link switch within NASTRAN. The last improvement allows for NASTRAN to execute above the 16 mega-byte line. This improvement allows for NASTRAN to have access to 2 giga-bytes of memory for open core and the in-memory data base.

Brown, W. Keith↗
NASA NTRS1989

Modelling Rift Valley fever (RVF) disease vector habitats using active and passive remote sensing systems

The NASA Ames Ecosystem Science and Technology Branch and the U.S. Army Medical Research Institute of Infectious Diseases are conducting research to detect Rift Valley fever (RVF) vector habitats in eastern Africa using active and passive remote-sensing. The normalized difference vegetation index (NDVI) calculated from Landsat TM and SPOT data is used to characterize the vegetation common to the Aedes mosquito. Relationships have been found between the highest NDVI and the 'dambo' habitat areas near Riuru, Kenya on both wet and dry data. High NDVI values, when combined with the vegetation classifications, are clearly related to the areas of vector habitats. SAR data have been proposed for use during the rainy season when optical systems are of minimal use and the short frequency and duration of the optimum RVF mosquito habitat conditions necessitate rapid evaluation of the vegetation/moisture conditions; only then can disease potential be stemmed and eradication efforts initiated.

Ambrosia, Vincent G.↗
NASA NTRS1993

Development of iterative techniques for the solution of unsteady compressible viscous flows

During the past two decades, there has been significant progress in the field of numerical simulation of unsteady compressible viscous flows. At present, a variety of solution techniques exist such as the transonic small disturbance analyses (TSD), transonic full potential equation-based methods, unsteady Euler solvers, and unsteady Navier-Stokes solvers. These advances have been made possible by developments in three areas: (1) improved numerical algorithms; (2) automation of body-fitted grid generation schemes; and (3) advanced computer architectures with vector processing and massively parallel processing features. In this work, the GMRES scheme has been considered as a candidate for acceleration of a Newton iteration time marching scheme for unsteady 2-D and 3-D compressible viscous flow calculation; from preliminary calculations, this will provide up to a 65 percent reduction in the computer time requirements over the existing class of explicit and implicit time marching schemes. The proposed method has ben tested on structured grids, but is flexible enough for extension to unstructured grids. The described scheme has been tested only on the current generation of vector processor architecture of the Cray Y/MP class, but should be suitable for adaptation to massively parallel machines.

Hixon, Duane↗
NASA NTRS2003

Development of an Efficient Binaural Simulation for the Analysis of Structural Acoustic Data

Applying binaural simulation techniques to structural acoustic data can be very computationally intensive as the number of discrete noise sources can be very large. Typically, Head Related Transfer Functions (HRTFs) are used to individually filter the signals from each of the sources in the acoustic field. Therefore, creating a binaural simulation implies the use of potentially hundreds of real time filters. This paper details two methods of reducing the number of real-time computations required by: (i) using the singular value decomposition (SVD) to reduce the complexity of the HRTFs by breaking them into dominant singular values and vectors and (ii) by using equivalent source reduction (ESR) to reduce the number of sources to be analyzed in real-time by replacing sources on the scale of a structural wavelength with sources on the scale of an acoustic wavelength. The ESR and SVD reduction methods can be combined to provide an estimated computation time reduction of 99.4% for the structural acoustic data tested. In addition, preliminary tests have shown that there is a 97% correlation between the results of the combined reduction methods and the results found with the current binaural simulation techniques

Johnson, Marty E.↗
NASA NTRSDate not supplied

Spacecraft Passive Safety Assessment Using Ellipse Constraints and Relative Orbital Elements

This paper presents necessary and sufficient conditions for validating spacecraft passive safety using relative orbital elements (ROE) centered around the far-field to near-field trajectory design of a hypothetical autonomous rendezvous and docking (AR&D) mission. The specific formulation of the ROEs used in this study are of quasi-nonsingular form based on elative eccentricity/inclination vectors. Current methodologies for ensuring passive safety apply keep-out volumes (KOV) to maintain appropriate separation between the Servicer and Client. Widely used techniques to assess the integrity of the KOV involve forward propagation of the relative Cartesian state to check for a potential KOV breach. In this study, an alternative approach to the propagation-based method is proposed using ROEs due to their valuable geometric insights of spacecraft relative motion. Modeling the relative trajectory and KOV ellipsoids as ellipses into the 2-D ROE sub-space simplifies the passive safety validation to a root-finding problem within the unit disk with high computational efficiency. Other approaches to intersection detection of the KOV are also evaluated in accuracy and run-time. Furthermore, a Monte Carlo simulation was employed to compare the ROE-based and relative Cartesian approaches in terms of maneuver error.

