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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 127 records · Page 7

Genetic algorithms applied to the scheduling of the Hubble Space Telescope

A prototype system employing a genetic algorithm (GA) has been developed to support the scheduling of the Hubble Space Telescope. A non-standard knowledge structure is used and appropriate genetic operators have been created. Several different crossover styles (random point selection, evolving points, and smart point selection) are tested and the best GA is compared with a neural network (NN) based optimizer. The smart crossover operator produces the best results and the GA system is able to evolve complete schedules using it. The GA is not as time-efficient as the NN system and the NN solutions tend to be better.

Sponsler, Jeffrey L.↗

Realizing the potential of rapid-cycling Brassica as a model system for use in plant biology research

Rapid-cycling Brassica populations were initially developed as a model for probing the genetic basis of plant disease. Paul Williams and co-workers selected accessions of the six main species for short time to flower and rapid seed maturation. Over multiple generations of breeding and selection, rapid-cycling populations of each of the six species were developed. Because of their close relationship with economically important Brassica species, rapid-cycling Brassica populations, especially those of B. rapa (RCBr) and B. oleracea, have seen wide application in plant and crop physiology investigations. Adding to the popularity of these small, short-lived plants for research applications is their extensive use in K-12 education and outreach.

Review, Tutorial↗

Insights to primitive replication derived from structures of small oligonucleotides

Available information on the structure of small oligonucleotides is surveyed. It is observed that even small oligomers typically exhibit defined structures over a wide range of pH and temperature. These structures rely on a plethora of non-standard base-base interactions in addition to the traditional Watson-Crick pairings. Stable duplexes, though typically antiparallel, can be parallel or staggered and perfect complementarity is not essential. These results imply that primitive template directed reactions do not require high fidelity. Hence, the extensive use of Watson-Crick complementarity in genes rather than being a direct consequence of the primitive condensation process, may instead reflect subsequent selection based on the advantage of accuracy in maintaining the primitive genetic machinery once it arose.

Review↗

Real Time Optima Tracking Using Harvesting Models of the Genetic Algorithm

Tracking optima in real time propulsion control, particularly for non-stationary optimization problems is a challenging task. Several approaches have been put forward for such a study including the numerical method called the genetic algorithm. In brief, this approach is built upon Darwinian-style competition between numerical alternatives displayed in the form of binary strings, or by analogy to 'pseudogenes'. Breeding of improved solution is an often cited parallel to natural selection in.evolutionary or soft computing. In this report we present our results of applying a novel model of a genetic algorithm for tracking optima in propulsion engineering and in real time control. We specialize the algorithm to mission profiling and planning optimizations, both to select reduced propulsion needs through trajectory planning and to explore time or fuel conservation strategies.

Baskaran, Subbiah↗

Probiotics in the Space Food System: Delivery, Microgravity Effects, and the Potential Benefit to Crew Health

