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Problems of constructing an overall convection pattern from various measurements of convection electric fields are examined. Since the measurement techniques used provide information on only a limited spatial region at any time, the construction of the pattern requires a synthesis of data obtained at a variety of times and places. Incoherent scatter radar data for drifting F region plasma are considered as an example.
From a critical comparison and synthesis of data from the four Pioneer Venus Probes, the Pioneer Venus Orbiter, and the Venera 10, 12, and 13 landers, models of the lower and middle atmosphere of Venus are derived. The models are consistent with the data sets within the measurement uncertainties and established variability of the atmosphere. The models represent the observed variations of state properties with latitude, and preserve the observed static stability. The rationale and the approach used to derive the models are discussed, and the remaining uncertainties are estimated.
From a synthesis of data from the Plasma-Science and Ultraviolet-Science instruments on Voyager 1 a radial profile is presented of O(2+) abundance between 4.9 and 42 Jovian radii. A sharp rise is noted in O(2+) mixing ratio near 7.5 Jovian radii, coincident with a sharp rise in effective electron temperature at the outer boundary of the Io plasma torus. Beyond 8.5 Jovian radii the O(2+) mixing ratio is found to be roughly constant which indicates freezing of the ionization prevailing at the outer edge of the hot torus.
HYDROSTAR is a hybrid synthesis radiometer, intended for spaceborne applications, which employs a real aperture (waveguide stick antenna) for resolution along track and employs aperture synthesis to obtain resolution across track. This L-band system is an extension of the successful aircraft prototype, the Electronically Steered Thinned Array Radiometer (ESTAR). A proof-of-concept, full size system was constructed (45 wavelength in the synthesis direction) and subjected to extensive antenna pattern and associated microwave component measurements in an outdoor antenna test facility. HYDROSTAR employs a thinned array of 16 elements each 5.8 inches long in the along track dimension and spanning 9.5 inches across track. Each element is a narrow-wall shunt slot array with 36 slots. The polarization is linear (along-track). In the across track dimension, the antennas are deployed in a minimum redundancy array which has 90 independent baselines spaced in integer multiples of half a wavelength. The closest spacings used are for the first three elements at each end, which are spaced by only one-half wavelength. This study was intended to assess how closely each of 16 stick element patterns compare with their nominal values (as an individual, isolated radiator), when installed in their intended composite thinned array configuration. Extensive pattern measurements of the 16 elements that constitute the HYDROSTAR antenna subsystem were conducted to observe their relative features along the synthesis plane. Data was also collected for the mutual coupling between pairs of selected antennas. All antenna patterns had features different from that of an isolated element indicating some level of interaction among neighboring radiators. Those elements which had nearest neighbors at least five wavelengths away were located near the middle of the array. Their radiation patterns displayed sonic small, symmetric ripple across their full azimuth range. The patterns of elements that lie within 2.5 wavelengths of their neighbors showed stronger and asymmetric features. These are believed to be caused by mutual coupling among these structures. Evidence for this was seen when an antenna position was displaced by 0.05 wavelengths, Its pattern and those of its near neighbors were seen to change. Displacement within the plane of the array were observed to have different effects than displacements out-of-plane. A program of data analysis and theoretical development is in progress to provide a physical interpretation of the properties of these antenna patterns and to develop methods which can optimize the performance of this synthetic aperture imaging system. This includes compensation for pattern asymmetries and element position perturbation.
The abundance of plant nucleolin mRNA is regulated during de-etiolation by phytochrome. A close correlation between the mRNA abundance of nucleolin and mitosis has also been previously reported. These results raised the question of whether the effects of light on nucleolin mRNA expression were a consequence of light effects on mitosis. To test this we compared the kinetics of light-mediated increases in cell proliferation with that of light-mediated changes in the abundance of nucleolin mRNA using plumules of dark-grown pea (Pisum sativum) seedlings. These experiments show that S-phase increases 9 h after a red light pulse, followed by M-phase increases in the plumule leaves at 12 h post-irradiation, a time course consistent with separately measured kinetics of red light-induced increases in the expression of cell cycle-regulated genes. These increases in cell cycle-regulated genes are photoreversible, implying that the light-induced increases in cell proliferation are, like nucleolin mRNA expression, regulated via phytochrome. Red light stimulates increases in the mRNA for nucleolin at 6 h post-irradiation, prior to any cell proliferation changes and concurrent with the reported timing of phytochrome-mediated increases of rRNA abundance. After a green light pulse, nucleolin mRNA levels increase without increasing S-phase or M-phase. Studies in animals and yeast indicate that nucleolin plays a significant role in ribosome biosynthesis. Consistent with this function, pea nucleolin can rescue nucleolin deletion mutants of yeast that are defective in rRNA synthesis. Our data show that during de-etiolation, the increased expression of nucleolin mRNA is more directly regulated by light than by mitosis.
