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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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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Design, Synthesis, and Validation: Genome Scale Optimization of Energy Flux through Compartmentalized Metabolic Networks in a Model Photosynthetic Eukaryotic Microbe (Final Report)

Photosynthetic organisms have recently gained considerable attention for a role in development of renewable energy sources. Genome-enabled systems biology methodology and modeling, coupled with high throughput genome engineering strategies, present opportunities to develop sustainable and economical applications such as fuel production within the next 10 to 15 years. However, optimization of light-driven metabolism for biomass or biofuel production will require significant advances in methodological throughput as well as improvements in detailed systems biology understanding of photosynthetic processes and cellular metabolism. The ability of diatoms to thrive in upwelling-induced, periodically nutrient-rich conditions makes them the base for the world’s shortest and most energy-efficient food webs. Diatom photosynthesis is estimated to account for between 25% and 40% of the 45-50 billion tons of organic carbon fixed annually in the sea.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2003

Mars Digital Image Model 2.1 Control Network

USGS is currently preparing a new version of its global Mars digital image mosaic, which will be known as MDIM 2.1. As part of this process we are completing a new photogrammetric solution of the global Mars control network. This is an improved version of the network established earlier by RAND and USGS personnel, as partially described previously. MDIM 2.1 will have many improvements over earlier Viking Orbiter (VO) global mosaics. Geometrically, it will be an orthoimage product, draped on Mars Orbiter Laser Altimeter (MOLA) derived topography, thus accounting properly for the commonly oblique VO imagery. Through the network being described here it will be tied to the newly defined IAU/IAG 2000 Mars coordinate system via ties to MOLA data. Thus, MDIM 2.1 will provide complete global orthorectified imagery coverage of Mars at the resolution of 1/256 deg of MDIM 2.0, and be compatible with MOLA and other products produced in the current coordinate system.

Archinal, B. A.↗
NASA NTRS1997

Electrical signal transmission and gap junction regulation in a bone cell network: a cable model for an osteon

A cable model is formulated to estimate the spatial distribution of intracellular electric potential and current, from the cement line to the lumen of an osteon, as the frequency of the loading and the conductance of the gap junction are altered. The model predicts that the characteristic diffusion time for the spread of current along the membrane of the osteocytic processes, 0.03 sec, is nearly the same as the predicted pore pressure relaxation time in Zeng et al. (Annals of Biomedical Engineering. 1994) for the draining of the bone fluid into the osteonal canal. This approximate equality of characteristic times causes the cable to behave as a high-pass, low-pass filter cascade with a maximum in the spectral response for the intracellular potential at approximately 30 Hz. This behavior could be related to the experiments of Rubin and McLeod (Osteoporosis, Academic Press, 1996) which show that live bone appears to be selectively responsive to mechanical loading in a specific frequency range (15-30 Hz) for several species.

NASA Discipline Musculoskeletal↗
NASA NTRS1998

Hidden Markov Models and Neural Networks for Fault Detection

Continuous online monitoring of complex dynamic systems is common in applications as diverse as industrial plant operations, telecommunications network, and biomedical health monitoring. For monitoring purposes, the exact nature of the system under observation is typically not relevant provided there exist some measurements or symptoms which provide diagnostics information regarding the underlying system state.

Markov Fault Detection↗