As mission distance and duration increase, the need grows for non‐invasive disease prevention and immunomodulation, especially given the limited medical response capability expected for these missions and the immune dysregulation documented in crew. Additionally, changes in diet, lifestyle, antibiotic usage, and the environmental stresses during spaceflight may alter crewmembers' intestinal microbiome. The addition of probiotic bacteria to the space food system is expected to confer immunostimulatory benefits on crewmembers, with the potential to counteract the immune dysregulation that has been documented in spaceflight. Based on previous studies that demonstrated unique microbiological responses to the low shear environment of spaceflight, probiotic organisms hold the potential to induce enhanced beneficial responses through mechanisms, such as beneficial interactions with human immune cells and repression of colonization of pathogens on the mucosa. The work presented here will begin to address two research gaps related to providing probiotics in spaceflight: 1) delivery, and 2) the effect of the low shear microgravity environment on probiotic attributes. The probiotic Lactobacillus acidophilus was selected for investigation due to its wide commercial use and documented benefits that include inhibition of virulence related gene expression in pathogens and mucosal stimulation of immune cells. The delivery system for probiotics has not been determined for spaceflight, where the food system is shelf stable and the lack of refrigeration prevents the use of traditional dairy delivery methods. In order to demonstrate the potential of the space food system to deliver viable probiotic bacteria to crewmembers, the probiotic L. acidophilus was packaged in high barrier flight packaging in nonfat dry milk (NFDM) or retained in commercial capsule form. Viable cells were enumerated over 8 months of storage at 22, 4, and ‐80ºC. The survival of L. acidophilus rehydrated in NFDM, in a PBS control, and directly from the capsule was also evaluated following stress challenge with simulated gastric and intestinal juices to determine the method that would deliver the most viable cells to the intestine, where they would be expected to confer beneficial effects. L. acidophilus was found to be stable to gastric and intestinal juice challenge when delivered in rehydrated NFDM, even after two hours of exposure. In comparison, L. acidophilus was reduced by 1‐5 logs when exposed to gastric and intestinal juice directly and when rehydrated in a PBS control. Shelf life data indicated that L. acidophilus would require refrigerated or frozen storage to remain viable at adequate levels over the multi‐year storage periods required for spaceflight. This study suggests that the protective effect provided by the dairy matrix, and not merely rehydration prior to consumption, extends probiotic viability and stress tolerance during storage in spaceflight and in simulated digestion conditions more adequately than a capsule. In addition to effective delivery, it is essential to understand the microgravity effects on the stress tolerances and genetic expression of probiotic bacteria to enable optimization of growth, survival, strain selection, and conferred benefits in spaceflight. In our current study, ground‐based characterization of the growth, stress response, and transcriptomic response of L. acidophilus will be accomplished using the low shear modeled microgravity (LSMMG) culture environment in the rotating wall vessel (RWV). We hypothesize that L. acidophilus will maintain or improve its growth and stress response following culture in the LSMMG environment, and that transcriptomic analysis will define the associated molecular mechanism(s), resulting in the ability to optimize strain selection.

Castro, S. L.↗

Bingo: A Customizable Framework for Symbolic Regression with Genetic Programming

In this paper, we introduce Bingo, a flexible and customizable yet performant Python framework for symbolic regression with genetic programming. Bingo maintains a modular code structure for simple abstraction and easily swappable components. Fitness functions, selection methods, and constant optimization methods allow for easy problem-specific customization. Bingo also maintains several features for increased efficiency such as parallelism, equation simplification, and a C++ backend. We compare Bingo’s performance to other genetic programming for symbolic regression (GPSR) methods to show that it is both competitive and flexible.

machine learning↗

Bingo: A Customizable Framework for Symbolic Regression with Genetic Programming

In this paper, we introduce Bingo, a flexible and customizable yet performant Python framework for symbolic regression with genetic programming. Bingo maintains a modular code structure for simple abstraction and easily swappable components. Fitness functions, selection methods, and constant optimization methods allow for easy problem-specific customization. Bingo also maintains several features for increased efficiency such as parallelism, equation simplification, and a C++ backend. We compare Bingo’s performance to other genetic programming for symbolic regression (GPSR) methods to show that it is both competitive and flexible.

David Randall↗

Robust Trajectory Optimization for Guided Powered Descent and Landing

A robust trajectory optimization approach for guidance algorithm gain selection for powered descent and landing is developed. This approach uses a genetic algorithm to determine optimal guidance algorithm parameters while incorporating uncertainty information from linear covariance analysis. The optimal guidance algorithm parameters are determined while accounting for environment, navigation, and vehicle property uncertainty and sensor suite fidelity. As a demonstration of this method, the optimal gains for the fractional polynomial powered descent guidance are found for the braking phase of a robotic lunar landing mission. Scenarios with differing sensor suites and sensor qualities are considered, with objective functions to minimize variability in propellant usage or terminal position. Results show that the optimal guidance algorithm gains for a given trajectory differ based on the sensor suite, and optimal guidance algorithm gains may result in up to 20% performance improvements over the baseline in propellant usage and landed accuracy.

