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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Evolution of catalytic function

An RNA-based evolution system was constructed in the laboratory and used to develop RNA enzymes with novel catalytic function. By controlling the nature of the catalytic task that the molecules must perform in order to survive, it is possible to direct the evolving population toward the expression of some desired catalytic behavior. More recently, this system has been coupled to an in vitro translation procedure, raising the possibility of evolving protein enzymes in the laboratory to produce novel proteins with desired catalytic properties. The aim of this line of research is to reduce darwinian evolution, the fundamental process of biology, to a laboratory procedure that can be made to operate in the service of organic synthesis.

NASA Program Exobiology↗
NASA NTRS1998

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

Liang, Shoudan↗
NASA NTRS1993

Structure and function of the homeotic gene complex (HOM-C) in the beetle, Tribolium castaneum

The powerful combination of genetic, developmental and molecular approaches possible with the fruit fly, Drosophila melanogaster, has led to a profound understanding of the genetic control of early developmental events. However, Drosophila is a highly specialized long germ insect, and the mechanisms controlling its early development may not be typical of insects or Arthropods in general. The beetle, Tribolium castaneum, offers a similar opportunity to integrate high resolution genetic analysis with the developmental/molecular approaches currently used in other organisms. Early results document significant differences between insect orders in the functions of genes responsible for establishing developmental commitments.

NASA Program NSCORT↗
NASA NTRS2006

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

Rai, Man Mohan↗
NASA NTRS1992

On the nature of global classification

Molecular sequencing technology has brought biology into the era of global (universal) classification. Methodologically and philosophically, global classification differs significantly from traditional, local classification. The need for uniformity requires that higher level taxa be defined on the molecular level in terms of universally homologous functions. A global classification should reflect both principal dimensions of the evolutionary process: genealogical relationship and quality and extent of divergence within a group. The ultimate purpose of a global classification is not simply information storage and retrieval; such a system should also function as an heuristic representation of the evolutionary paradigm that exerts a directing influence on the course of biology. The global system envisioned allows paraphyletic taxa. To retain maximal phylogenetic information in these cases, minor notational amendments in existing taxonomic conventions should be adopted.

NASA Program Exobiology↗
NASA NTRSDate not supplied

From Source to Surface: An Investigation of Magmatic Lunar Volatiles

Lunar missions led by NASA discovered water ice on the Moon’s surface [1-3], revolutionizing views of the abundance, distribution, and potential sources of H2O and other volatiles. Volatiles play an important role in affecting the rheological properties of minerals and melts and influencing magma eruption processes. In order to determine the indigenous volatile inventory of the Moon, it is vital to identify the magmatic and secondary processes that may have affected the volatile contents in lunar minerals [4]. As part of the Apollo Next Generation Sample Analysis (ANGSA) program we are investigating the petrogenesis of a set of four Apollo lunar basalts collected from the rim of Steno Crater 71035, 71037, 71055, and specially curated sample 71036. Our team is studying the petrology in 2D and 3D (this work), chronology (Pomeroy et al., LPSC 2022), oxidation state of sulfur in apatite (Brounce et al., LPSC 2022), and volatile inventory of the sample set in order to understand the age and genetic relationships among the basalts, their magma ascent conditions and eruptive signatures, and their degassing and surface histories. Here we present the first detailed study of the 2D and 3D mineralogy, textures, 3D vesiculation, and chemistry of these basalts to shed light on their magmatic, volcanic, and post-eruptive histories. Note: Extended abstract on document.

Z. E. Wilbur↗
NASA NTRS2016

Developing Personalized Sensorimotor Adaptability Countermeasures for Spaceflight

Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. In this paper we will be presenting results from our ground-based study that show how behavioral, brain imaging and genomic data may be used to predict individual differences in sensorimotor adaptability to novel sensorimotor environments. This approach will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive capacity, brain structure, functional capacities, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.

