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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Data for each figure of the article "Greater aperture counteracts effects of reduced stomatal density on WUE: a case study on sugarcane and meta-analysis" published in J. Ex. Bot.
G-jitter convection, caused by time-varying accelerations imparted on a heated container of fluid in low gravity, is investigated analytically. The mathematical model used is constructed from the Navier-Stokes equations which are solved with a finite-difference method on a digital computer. Results are presented for typical space processing configurations and anticipated g-jitter levels, with emphasis on sounding rocket applications. The calculations indicate that g-jitter can cause significant temperature oscillations, increase or decrease local heat transfer and produce oscillatory convective flow patterns. These factors can have significant effects on important processes such as crystal growth (banding, for example) and separation techniques.
Data acquisition, initial site characterization, image and geographic information methods available, and brief evaluations of first-year for NASA's Thematic Mapper (TM) working group are presented. The TM and other spectral data are examined in order to relate local, intensive ecosystem research findings to estimates of carbon cycling rates over wide geographic regions. The effort is to span environments ranging from dry to moist climates and from good to poor site quality using the TM capability, with and without the inclusion of geographic information system (GIS) data, and thus to interpret the local spatial pattern of factors conditioning biomass or productivity. Twenty-eight TM data sets were acquired, archived, and evaluated. The ERDAS image processing and GIS system were installed on the microcomputer (PC-AT) and its capabilities are being investigated. The TM coverage of seven study areas were exported via ELAS software on the Prime to the ERDAS system. Statistical analysis procedures to be used on the spectral data are being identified.
Human performance in orbit is currently limited by several factors beyond the intrinsic awkwardness of motor control in weightlessness. Cognitive functioning can be affected by such factors as cumulative sleep loss, stress and the psychological effects of long-duration small-group isolation. When an astronaut operates a scientific experiment, the performance decrement associated with such factors can lead to lost or poor quality data and even the total loss of a scientific objective, at great cost to the sponsors and to the dismay of the Principal Investigator. In long-duration flights, as anticipated on the International Space Station and on any planetary exploration, the experimental model is further complicated by long delays between training and experiment, and the large number of experiments each crew member must perform. Although no documented studies have been published on the subject, astronauts report that an unusually large number of simple errors are made in space. Whether a result of the effects of microgravity, accumulated fatigue, stress or other factors, this pattern of increased error supports the need for a computerized decision-making aid for astronauts performing experiments. Artificial intelligence and expert systems might serve as powerful tools for assisting experiments in space. Those conducting space experiments typically need assistance exactly when the planned checklist does not apply. Expert systems, which use bits of human knowledge and human methods to respond appropriately to unusual situations, have a flexibility that is highly desirable in circumstances where an invariably predictable course of action/response does not exist. Frequently the human expert on the ground is unavailable, lacking the latest information, or not consulted by the astronaut conducting the experiment. In response to these issues, we have developed "Principal Investigator-in-a-Box," or [PI], to capture the reasoning process of the real expert, the Principal Investigator, and combine that with real-time data available in space in order to advise the astronaut about how to proceed in real time. [PI] advises the astronaut during the progress of an experiment in much the same way a real Principal Investigator might do while looking over the astronaut's shoulder. In its original application, [PI] mimicked several of the tasks of the Principal Investigator, including data quality monitoring, troubleshooting, prescheduling, protocol management and "interesting data" detection. The proposed research focuses on the efficacy of this technique as applied to the data quality monitoring and troubleshooting aspects of [PI].