Grace E Calkins↗

Biomass yields, reproductive fertility, compositional analysis, and genetic diversity of newly developed triploid giant miscanthus hybrids

Abstract Miscanthus × giganteus (giant miscanthus), first found as a naturally occurring hybrid, has shown promise as a bioenergy/biomass crop throughout much of the temperate world. This allotriploid (2 n = 3 x = 57) hybrid resulted from a cross between tetraploid Miscanthus sacchariflorus (2 n = 4 x = 76) and diploid Miscanthus sinensis (2 n = 2 x = 38) and is particularly desirable due to its low fertility that minimizes reseeding and potential invasiveness. However, there is limited genetic diversity in commonly grown cultivars of triploid M. × giganteus and breeding and development efforts to improve and domesticate this crop have been minimal. Here, we report on newly developed M. × giganteus hybrids compared with the industry standard M. × giganteus '1993‐1780'. Dry biomass yields of new hybrids ranged from 19.5 to 32.4 Mg/ha/year for the fourth growing season, compared with 21.0 Mg/ha/year for M. × giganteus '1993‐1780'. Plant reproductive fertility remained low for all accessions with overall fertility [(seed set × seed germination)/100] ranging from 0.3% to 4.5% for new hybrids compared to 0.4% for M. × giganteus '1993‐1780'. Culm density and height varied among accessions and were positively correlated with increased biomass. Based on compositional analyses, theoretical ethanol yields ranged from 9, 740 to 16,278 L/ha/year for new hybrids compared to 10,406 L/ha/year for M. × giganteus '1993‐1780'. Relative feed value indices were low overall and ranged between 66.0 and 72.8 for new hybrids compared to M. × giganteus '1993‐1780' with 71.3. The genetic diversity of new hybrids, compared with existing cultivars, was characterized using whole genome sequences. Based on pair‐wise distances, cluster analysis clearly showed increased diversity of new hybrids compared with earlier selections. These results document new triploid hybrids of M. × giganteus with enhanced biomass and theoretical ethanol yields in combination with broader genetic diversity and lowreproductive fertility.

Touchell, Darren H.↗

A Computational Approach for Model Update of an LS-DYNA Energy Absorbing Cell

NASA and its contractors are working on structural concepts for absorbing impact energy of aerospace vehicles. Recently, concepts in the form of multi-cell honeycomb-like structures designed to crush under load have been investigated for both space and aeronautics applications. Efforts to understand these concepts are progressing from tests of individual cells to tests of systems with hundreds of cells. Because of fabrication irregularities, geometry irregularities, and material properties uncertainties, the problem of reconciling analytical models, in particular LS-DYNA models, with experimental data is a challenge. A first look at the correlation results between single cell load/deflection data with LS-DYNA predictions showed problems which prompted additional work in this area. This paper describes a computational approach that uses analysis of variance, deterministic sampling techniques, response surface modeling, and genetic optimization to reconcile test with analysis results. Analysis of variance provides a screening technique for selection of critical parameters used when reconciling test with analysis. In this study, complete ignorance of the parameter distribution is assumed and, therefore, the value of any parameter within the range that is computed using the optimization procedure is considered to be equally likely. Mean values from tests are matched against LS-DYNA solutions by minimizing the square error using a genetic optimization. The paper presents the computational methodology along with results obtained using this approach.

Horta, Lucas G.↗

Mapping Vegetation Structure in Kakadu National Park: An AIRSAR and GIS Application in Conservation

