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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Ground Testing of the EMCS Seed Cassette for Biocompatibility with the Cellular Slime Mold, Dictyostelium Discoideum

The European Modular Cultivation System, EMCS, was developed by ESA for plant experiments. To expand the use of flight verified hardware for various model organisms, we performed ground experiments to determine whether ARC EMCS Seed Cassettes could be adapted for use with cellular slime mold for future space flight experiments. Dictyostelium is a cellular slime mold that can exist both as a single-celled independent organism and as a part of a multicellular colony which functions as a unit (pseudoplasmodium). Under certain stress conditions, individual amoebae will aggregate to form multicellular structures. Developmental pathways are very similar to those found in Eukaryotic organisms, making this a uniquely interesting organism for use in genetic studies. Dictyostelium has been used as a genetic model organism for prior space flight experiments. Due to the formation of spores that are resistant to unfavorable conditions such as desiccation, Dictyostelium is also a good candidate for use in the EMCS Seed Cassettes. The growth substratum in the cassettes is a gridded polyether sulfone (PES) membrane. A blotter beneath the PES membranes contains dried growth medium. The goals of this study were to (1) verify that Dictyostelium are capable of normal growth and development on PES membranes, (2) develop a method for dehydration of Dictyostelium spores with successful recovery and development after rehydration, and (3) successful mock rehydration experiments in cassettes. Our results show normal developmental progression in two strains of Dictyostelium discoideum on PES membranes with a bacterial food source. We have successfully performed a mock rehydration of spores with developmental progression from aggregation to slug formation, and production of morphologically normal spores within 9 days of rehydration. Our results indicate that experiments on the ISS using the slime mold, Dictyostelium discoideum could potentially be performed in the flight verified hardware of the EMCS ARC Seed Cassettes.

biocompatibility↗
NASA NTRS1977

Orientale and Caloris

Based on revised stratigraphy, structural interpretation, explosion-crater data, and a genetic model for Orientale, it is suggested that Orientale and Caloris have much in common. It is noted that: (1) although the basin fill in Caloris is different from that seen in Orientale, the materials between the most prominent scarp and the weakly-developed outer scarp may be degraded equivalents of the massifs and knobs associated with the Montes Rook, (2) the Montes Rook and the main Caloris scarp have similar stratigraphic and structural features, (3) the lineated ejecta derived from shallower horizons are found near and beyond the weakly-developed outer Caloris scarp which is the counterpart of the Orientale scarp, (4) a well developed field of secondary craters is observed beyond 1 basin diameter at Caloris, (5) the observed textural differences between the material around the main Caloris scarp and the lineated material beyond suggest that Mercury is layered and that Caloris crater excavated coherent materials from one or more of these layers at depth, and (6) the difference in spacing between the Caloris rings is not related to internal layering effects.

Mccauley, J. F.↗
NASA NTRS1992

Origin of giant Martian polygons

Extensive areas of the Martian northern plains in Utopia and Acidalia planitiae are characterized by 'polygonal terrane'. Polygonal terrane consists of material cut by complex troughs defining a pattern resembling mudcracks, columnar joints, or frost-wedge polygons on earth. However, the Martian polygons are orders of magnitude larger than these potential earth analogues, leading to severe mechanical difficulties for genetic models based on simple analogy arguments. Plate-bending and finite element models indicate that shrinkage of desiccating sediment or cooling volcanics accompanied by differential compaction over buried topography can account for the stresses responsible for polygon troughs as well as the large size of the polygons. Although trough widths and depths relate primarily to shrinkage, the large scale of the polygonl pattern relates to the spacing between topographic elevations on the surface buried beneath polygonal terrane material. Geological relationships favor a sedimentary origin for polygonal terrane material, but our model is not dependent on the specific genesis. Our analysis also suggests that the polygons must have formed at a geologically rapid rate.

Mcgill, George E.↗
NASA NTRS1999

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↗
NASA NTRS1997

Information transfer from peptide nucleic acids to RNA by template-directed syntheses

Peptide nucleic acids (PNAs) are uncharged analogs of DNA and RNA in which the ribose-phosphate backbone is substituted by a backbone held together by amide bonds. PNAs are interesting as models of alternative genetic systems because they form potentially informational base paired helical structures. A PNA C10 oligomer has been shown to act as template for efficient formation of oligoguanylates from activated guanosine ribonucleotides. In a previous paper we used heterosequences of DNA as templates in sequence-dependent polymerization of PNA dimers. In this paper we show that information can be transferred from PNA to RNA. We describe the reactions of activated mononucleotides on heterosequences of PNA. Adenylic, cytidylic and guanylic acids were incorporated into the products opposite their complement on PNA, although less efficiently than on DNA templates.