Europa, with its indications of a sub-ice ocean, is of keen interest to astrobiology and planetary geology. Knowledge of the global distribution and timing of Europan geologic units is a key step for the synthesis of data from the Galileo mission, and for the planning of future missions to the satellite. The first geologic map of Europa was produced at a hemisphere scale with low resolution Voyager data. Following the acquisition of higher resolution data by the Galileo mission, researchers have identified surface units and determined sequences of events in relatively small areas of Europa through geologic mapping using images at various resolutions acquired by Galileo's Solid State Imaging camera. These works provided a local to subregional perspective and employed different criteria for the determination and naming of units. Unified guidelines for the identification, mapping and naming of Europan geologic units were put forth by and employed in regional-to-hemispheric scale mapping which is now being expanded into a global geologic map. A global photomosaic of Galileo and Voyager data was used as a basemap for mapping in ArcGIS, following suggested methodology of all-stratigraphy for planetary mapping. The following units have been defined in global mapping and are listed in stratigraphic order from oldest to youngest: ridged plains material, Argadnel Regio unit, dark plains material, lineaments, disrupted plains material, lenticulated plains material and Chaos material.
Adaptive changes in sensorimotor function during spaceflight are reflected by spatial disorientation, motion sickness, gaze destabilization and decrements in balance, locomotion and eye-hand coordination that occur during and following transitions between different gravitational states. The purpose of this study was to conduct a meta-synthesis of data from spaceflight analogs to evaluate their effectiveness in simulating adaptive changes in sensorimotor function. METHODS. The analogs under review were categorized as either acute analogs used to simulate performance decrements accompanied with transient changes, or adaptive analogs used to drive sensorimotor learning to altered sensory feedback. The effectiveness of each analog was evaluated in terms of mechanisms of action, magnitude and time course of observed deficits compared to spaceflight data, and the effects of amplitude and exposure duration. RESULTS. Parabolic flight has been used extensively to examine effects of acute variation in gravitational loads, ranging from hypergravity to microgravity. More recently, galvanic vestibular stimulation has been used to elicit acute postural, locomotor and gaze dysfunction by disrupting vestibular afferents. Patient populations, e.g., with bilateral vestibular loss or cerebellar dysfunction, have been proposed to model acute sensorimotor dysfunction. Early research sponsored by NASA involved living onboard rotating rooms, which appeared to approximate the time course of adaptation and post-exposure recovery observed in astronauts following spaceflight. Exposure to different bed-rest paradigms (6 deg head down, dry immersion) result in similar motor deficits to that observed following spaceflight. Shorter adaptive analogs have incorporated virtual reality environments, visual distortion paradigms, exposure to conflicting tilt-translation cues, and exposure to 3Gx centrifugation. As with spaceflight, there is considerable variability in responses to most of the analogs reviewed. DISCUSSION. A true ground-based flight analog for sensorimotor function is not feasible. A combination of flight analogs; however, can be used to selectively mimic different aspects of the spaceflight-induced sensorimotor performance decrements.
Ocean data assimilation is increasingly recognized as crucial for the accuracy of realtime ocean prediction systems and historical re-analyses. The current status of ocean data assimilation in support of the operational demands of analysis, forecasting and reanalysis is reviewed, focusing on methods currently adopted in operational and realtime prediction systems. Significant challenges associated with the most commonly employed approaches are identified and discussed. Overarching issues faced by ocean data assimilation are also addressed, and important future directions in response to scientific advances, evolving and forthcoming ocean observing systems and the needs of stakeholders and downstream applications are discussed.
Phytoplankton photosynthetic physiology can be investigated through single-turnover variable chlorophyll fluorescence (ST-ChlF) approaches, which carry unique potential to autonomously collect data at high spatial and temporal resolution. Over the past decades, significant progress has been made in the development and application of ST-ChlF methods in aquatic ecosystems, and in the interpretation of the resulting observations. At the same time, however, an increasing number of sensor types, sampling protocols, and data processing algorithms have created confusion and uncertainty among potential users, with a growing divergence of practice among different research groups. In this review, we assist the existing and upcoming user community by providing an overview of current approaches and consensus recommendations for the use of ST-ChlF measurements to examine in-situ phytoplankton productivity and photo-physiology. We argue that a consistency of practice and adherence to basic operational and quality control standards is critical to ensuring data inter-comparability. Large datasets of inter-comparable and globally coherent ST-ChlF observations hold the potential to reveal large-scale patterns and trends in phytoplankton photo-physiology, photosynthetic rates and bottom-up controls on primary productivity. As such, they hold great potential to provide invaluable physiological observations on the scales relevant for the development and validation of ecosystem models and remote sensing algorithms.