Airborne Synthetic Aperture Radar (AIRSAR) data were used to map vegetation structure in Kakadu National Park Australia as part of the PACRIM project. SAR data were co-registered with Landsat TM, aerial photos, and map data in a geographic information system for a small test area consisting of mangrove, floodplain grasslands, lowland tropical evergreen forest and upland mixed deciduous and evergreen tropical forest near the South Alligator River. Landsat (Thematic Mapper) TM very clearly showed the floristic composition and burn scars from the previous years fires and the AIRSAR data provided a profile of vegetation structure. Extensive field data on vegetation species composition and structure were collected across a series of transects in cooperation with a survey of avifauna in an effort to link the habitat edge structure with bird species responses. A test site was found that contained two types of habitat edges: 1) A structure specific edge - characterized by the appearance of a very strong structural change in the forest canopy occurring in the absence of a substantial turnover in floristics. 2) Floristic edge - a sharp transition in vegetation genetic composition with a mixed set of structural changes. Specific polarization combinations were selected that were highly correlated to a set of desired structural parameters found in the field data. Classification routines were employed to group radar pixels into 3 structural classes based on: the Surface Area to Volume ratio (SA/V) of the stems, the SA/V of the branches, and the leaf area index of the canopy. Separate canopy structure maps were then entered into the GIS and bird responses were observed relative to the classes and their boundaries. Follow-on work will consist of extending this approach to neighboring areas, generating structure maps, predicting bird responses across the edges, and make accuracy assessments.

Imhoff, Marc L.↗

Software Searches for Better Spacecraft-Navigation Models

ADAPT is a computer program that searches for better mathematical models for spacecraft navigation. The task of tuning trajectory-determination models for interplanetary navigation is complex, requiring an intensive search of multiple dynamical and nondynamical models that yield trajectory solutions with minimal errors. By automating the search, ADAPT eases the task of human analysts and enables them to consider wider ranges of potential solutions. ADAPT uses genetic algorithms to search a range of relevant parameters in a user-selected design space to arrive at values for those parameters that best fit the measured spacecraft-tracking data. The user s guide for ADAPT reviews the theoretical basis of the program and presents two example applications. One example is that of selecting a solar-radiation model for the Mars Pathfinder (MPF) mission using MPF tracking data and an extended Kalman filter from prior spacecraft-navigation software. The second example is of the use of tracking data from the Stardust spacecraft mission combined with a pseudo-epoch-state batch filter and an empirical small-forces model to find improved impulse models for use during Stardust attitude adjustments.

Ely, Todd↗

Effects of space environment on T-7 bacteriophage and spores of Bacillus subtilis 168

Two strains of Bacillus subtilis were exposed to components of the ultraviolet spectrum in space. Both strains possess multiple genetic markers, and one of the strains is defective in the ability to repair ultraviolet damage. The T-7 bacteriophage of Escherichia coli was also exposed to selected wavelengths and energy levels of ultraviolet light in space. Preliminary findings do not reveal anomalies in survival rates. Data are not yet available on detailed genetic analyses.

Spizizen, J.↗

In vitro selection of catalytic RNAs

In vitro selection techniques are poised to allow a rapid expansion of the study of catalysis by RNA enzymes (ribozymes). This truly molecular version of genetics has already been applied to the study of the structures of known ribozymes and to the tailoring of their catalytic activity to meet specific requirements of substrate specificity or reaction conditions. During the past year, in vitro selection has been successfully used to isolate novel RNA catalysts from random sequence pools.

NASA Discipline Exobiology↗

Leveraging CRISPR Cas9 RNPs and Cre- loxP in Picochlorum celeri for generation of field deployable strains and selection marker recycling

As new highly productive strains of algae are discovered and developed to meet the energy, chemical, and food requirements of the future, genetic engineering of those strains in a manner that yields deployable transformants is paramount. This study introduces the novel CRoxP ($\underline{\textrm{C}}$$\textrm{as9}$ $\underline{\textrm{R}}$$\textrm{NPs}$ coupled with an inducible $\underline{\textrm{CR}}$$\textrm{e}$-$\textrm{l}\underline{\textrm{oxP}}$) system for rapid generation of marker- and transgene-free strains of Picochlorum celeri. The CRoxP system allows reuse of selection markers without Cas9 expression in vivo, eliminating many of the bottlenecks associated with conventional CRISPR Cas9 use for precise genome editing. In P. celeri, transformants were generated with a turnaround time as short as 21 days between transformation and being ready for another round of transformation with the same selection marker by using the CRoxP system. As a use-case for CRoxP, depigmented strains of P. celeri were generated by multiplexed Cas9 disruption of major LHCII genes followed by either a second round of LHCII targeting, or knockout of an LHCI gene. One transformant tested in flask culture (R6) exhibited similar biomass production to the wild type with 46% less Chl a + b on a biomass basis. In photobioreactors and under diel light simulating a solar day, a transformant (LhcBM31) exhibited 34 g AFDW m –2 d –1 with 54% less Chl a + b on a biomass basis vs. wild type.

