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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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Behavior of low-kink-density steps in solution growth and consequences for general understanding of spiral crystal growth processes will be overviewed. Also, influence of turbulence on step bunching and possibility to diminish this bunching will be presented.
No abstract available
Dynamic differential thermal analysis with He flow performed on biological specimens, proteins and starches, showing discrete decomposition peaks monitoring pyrolysis process
An investigation into the effect of hypokinesia on the ribonucleic acid (RNA) content, the nucleotide composition, and dynamics of protein content in the motoneuron of the rat spinal cord anterior horns is described. Methodology and findings are presented. The study results showed that the nucleotide composition of the total cellular RNA at all the studied periods of hypokinesia remained unchanged and is characteristic for the cytoplasmic, high polymer ribosomal RNA. This means that with a change in the functional state of the neuron the newly formed RNA of the nerve cell has the same composition of bases as the original RNA that belongs to the ribosomal type.
No abstract available
No abstract available
Dynamic differential thermal analysis of dried plant and animal specimens and related substances yielding discrete decomposition peaks of exothermic type
The dynamic coupling between mass transport and incorporation of growth units into the surface of a crystal growing from solution in microgravity is used to derive quantitative information on the crystal growth kinetics. To this end, new procedures for experiment preparation, interferometric data processing and model fitting have been developed. The use of experimental data from the bulk diffusive maw transport together with a model for steady state stagnant crystal growth allows the detailed quantitative understanding of the kinetics of both the concentration depletion zone around the crystal and the growth of the crystal interface. The protein crystal used in the experiment is shown to be growing in the mixed kinetic regime (0.2 x 10(exp -6) centimeters per second less than beta R/D less than 0.9 x 10(exp -6) centimeters per second).
No abstract available
No abstract available
The effects of a very low calcium diet, with variable high and low protein intake, on the dynamics of calcium metabolism and the mechanism of calciuretics, are examined. The experiment, using male subjects, was designed to study the role of intestinal calcium absorption on urinary calcium excretion, and the rate of production of endogeneously secreted calcium in the gastrointestinal tract. The study showed an average of 70% fractional absorption rate during very low calcium intake, and that a decrease in renal tubular reabsorption of calcium is responsible for calciuretic effects of high protein intake. The study also indicates that there is a tendency to develop osteoporosis after long periods of low calcium intake, especially with a concurrent high protein intake.
Modeling dynamical systems composed of aggregations of primitive proteins is critical to the field of astrobiological science involving early evolutionary structures and the origins of life. Unfortunately traditional non-multi-agent methods either require oversimplified models or are slow to converge to adequate solutions. This paper shows how to address these deficiencies by modeling the protein aggregations through a utility based multi-agent system. In this method each agent controls the properties of a set of proteins assigned to that agent. Some of these properties determine the dynamics of the system, such as the ability for some proteins to join or split other proteins, while additional properties determine the aggregation s fitness as a viable primitive cell. We show that over a wide range of starting conditions, there are mechanisins that allow protein aggregations to achieve high values of overall fitness. In addition through the use of agent-specific utilities that remain aligned with the overall global utility, we are able to reach these conclusions with 50 times fewer learning steps.