Bruce Barbour↗
NASA NTRSDate not supplied

Benefits of Ka-band GaN MMIC High Power Amplifiers With Wide Bandwidth and High Spectral/Power Added Efficiencies for Cognitive Radio Platforms

A cognitive radio on a future NASA near-Earth spacecraft will be capable of sensing its environment and dynamically adapting its operating parameters to provide the desired SATCOM service to the mission. A key component that can enable this type of operation is a high-power amplifier (HPA) that resides on the radio platform. In this paper, we present the RF performance characteristics of a Ka-band gallium nitride (GaN) monolithic microwave integrated circuit (MMIC) based HPA for cognitive radio platforms. These characteristics include the output power, gain, power added efficiency (PAE), RMS error vector magnitude (EVM), spectral efficiency, 3rd-order intermodulation distortion (IMD) products, spectrum, spectral regrowth, noise figure (NF), and phase noise. The data presented indicates that the HPA meets NTIA, military, and commercial spectral mask requirements. In addition, we discuss the benefits offered by the above performance characteristics toward the design and implementation of a cognitive radio platform. Furthermore, as examples, we discuss three potential use cases that apply artificial intelligence (AI) and machine learning (ML) techniques and exploit the performance characteristics discussed above to provide a knowledge-based cognitive radio platform design for SATCOM. Thus, cognitive radios with performance flexibility can enable roaming and provide seamless interoperability autonomously in the future between NASA, commercial, and other space networks owned by U.S. government agencies.

Gallium nitride↗
NASA NTRS2023

Benefits of Ka-band GaN MMIC High Power Amplifiers With Wide Bandwidth and High Spectral/Power Added Efficiencies for Cognitive Radio Platforms

A cognitive radio on a future NASA near-Earth spacecraft will be capable of sensing its environment and dynamically adapting its operating parameters to provide the desired SATCOM service to the mission. A key component that can enable this type of operation is a high-power amplifier (HPA) that resides on the radio platform. In this report, we present the RF performance characteristics of a Ka-band gallium nitride (GaN) monolithic microwave integrated circuit (MMIC) based HPA for cognitive radio platforms. These characteristics include the output power, gain, power added efficiency (PAE), RMS error vector magnitude (EVM), spectral efficiency, 3rdorder intermodulation distortion (IMD) products, spectrum, spectral regrowth, noise figure (NF), phase noise, and group delay. The data presented indicates that the HPA meets NTIA, military, and commercial spectral mask requirements. In addition, we discuss the benefits offered by the above performance characteristics toward the design and implementation of a cognitive radio platform. Furthermore, as examples, we discuss three potential use cases that apply artificial intelligence (AI) and machine learning (ML) techniques and exploit the performance characteristics discussed above to provide a knowledge-based cognitive radio platform design for SATCOM. Thus, cognitive radios with performance flexibility can enable roaming and provide seamless interoperability autonomously in the future between NASA, commercial, and other space networks owned by U.S. government agencies.

Gallium nitride↗
NASA NTRS1996

Mapping Pixel Windows To Vectors For Parallel Processing

Mapping performed by matrices of transistor switches. Arrays of transistor switches devised for use in forming simultaneous connections from square subarray (window) of n x n pixels within electronic imaging device containing np x np array of pixels to linear array of n(sup2) input terminals of electronic neural network or other parallel-processing circuit. Method helps to realize potential for rapidity in parallel processing for such applications as enhancement of images and recognition of patterns. In providing simultaneous connections, overcomes timing bottleneck or older multiplexing, serial-switching, and sample-and-hold methods.

Duong, Tuan A.↗
NASA NTRS1979

Effects of lift force on ejecta transport

The possible effects of lift on individual ejecta trajectories after an impact event are examined, considering a dimensionless transport parameter (K), the initial velocity vector of the particles, and the ratio of the lift to drag coefficients. If this ratio is not equal to zero, the trajectory is greatly influenced by the lift coefficient, particularly for large values of K and high launch angles. It is suggested that lift potentially can affect small ejecta in the size range also affected by aerodynamic drag, thereby adding complexity to atmospheric effects discussed by Schultz and Gault (1978).

