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The purpose of this document is to describe the Cassini/Huygens science data archive system which includes policy, roles and responsibilities, description of science and supplementary data products or data sets, metadata, documentation, software, and archive schedule and methods for archive transfer to the NASA Planetary Data System (PDS).
Understanding protein-protein interactions (PPIs) between viruses and host organisms is crucial for uncovering infection mechanisms and identifying potential therapeutic targets. The ability to generalize PPI predictive models across understudied viruses presents a significant challenge. In this work, we use arenavirus-human PPIs to illustrate the difficulties associated with model generalization, which are compounded by a lack of both positive and negative data. We employ a Transfer Learning approach to investigate arenavirus-human PPIs by utilizing models trained on better-studied virus-human and human-human PPIs. Additionally, we curate and assess four types of negative sampling datasets to evaluate their impact on model performance. Despite the overall high accuracies (93–99 %) and AUPRC scores (0.8–0.9) appearing promising, further analysis indicates that these performance metrics can be misleading due to data leakage, data bias, and overfitting, especially concerning under-represented viral proteins. We reveal these gaps and assess the impact of data imbalance using standard k-fold cross-validation and Independent Blind Testing with a Balanced Dataset, resulting in a drop in accuracy below 50 %. We propose a viral protein-specific evaluation framework that categorizes viral proteins into majority and minority classes based on their representation in the dataset, enabling comparison of model performance across these groups using balanced accuracies. This framework offers a more robust evaluation of model generalizability, addressing biases inherent in standard evaluation techniques and paving the way for more reliable PPI prediction models for understudied viruses.
Due to the sheer volume of data, leveraging satellite instrument observations effectively in a data assimilation context for numerical weather prediction or for remote sensing requires a radiative transfer model as an observation operator that is both fast and accurate at the same time. Physics-based line-by-line radiative transfer (RT) models fulfil the requirement for accuracy, but are too slow and too costly in computational terms for operational applications. Therefore, fast methods were developed to be able to perform fast RT calculations using techniques such as spectral sampling or pre-computed look-up tables. The operational fast models currently calculate the absorption and scattering coefficients from the pre-computed regression coefficients and atmospheric state and cloud profiles. As a novel solution to this problem, this work investigates a deep learning approach to replace the regression coefficients in the fast RT models. A selection of hidden-layer neural network configurations is trained against atmospheric transmittance profile data computed by an accurate line-by-line model and their performance is evaluated and their advantages and disadvantages are discussed.
The Joint Center for Satellite Data Assimilation (JCSDA) Community Radiative Transfer Model (CRTM) is a fast, 1-D radiative transfer model used in numerical weather prediction, calibration/validation, etc. across multiple federal agencies and universities. The key benefit of the CRTM is that it is a satellite simulator. It provides a highly accurate representation of satellite radiances by using the specific sensor response functions convolved with a line-by-line radiative transfer model (LBLRTM). CRTM covers the spectral ranges consistent with all present operational and most research satellites, from visible to microwave. The capability to simulate ultraviolet radiances and support space-based radar sensors is being added over the next two years in CRTM Version 3.0. In addition to simulated radiances, the CRTM also provides Jacobian outputs needed to interpret satellite observations for numerical weather prediction. The Jacobian estimates how changes in geophysical parameters affect simulated measurements from satellite sensors. Using the Jacobian in modeling and weather prediction improves the accuracy and efficiency of data analysis, leading to better weather predictions. The CRTM model's success and growth depend on community contributions and evaluation. To facilitate this, we have made the CRTM highly accessible through modular programming, clear documentation and tutorials, public domain licensing, unfettered public access via Github, and a clear path to operational implementation for innovative research. We encourage and welcome contributions from the community to help us continue to improve the CRTM.
The objective of this paper is to evaluate aerothermal flight measurements made on the Space Shuttle External Tank (ET) during its initial flights. The ETs have been adequately instrumented to measure various quantities during flight including heat transfer, pressure, and structural temperature. The flight data have been compared with mathematical models based on an extensive wind tunnel data base, realistic flowfields, and empirical heat-transfer relationships. An analysis of the results points out the validity of the current aeroheating methodology and existing data base, and identifies problem areas in the methodology as indicated by the flight data.