The intensive field observational phase of JGOFS in the North Atlantic Ocean has shown the importance of oceanic mesoscale variability on biogeochemical cycles and on the strength of the ocean biological pump. Mesoscale physical dynamics govern the major time/space scales of bulk biological variability (biomass, production, and export). Mesoscale eddies seem to have a strong impact on the ecosystem structure and functioning, but observational evidence is rather limited. For the signature of the mesoscale features to exist in the ecosystem, the comparison of temporal scales of formation and evolution of mesoscale features and reaction of the ecosystem is a key factor. Biological patterns are driven by active changes in biological source and sink terms rather than simply by passive turbulent mixing. A first modelling assessment of the regional balances between horizontal and vertical eddy-induced nutrient supplies in the euphotic zone shows that the horizontal transport predominates over the vertical route in the subtropical gyre, whereas the reverse holds true for the other biogeochemical provinces of the North Atlantic. Presently, despite some difference in numbers, the net impact of modelled eddies yields an enhancement of the biological productivity in most provinces of the North Atlantic Ocean. Key issues remaining include variation on the mesoscale of subsurface particle and dissolved organic matter remineralization, improved knowledge of the ecological response to patterns of variability, synopticity in mesoscale surveys along with refining measures of biogeochemical time/space variability. Eventual success of assimilation of in situ and satellite data, still in its infancy in coupled physical/biogeochemical models, will be crucial to achieve JGOFS synthesis in answering which data are most informative, standing stocks or rates, and which ones are relevant. Depending on which end of the spectrum quantification of the effect of mesoscale features on production and community structure is required, complementary strategies are offered. Either one may choose to increase resolution of models up to the very fine mesoscale features scale (a few kms) for the high end, or to include a parametric representation of eddies for the low end.
The intensive field observational phase of JGOFS in the North Atlantic Ocean has shown the importance of oceanic mesoscale variability on biogeochemical cycles and on the strength of the ocean biological pump. Mesoscale physical dynamics govern the major time/space scales of bulk biological variability (biomass, production and export). Mesoscale eddies seem to have a strong impact on the ecosystem structure and functioning, but observational evidence is rather limited. For the signature of the mesoscale features to exist in the ecosystem, the comparison of temporal scales of formation and evolution of mesoscale features and reaction of the ecosystem is a key factor. Biological patterns are driven by active changes in biological source and sink terms rather than simply by passive turbulent mixing. A first modelling assessment of the regional balances between horizontal and vertical eddy-induced nutrient supplies in the euphotic zone shows that the horizontal transport predominates over the vertical route in the subtropical gyre, whereas the reverse holds true for the other biogeochemical provinces of the North Atlantic. Presently. despite some difference in numbers, the net impact of modelled eddies yields an enhancement of the biological productivity in most provinces of the North Atlantic Ocean. Key issues remaining include variation on the mesoscale of subsurface particle and dissolved organic matter remineralization, improved knowledge of the ecological response to patterns of variability, synopticity in mesoscale surveys along with refining measures of biogeochemical time/space variability. Eventual success of assimilation of in situ and satellite data, still in its infancy in coupled physical/biogeochemical models, will be crucial to achieve JGOFS synthesis in answering which data are most informative, standing stocks or rates, and which ones are relevant. Depending on which end of the spectrum quantification of the effect of mesoscale features on production and community structure is required, complementary strategies are offered. Either one may choose to increase resolution of models up to the very fine mesoscale features scale (a few kms) for the high end, or to include a parametric representation of eddies for the low end.
Can people learn to perform two tasks at the same time without interference? To answer this question, the authors trained 6 participants for 36 sessions in a Psychological Refractory Period (PRP) experiment, where Task 1 required a speeded vocal response to an auditory stimulus and Task 2 required a speeded manual response to a visual stimulus. The large PRP effect found initially (353 ms in Session 1) shrank to only about 40 ms over the course of practice, disappearing entirely for 1 of the 6 participants. This reduction in the PRP effect with practice is considerably larger than has been previously reported. The obtained pattern of factor interactions between stimulus onset asynchrony and each of three task difficulty manipulations (Task 1 judgment difficulty, Task 2 stimulus contrast, and Task 2 mapping compatibility) supports a postponement (bottleneck) account of dual-task interference, both before and after practice.
This presentation prepared for the upcoming NASA-Pratt/UTRC meeting describes background and developments on Active Combustion Control.
The relationships between two behavioral patterns, cardiac risk factors, and coronary heart disease are investigated. Risk factors used in the analysis were family history of coronary disease, smoking, cholesterol, obesity, systotic blood pressure, diastolic blood pressure, blood sugar, uric acid, erythrocyte sedimentation rate, and white blood unit. It was found that conventional, non-behavioral pattern risk factors alone were not significantly related to coronary heart disease.