Pai, S. I.↗
NASA NTRS1987

Thermodynamic budget diagrams for the hurricane subcloud layer

The idealized hurricane boundary layer budget from Malkus and Riehl (1960) are reexamined using vector diagrams for the thermodynamic budgets in the light of recent observational studies. A large air-sea temperature difference can only be maintained with both large fluxes through cloud-base level and a large evaporative cooling of the subcloud layer. The high equivalent potential temperature values observed in hurricane eyewalls can be reached if these cloud-base and evaporative fluxes are reduced and the subcloud layer moves toward the sea surface virtual potential temperature.

Betts, Alan K.↗
NASA NTRS2006

Computer Modeling of Thermal Convection in Melts to Explain Glass Formation in Low Gravity and on Earth

Experiments conducted up to this time on glass forming melts in the low gravity environment of space show that glasses prepared in low-g are more chemically homogeneous and more resistant to crystallization than the comparable glasses prepared at 1-g on Earth. This result is somewhat surprising and opposite to the accepted concept on glass formation for a melt. A hypothesis based on "shear thinning" of a melt, a decrease in viscosity with increasing shear stress, is proposed as an explanation for the observed low-gravity results. This paper describes detailed simulation procedures to test the role of thermal convection in introducing shear stress in glass forming melts, using a lithium disilcate melt as a model. The simulation system in its idealized version consists of a cylinder that is heated at one end and cooled at the other with gravity acting in a transverse direction to the thermal gradient. The side wall of the cylinder is assumed to be insulating. The governing equations of motion and energy are solved using variable properties for viscosity (Arrehenius and non-Arrehenius behaviors) and density (constant and temperature dependent). Other parametric variables in the calculations include gravity level and gravity vector orientation. The shear stress in the system are then computed as a function of gravity from the calculated values of maximum melt velocity, and its effect on melt viscosity (shear thinning) is predicted. Also included and discussed are the modeling efforts related to other potential convective processes in glass forming melts and their possible effects on melt viscosity.

Ray, Chandra S.↗
NASA NTRS2016

CubeSat Constellation Cloud Winds(C3Winds) A New Wind Observing System to Study Mesoscale Cloud Dynamics and Processes

The CubeSat Constellation Cloud Winds (C3Winds) is a NASA Earth Venture Instrument (EV-I) concept with the primary objective to better understand mesoscale dynamics and their structures in severe weather systems. With potential catastrophic damage and loss of life, strong extratropical and tropical cyclones (ETCs and TCs) have profound three-dimensional impacts on the atmospheric dynamic and thermodynamic structures, producing complex cloud precipitation patterns, strong low-level winds, extensive tropopause folds, and intense stratosphere-troposphere exchange. Employing a compact, stereo IR-visible imaging technique from two formation-flying CubeSats, C3Winds seeks to measure and map high-resolution (2 km) cloud motion vectors (CMVs) and cloud geometric height (CGH) accurately by tracking cloud features within 5-15 min. Complementary to lidar wind observations from space, the high-resolution wind fields from C3Winds will allow detailed investigations on strong low-level wind formation in an occluded ETC development, structural variations of TC inner-core rotation, and impacts of tropopause folding events on tropospheric ozone and air quality. Together with scatterometer ocean surface winds, C3Winds will provide a more comprehensive depiction of atmosphere-boundary-layer dynamics and interactive processes. Built upon mature imaging technologies and long history of stereoscopic remote sensing, C3Winds provides an innovative, cost-effective solution to global wind observations with potential of increased diurnal sampling via CubeSat constellation.

mesoscale dynamics↗
NASA NTRS1982

The airborne laser ranging system, its capabilities and applications

The airborne laser ranging system is a multibeam short pulse laser ranging system on board an aircraft. It simultaneously measures the distances between the aircraft and six laser retroreflectors (targets) deployed on the Earth's surface. The system can interrogate over 100 targets distributed over an area of 25,000 sq, kilometers in a matter of hours. Potentially, a total of 1.3 million individual range measurements can be made in a six hour flight. The precision of these range measurements is approximately + or - 1 cm. These measurements are used in procedure which is basically an extension of trilateration techniques to derive the intersite vector between the laser ground targets. By repeating the estimation of the intersite vector, strain and strain rate errors can be estimated. These quantities are essential for crustal dynamic studies which include determination and monitoring of regional strain in the vicinity of active fault zones, land subsidence, and edifice building preceding volcanic eruptions.

Kahn, W. D.↗