Mulavara, A. P.↗
NASA NTRS2018

Development and Application of a Tool for Optimizing Composite Matrix Viscoplastic Material Parameters

This document describes a recently developed analysis tool that enhances the resident capabilities of the Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) and its application. MAC/GMC is a composite material and laminate analysis software package developed at NASA Glenn Research Center. The primary focus of the current effort is to provide a graphical user interface (GUI) capability that helps users optimize highly nonlinear viscoplastic constitutive law parameters by fitting experimentally observed/measured stress-strain responses under various thermo-mechanical conditions for braided composites. The tool has been developed utilizing the MATrix LABoratory (MATLAB) (The Mathworks, Inc., Natick, MA) programming language. Illustrative examples shown are for a specific braided composite system wherein the matrix viscoplastic behavior is represented by a constitutive law described by seven parameters. The tool is general enough to fit any number of experimentally observed stress-strain responses of the material. The number of parameters to be optimized, as well as the importance given to each stress-strain response, are user choice. Three different optimization algorithms are included: (1) Optimization based on gradient method, (2) Genetic algorithm (GA) based optimization and (3) Particle Swarm Optimization (PSO). The user can mix and match the three algorithms. For example, one can start optimization with either 2 or 3 and then use the optimized solution to further fine tune with approach 1. The secondary focus of this paper is to demonstrate the application of this tool to optimize/calibrate parameters for a nonlinear viscoplastic matrix to predict stress-strain curves (for constituent and composite levels) at different rates, temperatures and/or loading conditions utilizing the Generalized Method of Cells. After preliminary validation of the tool through comparison with experimental results, a detailed virtual parametric study is presented wherein the combined effects of temperature and loading rate on the predicted response of a braided composite is investigated.

thermo-mechanical; MATLAB; GUI-Based Too↗
NASA NTRS1989

ECUT (Energy Conversion and Utilization Technologies) program: Biocatalysis project

The Annual Report presents the fiscal year (FY) 1988 research activities and accomplishments, for the Biocatalysis Project of the U.S. Department of Energy, Energy Conversion and Utilization Technologies (ECUT) Division. The ECUT Biocatalysis Project is managed by the Jet Propulsion Laboratory, California Institute of Technology. The Biocatalysis Project is a mission-oriented, applied research and exploratory development activity directed toward resolution of the major generic technical barriers that impede the development of biologically catalyzed commercial chemical production. The approach toward achieving project objectives involves an integrated participation of universities, industrial companies and government research laboratories. The Project's technical activities were organized into three work elements: (1) The Molecular Modeling and Applied Genetics work element includes research on modeling of biological systems, developing rigorous methods for the prediction of three-dimensional (tertiary) protein structure from the amino acid sequence (primary structure) for designing new biocatalysis, defining kinetic models of biocatalyst reactivity, and developing genetically engineered solutions to the generic technical barriers that preclude widespread application of biocatalysis. (2) The Bioprocess Engineering work element supports efforts in novel bioreactor concepts that are likely to lead to substantially higher levels of reactor productivity, product yields and lower separation energetics. Results of work within this work element will be used to establish the technical feasibility of critical bioprocess monitoring and control subsystems. (3) The Bioprocess Design and Assessment work element attempts to develop procedures (via user-friendly computer software) for assessing the energy-economics of biocatalyzed chemical production processes, and initiation of technology transfer for advanced bioprocesses.

Baresi, Larry↗
NASA NTRS1985

Photometric support for future astonomical research

The I.A.P.P.P. is described and how that organization can provide photometric support for future astronomical research projects such as the 1982-1984 eclipse of epsilon Aurigae discussed at this workshop. I.A.P.P.P., International Amateur-Professional Photoelectric Photometry, is an organization founded in Fairborn, Ohio by the authors in 1980. Its purpose is to encourage contact between amateur and professional astronomers interested in photoelectric photometry, for their mutual benefit and for the benefit of astronomical research. Aspects dealt with include instrumentation, electronics, computer hardware and software, observing techniques, data reduction, and observing programs. Starting with the June 1980 issue, I.A.P.P.P. has published the quarterly I.A.P.P.P. Communications. The Communications contain articles dealing with all the above aspects of photoelectric photometry, although it does not publish observational results as such. Photoelectric photometry obtained by amateurs is published in the same journals which publish photometry obtained by professionals.