Isolation and confinement studies have been essential to the preparation of crewed long-duration space missions, acting as analogues that facilitate the study of psychological and physiological responses to isolation and confinement. They also serve as opportunities for the development, testing, and validation of countermeasures and coping methods to handle the challenges that arise in such scenarios. Due to the small sample sizes in combination with high inter-individual variability, single isolation campaigns are not always sufficient for obtaining statistically significant scientific findings. To address this issue and improve comparability between different studies, the need for standardized measures to be collected in all future isolation and confinement studies was identified. Additionally, these measures should also be shown to be generally valid, reliable, feasible and acceptable in analogue and spaceflight environments. Standard measures in isolation and confinement studies allow for more direct comparisons of results and synthesis of data across isolation and confinement studies as well as provide an important step toward standard measures in spaceflight. An international expert group with representatives from different space agencies worldwide was brought together to define a core set of standard measures for isolation and confinement studies. This paper provides an overview of the expert group’s recommendations for international standard measures for future isolation and confinement studies, along with subsequent updates coordinated by the International Countermeasures Working Group (ICMWG), which was established as a sub-Working Group under the International Space Life Sciences Working Group (ISLSWG). Additional experts were consulted by the ICMWG partner agencies as required. The collection of the described set of isolation standard measures will provide data on the following parameters: sleep, mood, psychological state, psychophysiology, cognitive performance, stress and the immune system, general health and well-being, team measures, nutritional measures, and environmental conditions. For each measure, recommendations were made about duration and frequency of administration, along with specific implementation recommendations in relation to the duration of the isolation study. The set of isolation standard measures will be reassessed every two years at a minimum to ensure they are up to date and reflect the current state-of-the-art.
The Center for Information and Numerical Data Analysis and Synthesis, (CINDAS), measures and maintains databases on thermophysical, thermoradiative, mechanical, optical, electronic, ablation, and physical properties of materials. Emphasis is on aerospace structural materials especially composites and on infrared detector/sensor materials. Within CINDAS, the Department of Defense sponsors at Purdue several centers: the High Temperature Material Information Analysis Center (HTMIAC), the Ceramics Information Analysis Center (CIAC) and the Metals Information Analysis Center (MIAC). The responsibilities of CINDAS are extremely broad encompassing basic and applied research, measurement of the properties of thin wires and thin foils as well as bulk materials, acquisition and search of world-wide literature, critical evaluation of data, generation of estimated values to fill data voids, investigation of constitutive, structural, processing, environmental, and rapid heating and loading effects, and dissemination of data. Liquids, gases, molten materials and solids are all considered. The responsibility of maintaining widely used databases includes data evaluation, analysis, correlation, and synthesis. Material property data recorded on the literature are often conflicting, diverging, and subject to large uncertainties. It is admittedly difficult to accurately measure materials properties. Systematic and random errors both enter. Some errors result from lack of characterization of the material itself (impurity effects). In some cases assumed boundary conditions corresponding to a theoretical model are not obtained in the experiments. Stray heat flows and losses must be accounted for. Some experimental methods are inappropriate and in other cases appropriate methods are carried out with poor technique. Conflicts in data may be resolved by curve fitting of the data to theoretical or empirical models or correlation in terms of various affecting parameters. Reasons (e.g. phase transitions) must be found for unusual dependence or any anomaly. Such critical evaluation involves knowledge of theory, experience in measurement, familiarity with metallurgy (microstructural behavior) and not inconsiderable judgment. An examination of typical data compiled and analyzed by CINDAS shows that the thermal conductivity of a material reported in the literature may vary by a factor of two of more; the range of reported values increases as temperature increases reflecting the difficulty of high temperature measurements. Often only estimates of melt behavior are available, despite the importance of melt properties in modeling, welding, or other solidification processes. There may be only a few measurements available for properties such as kinematic viscosity, even for widely used materials such as stainless steel. In the face of such a paucity of existing data and in a national environment where too few new data are being generated it is nonetheless the responsibility of CINDAS to select and disseminate recommended values of a wide variety of thermophysical properties.
The main features of the data analysis methods adopted by FAST in the calibration and processing of the Hipparcos data are discussed. The structure of the data reduction software is examined, and the actual processing and evaluation are presented. Attention is given to the first look task, the calibration task, data preparation, attitude determination, the great circle reduction, synthesis treatment, iterations, data management and command software, and follow-up and evaluation activities.