This paper systematically presents the results of heat transfer and friction factor data measured in five short rectangular channels with turbulence promoters. The project investigated the combined effects of the channel aspect ratio, rib angle-of-attack, and flow Reynolds number on heat transfer and pressure drop in rectangular channels with two opposite ribbed walls. The channel aspect ratio (width-to-height, W/H, ribs on side W) varied from 1/4 to 1/2, to 1, 2, and 4, while the corresponding rib angles-of-attack alpha were 90 deg, 60 deg, 45 deg, and 30 deg, respectively. The Reynolds number range was 10,000-60,000. The results suggest that the narrow aspect ratio channels (W/H less than 1) give much better heat transfer performance than the wide aspect ratio channels (W/H greater than 1). For the square channel (W/H = 1), the 60 deg/45 deg angled ribs provide the best heat transfer performance. For the narrow aspect ratio channel (W/H = 1/4 or 1/2), the 45 deg/60 deg angled ribs are recommended, while the 30 deg/45 deg angled ribs are better for wide aspect ratio channels (W/H = 4 or 2).
Synthetic head related transfer functions (HRTF's) for imposing reprogrammable spatial cues to a plurality of audio input signals included, for example, in multiple narrow-band audio communications signals received simultaneously are generated and stored in interchangeable programmable read only memories (PROM's) which store both head related transfer function impulse response data and source positional information for a plurality of desired virtual source locations. The analog inputs of the audio signals are filtered and converted to digital signals from which synthetic head related transfer functions are generated in the form of linear phase finite impulse response filters. The outputs of the impulse response filters are subsequently reconverted to analog signals, filtered, mixed, and fed to a pair of headphones.
Synthetic head related transfer functions (HRTF's) for imposing reprogramable spatial cues to a plurality of audio input signals included, for example, in multiple narrow-band audio communications signals received simultaneously are generated and stored in interchangeable programmable read only memories (PROM's) which store both head related transfer function impulse response data and source positional information for a plurality of desired virtual source locations. The analog inputs of the audio signals are filtered and converted to digital signals from which synthetic head related transfer functions are generated in the form of linear phase finite impulse response filters. The outputs of the impulse response filters are subsequently reconverted to analog signals, filtered, mixed and fed to a pair of headphones.
Finite-element, transient heat transfer analyses were performed for the first-stage blades of the space shuttle main engine (SSME) high-pressure fuel turbopump. The analyses were based on test engine data provided by Rocketdyne. Heat transfer coefficients were predicted by performing a boundary-layer analysis at steady-state conditions with the STAN5 boundary-layer code. Two different peak-temperature overshoots were evaluated for the startup transient. Cutoff transient conditions were also analyzed. A reduced gas temperature profile based on actual thermocouple data was also considered. Transient heat transfer analyses were conducted with the MARC finite-element computer code.
Engine design, performance, weight and envelope data were established for three mixed-mode orbit-transfer vehicle engine candidates. Engine concepts evaluated are the tripropellant, dual-expander and plug cluster. Oxygen, RP-1 and hydrogen are the propellants considered for use in these engines. Theoretical performance and propellant properties were established for bipropellant and tripropellant mixes of these propellants. RP-1, hydrogen and oxygen were evaluated as coolants and the maximum attainable chamber pressures were determined for each engine concept within the constraints of the propellant properties and the low cycle thermal fatigue (300 cycles) requirement. The baseline engine design and component operating characteristics are determined at a thrust level of 88,964N (20,000 lbs) and a thrust split of 0.5. The parametric data is generated over ranges of thrust and thrust split of 66.7 to 400kN (15 to 90 klb) and 0.4 to 0.8, respectively.