Hall, D. S.↗
NASA NTRS1996

The August Krogh principle applies to plants

The Krogh principle refers to the use of a large number of animals to study the large number of physiological problems, rather than limiting study to a particular organism for all problems. There may be organisms that are more suited to study of a particular problem than others. This same principle applies to plants. The authors are concerned with the recent trend in plant biology of using Arabidopsis thaliana as the "organism of choice." Arabidopsis is an excellent organism for molecular genetic research, but other plants are superior models for other research areas of plant biology. The authors present examples of the successful use of the Krogh principle in plant cell biology research, emphasizing the particular characteristics of the selected research organisms that make them the appropriate choice.

NASA Discipline Plant Biology↗
NASA NTRS1993

HSP86 and HSP84 exhibit cellular specificity of expression and co-precipitate with an HSP70 family member in the murine testis

This study extends to the protein level our previous observations, which had established the stage and cellular specificity of expression of hsp86 and hsp84 in the murine testis in the absence of exogenous stress. Immunoblot analysis was used to demonstrate that HSP86 protein was present throughout testicular development and that its levels increased with the appearance of differentiating germ cells. HSP86 was most abundant in the germ cell population and was present at significantly lower levels in the somatic cells. By contrast, the HSP84 protein was detected in the somatic cells of the testis rather than in germ cells. The steady-state levels of HSP86 and HSP84 paralleled the pattern of the expression of their respective mRNAs, suggesting that regulation at the level of translation was not a major mechanism controlling hsp90 gene expression in testicular cells. Immunoprecipitation analysis revealed that a 70-kDa protein coprecipitated with the HSP86/HSP84 proteins in testicular homogenates. This protein was identified as an HSP70 family member by immunoblot analysis, suggesting that HSP70 and HSP90 family members interact in testicular cells.

NASA Discipline Number 40-20↗
NASA NTRS1995

Statistical and linguistic features of DNA sequences

We present evidence supporting the idea that the DNA sequence in genes containing noncoding regions is correlated, and that the correlation is remarkably long range--indeed, base pairs thousands of base pairs distant are correlated. We do not find such a long-range correlation in the coding regions of the gene. We resolve the problem of the "non-stationary" feature of the sequence of base pairs by applying a new algorithm called Detrended Fluctuation Analysis (DFA). We address the claim of Voss that there is no difference in the statistical properties of coding and noncoding regions of DNA by systematically applying the DFA algorithm, as well as standard FFT analysis, to all eukaryotic DNA sequences (33 301 coding and 29 453 noncoding) in the entire GenBank database. We describe a simple model to account for the presence of long-range power-law correlations which is based upon a generalization of the classic Levy walk. Finally, we describe briefly some recent work showing that the noncoding sequences have certain statistical features in common with natural languages. Specifically, we adapt to DNA the Zipf approach to analyzing linguistic texts, and the Shannon approach to quantifying the "redundancy" of a linguistic text in terms of a measurable entropy function. We suggest that noncoding regions in plants and invertebrates may display a smaller entropy and larger redundancy than coding regions, further supporting the possibility that noncoding regions of DNA may carry biological information.

