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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Heavy-ion induced genetic changes and evolution processes

On Moon and Mars, there will be more galactic cosmic rays and higher radiation doses than on Earth. Our experimental studies showed that heavy ion radiation can effectively cause mutation and chromosome aberrations and that high Linear Energy Transfer (LET) heavy-ion induced mutants can be irreversible. Chromosome translocations and deletions are common in cells irradiated by heavy particles, and ionizing radiations are effective in causing hyperploidy. The importance of the genetic changes in the evolution of life is an interesting question. Through evolution, there is an increase of DNA content in cells from lower forms of life to higher organisms. The DNA content, however, reached a plateau in vertebrates. By increasing DNA content, there can be an increase of information in the cell. For a given DNA content, the quality of information can be changed by rearranging the DNA. Because radiation can cause hyperploidy, an increase of DNA content in cells, and can induce DNA rearrangement, it is likely that the evolution of life on Mars will be effected by its radiation environment. A simple analysis shows that the radiation level on Mars may cause a mutation frequency comparable to that of the spontaneous mutation rate on Earth. To the extent that mutation plays a role in adaptation, radiation alone on Mars may thus provide sufficient mutation for the evolution of life.

Yang, C. H.↗
NASA NTRS1994

Constrained minimization of smooth functions using a genetic algorithm

The use of genetic algorithms for minimization of differentiable functions that are subject to differentiable constraints is considered. A technique is demonstrated for converting the solution of the necessary conditions for a constrained minimum into an unconstrained function minimization. This technique is extended as a global constrained optimization algorithm. The theory is applied to calculating minimum-fuel ascent control settings for an energy state model of an aerospace plane.

Moerder, Daniel D.↗
NASA NTRS1994

Scheduling with genetic algorithms

In many domains, scheduling a sequence of jobs is an important function contributing to the overall efficiency of the operation. At Boeing, we develop schedules for many different domains, including assembly of military and commercial aircraft, weapons systems, and space vehicles. Boeing is under contract to develop scheduling systems for the Space Station Payload Planning System (PPS) and Payload Operations and Integration Center (POIC). These applications require that we respect certain sequencing restrictions among the jobs to be scheduled while at the same time assigning resources to the jobs. We call this general problem scheduling and resource allocation. Genetic algorithms (GA's) offer a search method that uses a population of solutions and benefits from intrinsic parallelism to search the problem space rapidly, producing near-optimal solutions. Good intermediate solutions are probabalistically recombined to produce better offspring (based upon some application specific measure of solution fitness, e.g., minimum flowtime, or schedule completeness). Also, at any point in the search, any intermediate solution can be accepted as a final solution; allowing the search to proceed longer usually produces a better solution while terminating the search at virtually any time may yield an acceptable solution. Many processes are constrained by restrictions of sequence among the individual jobs. For a specific job, other jobs must be completed beforehand. While there are obviously many other constraints on processes, it is these on which we focussed for this research: how to allocate crews to jobs while satisfying job precedence requirements and personnel, and tooling and fixture (or, more generally, resource) requirements.

Fennel, Theron R.↗
NASA NTRS1994

Three stages during 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 and a small codon number those amino acids emerging later in a translation process are derived. Both criteria 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 one use purines rich codons, thus purines have been retained in their third codon position. All the amino acids introduced in the second stage, in contrast, use pyrimidines in this codon position. A low abundance of pyrimidines during early translation is derived. This assumption is supported by experiments on non enzymatic replication and interactions of DNA 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 form prebiotic synthesis were thus correlated to purine rich codons. Conclusions on prebiotic replication are discussed also in the light of recent codon usage data.

Baumann, U.↗
NASA NTRS1996

DeMAID/GA USER'S GUIDE Design Manager's Aid for Intelligent Decomposition with a Genetic Algorithm

Many companies are looking for new tools and techniques to aid a design manager in making decisions that can reduce the time and cost of a design cycle. One tool that is available to aid in this decision making process is the Design Manager's Aid for Intelligent Decomposition (DeMAID). Since the initial release of DEMAID in 1989, numerous enhancements have been added to aid the design manager in saving both cost and time in a design cycle. The key enhancement is a genetic algorithm (GA) and the enhanced version is called DeMAID/GA. The GA orders the sequence of design processes to minimize the cost and time to converge to a solution. These enhancements as well as the existing features of the original version of DEMAID are described. Two sample problems are used to show how these enhancements can be applied to improve the design cycle. This report serves as a user's guide for DeMAID/GA.