A computer-assisted map analysis system is discussed that characterizes timber supply in terms of standing timber; accessibility considering various harvesting factors; and availability as affected by ownership patterns of timberlands. Factors affecting harvesting include proximity to existing roads and consideration of terrain characteristics. Availability considerations include size of ownership, housing density and excluded areas. The model is demonstrated for a seventy square mile tract in western Massachusetts.
SUMMARY Phytosulfokine (PSK) is a plant growth‐promoting peptide hormone that is perceived by its cell surface receptors PSKR1 and PSKR2 in Arabidopsis. Plants lacking the PSK receptors show phenotypes consistent with PSK signaling repressing some plant defenses. To gain further insight into the PSK signaling mechanism, comprehensive transcriptional profiling of Arabidopsis treated with PSK was performed, and the effects of PSK treatment on plant defense readouts were monitored. Our study indicates that PSK's major effect is to downregulate defense‐related genes; it has a more modest effect on the induction of growth‐related genes. WRKY transcription factors (TFs) emerged as key regulators of PSK‐responsive genes, sharing commonality with a pathogen‐associated molecular pattern (PAMP) responses, flagellin 22 (flg22), but exhibiting opposite regulatory directions. These PSK‐induced transcriptional changes were accompanied by biochemical and physiological changes that reduced PAMP responses, notably mitogen‐activated protein kinase (MPK) phosphorylation (previously implicated in WRKY activation) and the cell wall modification of callose deposition. Comparison with previous studies using other growth stimuli (the sulfated plant peptide containing sulfated tyrosine [PSY] and Pseudomonas simiae strain WCS417) also reveals WRKY TFs' overrepresentations in these pathways, suggesting a possible shared mechanism involving WRKY TFs for plant growth–defense trade‐off.
11 tests were selected from two microcomputer-based performance test batteries because previously these tests exhibited rapid stability (less than 10 min, of practice) and high retest reliability efficiencies (r greater than 0.707 for each 3 min. of testing). The battery was administered three times to each of 108 college students (48 men and 60 women) and a factor analysis was performed. Two of the three identified factors appear to be related to information processing ("encoding" and "throughput/decoding"), and the third named an "output/speed" factor. The spatial, memory, and verbal tests loaded on the "encoding" factor and included Grammatical Reasoning, Pattern Comparison, Continuous Recall, and Matrix Rotation. The "throughput/decoding" tests included perceptual/numerical tests like Math Processing, Code Substitution, and Pattern Comparison. The output speed factor was identified by Tapping and Reaction Time tests. The Wonderlic Personnel Test was group administered before the first and after the last administration of the performance tests. The multiple Rs in the total sample between combined Wonderlic as a criterion and less than 5 min. of microcomputer testing on Grammatical Reasoning and Math Processing as predictors ranged between 0.41 and 0.52 on the three test administrations. Based on these results, the authors recommend a core battery which, if time permits, would consist of two tests from each factor. Such a battery is now known to permit stable, reliable, and efficient assessment.
Neuroscientists are often interested in grouping variables to facilitate understanding of a particular phenomenon. Factor analysis is a powerful statistical technique that groups variables into conceptually meaningful clusters, but remains underutilized by neuroscience researchers presumably due to its complicated concepts and procedures. This paper illustrates an application of factor analysis to identify coordinated patterns of whole-body muscle activation during treadmill walking. Ten male subjects walked on a treadmill (6.4 km/h) for 20 s during which surface electromyographic (EMG) activity was obtained from the left side sternocleidomastoid, neck extensors, erector spinae, and right side biceps femoris, rectus femoris, tibialis anterior, and medial gastrocnemius. Factor analysis revealed 65% of the variance of seven muscles sampled aligned with two orthogonal factors, labeled 'transition control' and 'loading'. These two factors describe coordinated patterns of muscular activity across body segments that would not be evident by evaluating individual muscle patterns. The results show that factor analysis can be effectively used to explore relationships among muscle patterns across all body segments to increase understanding of the complex coordination necessary for smooth and efficient locomotion. We encourage neuroscientists to consider using factor analysis to identify coordinated patterns of neuromuscular activation that would be obscured using more traditional EMG analyses.