Variable-Domain Displacement Transfer Functions were formulated for shape predictions of complex wing structures, for which surface strain-sensing stations must be properly distributed to avoid jointed junctures, and must be increased in the high strain gradient region. Each embedded beam (depth-wise cross section of structure along a surface strain-sensing line) was discretized into small variable domains. Thus, the surface strain distribution can be described with a piecewise linear or a piecewise nonlinear function. Through discretization, the embedded beam curvature equation can be piece-wisely integrated to obtain the Variable-Domain Displacement Transfer Functions (for each embedded beam), which are expressed in terms of geometrical parameters of the embedded beam and the surface strains along the strain-sensing line. By inputting the surface strain data into the Displacement Transfer Functions, slopes and deflections along each embedded beam can be calculated for mapping out overall structural deformed shapes. A long tapered cantilever tubular beam was chosen for shape prediction analysis. The input surface strains were analytically generated from finite-element analysis. The shape prediction accuracies of the Variable- Domain Displacement Transfer Functions were then determined in light of the finite-element generated slopes and deflections, and were fofound to be comparable to the accuracies of the constant-domain Displacement Transfer Functions
A random access system is proposed for digital storage and retrieval of up to a Petabyte of user data. The system is comprised of stacked memory modules using laser heads writing to an optical medium, in a new shirt-pocket-sized optical storage device called the Opticel. The Opticel described is a completely sealed 'black box' in which an optical medium is accelerated and driven at very high rates to accommodate the desired transfer rates, yet in such a manner that wear is virtually eliminated. It essentially emulates a disk, but with storage area up to several orders of magnitude higher. Access time to the first bit can range from a few milliseconds to a fraction of a second, with time to the last bit within a fraction of a second to a few seconds. The actual times are dependent on the capacity of each Opticel, which ranges from 72 Gigabytes to 1.25 Terabytes. Data transfer rate is limited strictly by the head and electronics, and is 15 Megabits per second in the first version. Independent parallel write/read access to each Opticel is provided using dedicated drives and heads. A Petabyte based on the present Opticel and drive design would occupy 120 cubic feet on a footprint of 45 square feet; with further development, it could occupy as little as 9 cubic feet.
In the early years of remote sensing, emphasis was placed on the processing and analysis of data from a single multispectral sensor, such as the Landsat Multispectral Scanner System (MSS). However, in connection with attempts to use the data for resource management, it was realized that many deficiencies existed in single data sets. A need was established to geographically reference the MSS data and to register with it data from disparate sources. Technological transfer activities have required systems concepts that can be easily transferred to computers of different types in other organizations. ELAS (Earth Resources Laboratory Applications Software), a geographically based information system, was developed to meet the considered needs. ELAS accepts data from a variety of sources. It contains programs to geographically reference the data to the Universal Transverse Mercator grid. One of the primary functions of ELAS is to produce a surface cover map.
Results of research in the remote sensing of natural boreal forest vegetation (the COVER project) are summarized. The study objectives were to establish a baseline forest test site; develop transforms of LANDSAT MSS and TM data for forest composition, biomass, leaf area index, and net primary productivity; and perform tasks required for testing hypotheses regarding observed spectral responses to changes in leaf area index in aspen. In addition, the transfer and documentation of data collected in the COVER project (removed from the Johnson Space Center following the discontinuation of Earth resources research at that facility) is described.
Turbine vane heat transfer predictions are given for smooth and rough vanes where the experimental data show transition moving forward on the vane as the surface roughness physical height increases. Consistent with smooth vane heat transfer, the transition moves forward for a fixed roughness height as the Reynolds number increases. Comparisons are presented with published experimental data. Some of the data are for a regular roughness geometry with a range of roughness heights, Reynolds numbers, and inlet turbulence intensities. The approach taken in this analysis is to treat the roughness in a statistical sense, consistent with what would be obtained from blades measured after exposure to actual engine environments. An approach is given to determine the equivalent sand grain roughness from the statistics of the regular geometry. This approach is guided by the experimental data. A roughness transition criterion is developed, and comparisons are made with experimental data over the entire range of experimental test conditions. Additional comparisons are made with experimental heat transfer data, where the roughness geometries are both regular and statistical. Using the developed analysis, heat transfer calculations are presented for the second stage vane of a high pressure turbine at hypothetical engine conditions.
This paper examines the JPL/Caltech parallel processing system designed for rapid processing and transfer of large quantities of data from remote sensing instruments flown on NASA missions. Two remote sensing analysis applications that use this processing system are described: (1) an analysis system for retrieval of atmospheric parameters (such as species abundance, atmospheric temperature, and water vapor profiles) from data obtained by a Fourier transform IR spectrometer and (2) a prototype airborne SAR processing system. It is shown that a parallel processing system such as the JPL/Caltech system can offer supercomputer computational capability and high-volume data throughput and still be cost-effective.
Measuring apparatus and techniques for heat transfer and pressure drop data in forced convection boiling potassium
Local heat transfer and static pressure data for mercury condensing single tube heat exchangers cooled by sodium potassium