Rogers, James L.↗
NASA NTRS1993

Sequence and Genetic Characterization of etrA, an fnr Analog that Regulates Anaerobic Respiration in Shewanella putrefaciens MR-1

An electron transport regulatory gene, etrA, has been isolated and characterized from the obligate respiratory bacterium Shewanella putrefaciens MR-l. The deduced amino acid sequence of etrA (EtrA) shows a high degree of identity to both the Fnr of Escherichia coli (73.6%) and the analogous protein (ANR) of Pseudomonas aeruginosa (50.8%). The four active cysteine residues of Fnr are conserved in EtrA, and the amino acid sequence of the DNA-binding domains of the two proteins are identical. Further, S.putrefaciens etrA is able to complement an fnr mutant of E.coli. In contrast to fnr, there is no recognizable Fnr box upstream of the etrA sequence. Gene replacement etr.A mutants of MR-1 were deficient in growth on nitrite, thiosulfate, sulfite, trimethylamine-N-oxide, dimethyl sulfoxide, Fe(III), and fumarate, suggesting that EtrA is involved in the regulation of the corresponding reductase genes. However, the mutants were all positive for reduction of and growth on nitrate and Mn(IV), indicating that EtrA is not involved in the regulation of these two systems. Southern blots of S.putrefaciens DNA with use of etrA as a probe revealed the expected etrA bands and a second set of hybridization signals whose genetic and functional properties remain to be determined.

Saffarini, Daad A.↗
NASA NTRS1996

Crystals of Serum Albumin for Use in Genetic Engineering and Rational Drug Design

Serum albumin crystal forms have been produced which exhibit superior x-ray diffraction quality. The crystals are produced from both recombinant and wild-type human serum albumin, canine, and baboon serum albumin and allow the performance of drug-binding studies as well as genetic engineering studies. The crystals are grown from solutions of polyethylene glycol or ammonium sulphate within prescribed limits during growth times from one to several weeks and include the following space groups: P2(sub 1), C2, P1.

Carter, Daniel C.↗
NASA NTRS1996

APS Conference on Understanding the Biological Clock: From Genetics to Physiology

The Conference was designed to take advantage of the fusion of two intellectually dominant but heretofore separate lines of clock research, vertebrate physiology and invertebrate and microbial genetics. The APS Conference attracted 251 scientists, 68 of whom were students. In addition to the excellent speaker program organized by Dunlap and Loros, the attendees also submitted 93 volunteer abstracts that were programmed in poster sessions. Thirty-four percent of the submitted abstracts were first authorized by a female student or scientist.

Frank, Martin↗
NASA NTRS1998

Genetic Regulatory Networks in Embryogenesis and Evolution

The article introduces a series of papers that were originally presented at a workshop titled Genetic Regulatory Network in Embryogenesis and Evaluation. Contents include the following: evolution of cleavage programs in relationship to axial specification and body plan evolution, changes in cell lineage specification elucidate evolutionary relations in spiralia, axial patterning in the leech: developmental mechanisms and evolutionary implications, hox genes in arthropod development and evolution, heterochronic genes in development and evolution, a common theme for LIM homeobox gene function across phylogeny, and mechanisms of specification in ascidian embryos.