NASA Discipline Exobiology↗
NASA NTRS2003

Evaluation of Genetic Algorithm Concepts Using Model Problems: Multi-Objective Optimization - Part 2

A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. Several new features including a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all optimization problems attempted. The binning algorithm generally provides pareto front quality enhancements and moderate convergence efficiency improvements for most of the model problems. The gene-space transformation procedure provides a large convergence efficiency enhancement for problems with non-convoluted pareto fronts and a degradation in efficiency for problems with convoluted pareto fronts. The most difficult problems --multi-mode search spaces with a large number of genes and convoluted pareto fronts-- require a large number of function evaluations for GA convergence, but always converge.

Holst, Terry L.↗
NASA NTRS2003

Evaluation of Genetic Algorithm Concepts using Model Problems: Single-Objective Optimization - Part 1

A genetic-algorithm-based optimization approach is described and evaluated using a simple hill-climbing model problem. The model problem utilized herein allows for the broad specification of a large number of search spaces including spaces with an arbitrary number of genes or decision variables and an arbitrary number hills or modes. In the present study, only single objective problems are considered. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all problems attempted. The most difficult problems - those with large hyper-volumes and multi-mode search spaces containing a large number of genes - require a large number of function evaluations for GA convergence, but they always converge.

Holst, Terry L.↗
NASA NTRS2000

Modeling the Normal and Neoplastic Cell Cycle with 'Realistic Boolean Genetic Networks': Their Application for Understanding Carcinogenesis and Assessing Therapeutic Strategies

In this paper we show how Boolean genetic networks could be used to address complex problems in cancer biology. First, we describe a general strategy to generate Boolean genetic networks that incorporate all relevant biochemical and physiological parameters and cover all of their regulatory interactions in a deterministic manner. Second, we introduce 'realistic Boolean genetic networks' that produce time series measurements very similar to those detected in actual biological systems. Third, we outline a series of essential questions related to cancer biology and cancer therapy that could be addressed by the use of 'realistic Boolean genetic network' modeling.

Szallasi, Zoltan↗
NASA NTRS1996

Genetic Algorithms and Local Search

The first part of this presentation is a tutorial level introduction to the principles of genetic search and models of simple genetic algorithms. The second half covers the combination of genetic algorithms with local search methods to produce hybrid genetic algorithms. Hybrid algorithms can be modeled within the existing theoretical framework developed for simple genetic algorithms. An application of a hybrid to geometric model matching is given. The hybrid algorithm yields results that improve on the current state-of-the-art for this problem.

Whitley, Darrell↗
NASA NTRS2019

Thermal Property Estimation of Fibrous Insulation: Heat Transfer Modeling and the Continuous Genetic Algorithm

Thermal properties of high-temperature fibrous insulation materials were estimated from transient thermal tests using an inverse heat transfer technique. Transient temperature data from an experimental set up was collected and a simple, one-dimensional numerical model was constructed to replicate the temperatures within the test assembly. The Continuous Genetic Algorithm optimization technique in conjunction with a numerical thermal model and transient test data was used to estimate coefficients of a functional representation of the thermal property. The thermal properties, i.e., thermal conductivity and specific heat, of an alumina insulation felt were estimated over the temperature range of 300 K to 1700 K at various constant static pressures in nitrogen gas and compared with published data. The resulting thermal property estimates were within 10% of published values over the entire temperature range at various pressures. The methodology, application, and results are presented.

Frye, Elora↗
DOE OSTI2025

FluxRETAP: a REaction TArget Prioritization genome-scale modeling technique for selecting genetic targets

MOTIVATION: Metabolic engineering is rapidly evolving as a result of new advances in synthetic biology tools and automation platforms that enable high throughput strain construction, as well as the development of machine learning tools (ML) for biology. However, selecting genetic engineering targets that effectively guide the metabolic engineering process is still challenging. ML can provide predictive power for synthetic biology, but current technical limitations prevent the independent use of ML approaches without previous biological knowledge. RESULTS: Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale models for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing the production of a desired metabolite. This method can provide a list of desirable engineering targets that can be combined with current ML pipelines. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production, 50% of targets that experimentally improved taxadiene production in E. coli and ∼60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida, while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets. AVAILABILITY AND IMPLEMENTATION: FluxRETAP is implemented in python and released under the creative commons license. The implementation and code are freely available at: https://github.com/JBEI/FluxRETAP.

Czajka, Jeffrey J↗
NASA NTRS1990

Ocean feature recognition using genetic algorithms with fuzzy fitness functions (GA/F3)

A model for genetic algorithms with semantic nets is derived for which the relationships between concepts is depicted as a semantic net. An organism represents the manner in which objects in a scene are attached to concepts in the net. Predicates between object pairs are continuous valued truth functions in the form of an inverse exponential function (e sub beta lxl). 1:n relationships are combined via the fuzzy OR (Max (...)). Finally, predicates between pairs of concepts are resolved by taking the average of the combined predicate values of the objects attached to the concept at the tail of the arc representing the predicate in the semantic net. The method is illustrated by applying it to the identification of oceanic features in the North Atlantic.