A multirate control law synthesized algorithm based on an infinite-time quadratic cost function, was developed along with a method for analyzing the robustness of multirate systems. A generalized multirate sampled-data control law structure (GMCLS) was introduced. A new infinite-time-based parameter optimization multirate sampled-data control law synthesis method and solution algorithm were developed. A singular-value-based method for determining gain and phase margins for multirate systems was also developed. The finite-time-based parameter optimization multirate sampled-data control law synthesis algorithm originally intended to be applied to the aircraft problem was instead demonstrated by application to a simpler problem involving the control of the tip position of a two-link robot arm. The GMCLS, the infinite-time-based parameter optimization multirate control law synthesis method and solution algorithm, and the singular-value based method for determining gain and phase margins were all demonstrated by application to the aircraft control problem originally proposed for this project.
Earth science research and application requirements for multispectral data have often been driven by currently available remote sensing technology. Few parametric studies exist that specify data required for certain applications. Consequently, data requirements are often defined based on the best data available or on what has worked successfully in the past. Since properties such as spatial resolution, swath width, spectral bands, signal-to-noise ratio (SNR), data quantization and band-to-band registration drive sensor platform and spacecraft system architecture and cost, analysis of these criteria is important to optimize system design objectively. Remote sensing data requirements are also linked to calibration and characterization methods. Parameters such as spatial resolution, radiometric accuracy and geopositional accuracy affect the complexity and cost of calibration methods. However, few studies have quantified the true accuracies required for specific problems. As calibration methods and standards are proposed, it is important that they be tied to well-known data requirements. The Application Research Toolbox (ART) developed at the John C. Stennis Space Center provides a simulation-based method for multispectral data requirements development. The ART produces simulated datasets from hyperspectral data through band synthesis. Parameters such as spectral band shape and width, SNR, data quantization, spatial resolution and band-to-band registration can be varied to create many different simulated data products. Simulated data utility can then be assessed for different applications so that requirements can be better understood.
Earth science research and application requirements for multispectral data have often been driven by currently available remote sensing technology. Few parametric studies exist that specify data required for certain applications. Consequently, data requirements are often defined based on the best data available or on what has worked successfully in the past. Since properites such as spatial resolution, swath width, spectral bands, signal-to-noise ratio (SNR), data quantization, and band-to-band registration drive sensor platform and spaceraft system architecture and cost, analysis of these criteria is important to objectively optimize system design. Remote sensing data requirements are also linked to calibration and characterization methods. Parameters such as spatial resolution, radiometric accuracy, and geopositional accuracy affect the complexity and cost of calibration methods. However, there are few studies that quantify the true accuracies required for specific problems. As calibration methods and standards are proposed, it is important that they be tied to well-known data requirements. The Application Research Toolbox (ART) developed at Stennis Space Center provides a simulation-based method for multispectral data requirements development. The ART produces simulated data sets from hyperspectral data through band synthesis. Parameters such as spectral band shape and width, SNR, data quantization, spatial resolution, and band-to-band registration can be varied to create many different simulated data products. Simulated data utility can then be assessed for different applications so that requirements can be better understood. This paper describes the ART and its applicability for rigorously deriving remote sensing data requirements.
Programmed search and gradient search methods for determination of sampling intervals in synthesis of sampled data models of human operators
The finding of smooth analytic representations for antenna reflector surfaces which are prescribed only by discretized data obtained by various synthesis methods is examined. Frequently the data are distributed in a nonuniform grid and contain noise. The smoothness required is to C sub 1 for physical optics diffraction analysis and to C sub 2 for geometrical theory of diffraction (GTD) analysis. The GTD analysis approach requires a surface description which returns data very rapidly. Two methods of interpolation, the global and the local methods, are discussed. They each have advantages and disadvantages; characteristics are discussed and examples are presented.
The Space Shuttle Challenger was maneuvered into an SAR data-acquisition mode to capture a SIR-B scene of Hurricane Josephine, which presented itself as an unscheduled target of opportunity during NASA Mission 41-G during October 1984. Steeply sloped seas approaching 10 m in height were observed several hundred km in advance of the hurricane track. Mission attitude data indicate that the Shuttle pitch, roll, and yaw were unstable during the data take. The statistical clutterlock used by the ground SAR processor yields a Doppler frequency estimate that tracks the Shuttle yaw variation but is ambiguous with a single discontinuity equal to one multiple of the radar pulse repetition frequency. The SIR-B signal data have been compressed under several Doppler parameterizations to investigate the ambiguity of the clutterlock. Resultant ocean images are analyzed for their contrast and resolution properties.