09 BIOMASS FUELS↗

Adaptive gene loss in the common bean pan-genome during range expansion and domestication

The common bean ( Phaseolus vulgaris L.) is a crucial legume crop and an ideal evolutionary model to study adaptive diversity in wild and domesticated populations. Here, we present a common bean pan-genome based on five high-quality genomes and whole-genome reads representing 339 genotypes. It reveals ~234 Mb of additional sequences containing 6,905 protein-coding genes missing from the reference, constituting 49% of all presence/absence variants (PAVs). More non-synonymous mutations are found in PAVs than core genes, probably reflecting the lower effective population size of PAVs and fitness advantages due to the purging effect of gene loss. Our results suggest pan-genome shrinkage occurred during wild range expansion. Selection signatures provide evidence that partial or complete gene loss was a key adaptive genetic change in common bean populations with major implications for plant adaptation. The pan-genome is a valuable resource for food legume research and breeding for climate change mitigation and sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗

Engineering the green algae Chlamydomonas incerta for recombinant protein production

Chlamydomonas incerta , a genetically close relative of the model green alga Chlamydomonas reinhardtii , shows significant potential as a host for recombinant protein expression. Because of the close genetic relationship between C. incerta and C. reinhardtii , this species offers an additional reference point for advancing our understanding of photosynthetic organisms, and also provides a potential new candidate for biotechnological applications. This study investigates C. incerta ’s capacity to express three recombinant proteins: the fluorescent protein mCherry, the hemicellulose-degrading enzyme xylanase, and the plastic-degrading enzyme PHL7. We have also examined the capacity to target protein expression to various cellular compartments in this alga, including the cytosol, secretory pathway, cytoplasmic membrane, and cell wall. When compared directly with C. reinhardtii , C. incerta exhibited a distinct but notable capacity for recombinant protein production. Cellular transformation with a vector encoding mCherry revealed that C. incerta produced approximately 3.5 times higher fluorescence levels and a 3.7-fold increase in immunoblot intensity compared to C. reinhardtii . For xylanase expression and secretion, both C. incerta and C. reinhardtii showed similar secretion capacities and enzymatic activities, with comparable xylan degradation rates, highlighting the industrial applicability of xylanase expression in microalgae. Finally, C. incerta showed comparable PHL7 activity levels to C. reinhardtii , as demonstrated by the in vitro degradation of a polyester polyurethane suspension, Impranil® DLN. Finally, we also explored the potential of cellular fusion for the generation of genetic hybrids between C. incerta and C. reinhardtii as a means to enhance phenotypic diversity and augment genetic variation. We were able to generate genetic fusion that could exchange both the recombinant protein genes, as well as associated selectable marker genes into recombinant offspring. These findings emphasize C. incerta ’s potential as a robust platform for recombinant protein production, and as a powerful tool for gaining a better understanding of microalgal biology.

cell membranes↗

Comparison of Structural Optimization Techniques for a Nuclear Electric Space Vehicle

The purpose of this paper is to utilize the optimization method of genetic algorithms (GA) for truss design on a nuclear propulsion vehicle. Genetic Algorithms are a guided, random search that mirrors Darwin s theory of natural selection and survival of the fittest. To verify the GA s capabilities, other traditional optimization methods were used to compare the results obtained by the GA's, first on simple 2-D structures, and eventually on full-scale 3-D truss designs.

Benford, Andrew↗