Ankenbrandt, C. A.↗
NASA NTRS1994

A computational approach to the relationship between radiation induced double strand breaks and translocations

A theoretical framework is presented which provides a quantitative analysis of radiation induced translocations between the ab1 oncogene on CH9q34 and a breakpoint cluster region, bcr, on CH 22q11. Such translocations are associated frequently with chronic myelogenous leukemia. The theory is based on the assumption that incorrect or unfaithful rejoining of initial double strand breaks produced concurrently within the 200 kbp intron region upstream of the second abl exon, and the 16.5 kbp region between bcr exon 2 and exon 6 interact with each other, resulting in a fusion gene. for an x-ray dose of 100 Gy, there is good agreement between the theoretical estimate and the one available experimental result. The theory has been extended to provide dose response curves for these types of translocations. These curves are quadratic at low doses and become linear at high doses.

NASA Discipline Radiation Health↗
NASA NTRS1993

Three stages in the evolution of the genetic code

A diversification of the genetic code based on the number of codons available for the proteinous amino acids is established. Three groups of amino acids during evolution of the code are distinguished. On the basis of their chemical complexity those amino acids emerging later in a translation process are derived. Codon number and chemical complexity indicate that His, Phe, Tyr, Cys and either Lys or Asn were introduced in the second stage, whereas the number of codons alone gives evidence that Trp and Met were introduced in the third stage. The amino acids of stage 1 use purine-rich codons, while all the amino acids introduced in the second stage, in contrast, use pyrimidines in the third position of their codons. A low abundance of pyrimidines during early translation is derived. This assumption is supported by experiments on non-enzymatic replication and interactions of hairpin loops with a complementary strand. A back extrapolation concludes a high purine content of the first nucleic acids, which gradually decreased during their evolution. Amino acids independently available from prebiotic synthesis were thus correlated to purine-rich codons. Implications on the prebiotic replication are discussed also in the light of recent codon usage data.

Review↗
DOE OSTI2026

Knowledge-guided learning with curated prior genetic biomarkers for robust model interpretation

Abstract Motivation Knowledge-guided learning offers effective and robust model training strategies in data-scarce settings by incorporating established domain knowledge, thereby enhancing generalization, robustness, and interpretability. By contrast, conventional deep learning approaches rely purely on data-driven learning, which can limit robust model interpretability, particularly in high-dimensional settings with limited size samples. In computational biology, knowledge-guided learning has primarily leveraged network- and structural-based knowledge, leading to biologically interpretable representations and enhanced predictive performance compared to conventional approaches. However, curated biomarkers, one of the most accessible forms of biological knowledge, remain largely unexplored within knowledge-guided paradigms. Results In this study, we propose a model-agnostic training paradigm, Biomarker-driven Explainable Prior-guided Learning (BioExPL), that can be applied to any neural networks that incorporates curated prior knowledge. BioExPL enforces neural networks to reflect curated biomarker priors in their latent representations through a novel knowledge-alignment loss. BioExPL consistently demonstrated significantly improved predictive performance and enhanced model interpretability with minimized computational overhead in simulation studies and intensive experiments on multiple cancer datasets. BioExPL not only integrates prior curated knowledge into the model but also accurately identifies unknown associated signals additionally. BioExPL is model-agnostic and domain-independent, enabling its integration into diverse neural network architectures. Availability and implementation The open-source is publicly available at: https://github.com/datax-lab/BioExPL.

Baek, Beomsu [Department of Computer Science, Univ↗
NASA NTRS2002

Genetic predisposition to low bone mass is paralleled by an enhanced sensitivity to signals anabolic to the skeleton

The structure of the adult skeleton is determined, in large part, by its genome. Whether genetic variations may influence the effectiveness of interventions to combat skeletal diseases remains unknown. The differential response of trabecular bone to an anabolic (low-level mechanical vibration) and a catabolic (disuse) mechanical stimulus were evaluated in three strains of adult mice. In low bone-mineral-density C57BL/6J mice, the low-level mechanical signal caused significantly larger bone formation rates (BFR) in the proximal tibia, but the removal of functional weight bearing did not significantly alter BFR. In mid-density BALB/cByJ mice, mechanical stimulation also increased BFR, whereas disuse significantly decreased BFR. In contrast, neither anabolic nor catabolic mechanical signals influenced any index of bone formation in high-density C3H/HeJ mice. Together, data from this study indicate that the sensitivity of trabecular tissue to both anabolic and catabolic stimuli is influenced by the genome. Extrapolated to humans, these results may explain in part why prophylaxes for low bone mass are not universally effective, yet also indicate that there may be a genotypic indication of people who are at reduced risk of suffering from bone loss.

Non-NASA Center↗