Modern biodistributional patterns suggest that modes of larval development are a factor in determining the patterns of diversity in benthic invertebrates. Paleozoic brachiopods had diversity patterns suggesting that they possessed both planktotrophic and nonplanktotrophic modes. It is presently hypothesized that the planktotrophic lineages were lost to extinction, largely or entirely during the Permian-Triassic event, and that the failure of the articulate brachiopods to regain their former importance is substantially due to their nonplanktotrophic developmental mode.
Psychometric analyses of college students' responses to the Jenkins Activity Survey, a self-report measure of the Type A behavior pattern, revealed the presence of two relatively independent factors. Based on these analyses, two scales, labeled Achievement Strivings (AS) and Impatience and Irritability (II), were developed. In two samples of male and female college students, scores on AS but not on II were found to be significantly correlated with grade point average. Responses to a health survey, on the other hand, indicated that frequency of physical complaints was significantly correlated with II but not with AS. These results suggest that there are two relatively independent factors in the Type A pattern that have differential effects on performance and health. Future research on the personality factors related to coronary heart disease and other disorders might more profitably focus on the syndrome reflected in the II scale than on the Type A pattern.
The relationship between the movement time (MT) for accurate and rapid discrete movements of distance A to a target of width W was quantified by Fitts and is given by the equation: MT = a + b log sub 2 (2A/W). This relationship, known as Fitt's Law, received considerable support for many types of movements. It also raises the interesting question: if MT is affected by distance moved and accuracy, then how do the patterns of muscle activation alter? It is suggested that it is unlikely that all movements are initiated by a pulse of constant duration. Instead, it seems that movements are initiated by an agonist burst which is scaled both in the amount of activation and the duration of activation according to either distance, target size, velocity, or a combination of factors. The number of bursts varies considerably and further research is required to establish: (1) which factors affect the pattern of the signal and (2) how different patterns produce movement trajectories.
The spatial organization of chromatin is governed by epigenetic factors, including epigenetic marks and the reader proteins that bind them. By dictating the accessibility of genomic loci, epigenetic factors contribute to the physical regulation of gene expression, enabling diverse cellular phenotypes to be encoded by a shared genome in an individual. Epigenetic dysregulation can lead to aberrations in chromatin architecture, contributing to diseases such as neurological disorders and cancers. Despite the known importance of chromatin organization for human health, the physical mechanisms governing chromatin folding remain underspecified. In this work, we develop a physical model of chromatin organization based on contributions from multiple epigenetic factors. Using our model, we evaluate how conditions in the nuclear environment and crosstalk between epigenetic marks affect the compartmentalization of chromatin into dense heterochromatin and loose euchromatin. Our results emphasize the role of reader protein binding in chromatin compartmentalization. We show that reader proteins interact through an indirect mechanism facilitated by the shared chromatin “scaffold” to which they bind. Under a scenario where reader proteins compete for binding sites, we find that indirect interactions affect the program adopted by the chromatin fiber. By isolating indirect modes of epigenetic crosstalk, we demonstrate how the interplay between epigenetic patterning and environmental factors influences chromatin architecture.
Circadian modulation of episodic bursts is recognized as the normal physiological pattern of diurnal variation in plasma cortisol levels. The primary physiological factors underlying these diurnal patterns are the ultradian timing of secretory events, circadian modulation of the amplitude of secretory events, infusion of the hormone from the adrenal gland into the plasma, and clearance of the hormone from the plasma by the liver. Each measured plasma cortisol level has an error arising from the cortisol immunoassay. We demonstrate that all of these three physiological principles can be succinctly summarized in a single stochastic differential equation plus measurement error model and show that physiologically consistent ranges of the model parameters can be determined from published reports. We summarize the model parameters in terms of the multivariate Gaussian probability density and establish the plausibility of the model with a series of simulation studies. Our framework makes possible a sensitivity analysis in which all model parameters are allowed to vary simultaneously. The model offers an approach for simultaneously representing cortisol's ultradian, circadian, and kinetic properties. Our modeling paradigm provides a framework for simulation studies and data analysis that should be readily adaptable to the analysis of other endocrine hormone systems.