Non-NASA Center↗
NASA NTRS2003

Quantitative analysis of bristle number in Drosophila mutants identifies genes involved in neural development

BACKGROUND: The identification of the function of all genes that contribute to specific biological processes and complex traits is one of the major challenges in the postgenomic era. One approach is to employ forward genetic screens in genetically tractable model organisms. In Drosophila melanogaster, P element-mediated insertional mutagenesis is a versatile tool for the dissection of molecular pathways, and there is an ongoing effort to tag every gene with a P element insertion. However, the vast majority of P element insertion lines are viable and fertile as homozygotes and do not exhibit obvious phenotypic defects, perhaps because of the tendency for P elements to insert 5' of transcription units. Quantitative genetic analysis of subtle effects of P element mutations that have been induced in an isogenic background may be a highly efficient method for functional genome annotation. RESULTS: Here, we have tested the efficacy of this strategy by assessing the extent to which screening for quantitative effects of P elements on sensory bristle number can identify genes affecting neural development. We find that such quantitative screens uncover an unusually large number of genes that are known to function in neural development, as well as genes with yet uncharacterized effects on neural development, and novel loci. CONCLUSIONS: Our findings establish the use of quantitative trait analysis for functional genome annotation through forward genetics. Similar analyses of quantitative effects of P element insertions will facilitate our understanding of the genes affecting many other complex traits in Drosophila.

Non-NASA Center↗
NASA NTRS2005

Expanding the Frontiers of Knowledge

So space is supremely hostile, but we know this. But when we ask what is the cost of human space missions, we need to consider as many contingencies as possible. This is important because we want to do more than send people on one-way trips, we want to be able to bring astronauts back. So if exploration is what really matters and not just pride of nation, then perhaps we should genetically engineer a version of ourselves that can survive the hostile environments of space. We've got cloning. We're inside the genome. Let s just do it. Well in fact, we ve done that already. Yes, we have emissaries of ourselves that survive the hazards of space; they re called robots. You don t have to feed them or bring them back, and they don t complain if you lose them in space. So my concern is if costs turn out to be what they have historically been and the time to execute programs lasts as long as it historically has, then I am not convinced that economic cycles and political cycles will allow such programs to survive if they do not satisfy one of these three criteria. The record of history tells us this, unless somehow you want to believe that we are different today than 6,000 years of our predecessors.

deGrasse Tyson, Neil↗
NASA NTRS2003

Software Helps Retrieve Information Relevant to the User

The Adaptive Indexing and Retrieval Agent (ARNIE) is a code library, designed to be used by an application program, that assists human users in retrieving desired information in a hypertext setting. Using ARNIE, the program implements a computational model for interactively learning what information each human user considers relevant in context. The model, called a "relevance network," incrementally adapts retrieved information to users individual profiles on the basis of feedback from the users regarding specific queries. The model also generalizes such knowledge for subsequent derivation of relevant references for similar queries and profiles, thereby, assisting users in filtering information by relevance. ARNIE thus enables users to categorize and share information of interest in various contexts. ARNIE encodes the relevance and structure of information in a neural network dynamically configured with a genetic algorithm. ARNIE maintains an internal database, wherein it saves associations, and from which it returns associated items in response to a query. A C++ compiler for a platform on which ARNIE will be utilized is necessary for creating the ARNIE library but is not necessary for the execution of the software.

Mathe, Natalie↗
NASA NTRS1984

A research program in determination of heavy metals in sediments and benthic species in relation to nuclear power plant operation

Heavy metals in the estuarine environment can be toxic to fish and shellfish early life history stages and concentrations build up to levels of concern in marketable shellfish. The present survey was begun just before startup in 1974 of the 1900 megawatt Calvert Cliffs Nuclear Power Plant on the Chesapeake Bay in order to assess and understand factors relating to heavy metal accumulation in estuarine biota. Oysters were collected in large numbers at test and reference sites in June 1974 to 77 and individually analyzed for copper and zinc. Oyster copper and zinc concentrations were correlated with salinity read at time of collection. The relationship of oyster age to metal concentration was examined with two sets of oysters of known age and genetic origin (laboratory spawned). Copper sorption by typical mid Bay sediments, and field studies on cadmium concentrations in sediments were examined.

Phelps, H. L.↗