Source record↗
NASA NTRS1999

Using a Genetic Algorithm to Model Broadband Regional Waveforms for Crustal Structure in the Western United States

In this study, we analyze regional seismograms to obtain the crustal structure in the eastern Great Basin and western Colorado plateau. Adopting a for- ward-modeling approach, we develop a genetic algorithm (GA) based parameter search technique to constrain the one-dimensional crustal structure in these regions. The data are broadband three-component seismograms recorded at the 1994-95 IRIS PASSCAL Colorado Plateau to Great Basin experiment (CPGB) stations and supplemented by data from U.S. National Seismic Network (USNSN) stations in Utah and Nevada. We use the southwestern Wyoming mine collapse event (M(sub b) = 5.2) that occurred on 3 February 1995 as the seismic source. We model the regional seismograms using a four-layer crustal model with constant layer parameters. Timing of teleseismic receiver functions at CPGB stations are added as an additional constraint in the modeling. GA allows us to efficiently search the model space. A carefully chosen fitness function and a windowing scheme are added to the algorithm to prevent search stagnation. The technique is tested with synthetic data, both with and without random Gaussian noise added to it. Several separate model searches are carried out to estimate the variability of the model parameters. The average Colorado plateau crustal structure is characterized by a 40-km-thick crust with velocity increases at depths of about 10 and 25 km and a fast lower crust while the Great Basin has approximately 35- km-thick crust and a 2.9-km-thick sedimentary layer.

Bhattacharyya, Joydeep↗
NASA NTRS1997

Simulating and Synthesizing Substructures Using Neural Network and Genetic Algorithms

The feasibility of simulating and synthesizing substructures by computational neural network models is illustrated by investigating a statically indeterminate beam, using both a 1-D and a 2-D plane stress modelling. The beam can be decomposed into two cantilevers with free-end loads. By training neural networks to simulate the cantilever responses to different loads, the original beam problem can be solved as a match-up between two subsystems under compatible interface conditions. The genetic algorithms are successfully used to solve the match-up problem. Simulated results are found in good agreement with the analytical or FEM solutions.

Liu, Youhua↗
NASA NTRS1999

Genetic Regulation of Charged Particle Mutagenesis in Human Cells

Our studies use a series of syngeneic, and where possible, isogenic human B-lymphoblastoid cell lines to assess the genetic factors that modulate susceptibility apoptosis and their impact on the mutagenic risks of low fluence exposures to 1 GeV Fe ions and 55 MeV protons. These ions are representative of the types of charged particle radiation that are of particular significance for human health in the space radiation environment. The model system employs cell lines derived from the male donor WIL-2. These cells have a single X chromosome and they are hemizygous for one mutation marker, hypoxanthine phosphoribosyltransferase (HPRT). TK6 and WTK1 cells were each derived from descendants of WIL-2 and were each selected as heterozygotes for a second mutation marker, the thymidine kinase (TK) gene located on chromosome 17q. The HPRT and TK loci can detect many different types of mutations, from single basepair substitutions up to large scale loss of heterozygosity (LOH). The single expressing copy of TK in the TK6 and WTKI cell lines is found on the same copy of chromosome 17, and this allele can be identified by a restriction fragment length polymorphism (RFLP) identified when high molecular weight DNA is digested by the SacI restriction endonuclease and hybridized against the cDNA probe for TK. A large series of polymorphic linked markers has been identified that span more than 60 cM of DNA (approx. 60 megabasepairs) and distinguish the copy of chromosome 17 bearing the initially active TK allele from the copy of chromosome 17 bearing the silent TK allele in both TK6 and WTKI cells. TK6 cells express normal p53 protein while WTKI cells express homozygous mutant p53. Expression of mutant p53 can increase susceptibility to x-ray-induced mutations. It's been suggested that the increased mutagenesis in p53 mutant cells might be due to reduced apoptosis.

Kronenberg, Amy↗
NASA NTRS2000

Experience with a Genetic Algorithm Implemented on a Multiprocessor Computer

Numerical experiments were conducted to find out the extent to which a Genetic Algorithm (GA) may benefit from a multiprocessor implementation, considering, on one hand, that analyses of individual designs in a population are independent of each other so that they may be executed concurrently on separate processors, and, on the other hand, that there are some operations in a GA that cannot be so distributed. The algorithm experimented with was based on a gaussian distribution rather than bit exchange in the GA reproductive mechanism, and the test case was a hub frame structure of up to 1080 design variables. The experimentation engaging up to 128 processors confirmed expectations of radical elapsed time reductions comparing to a conventional single processor implementation. It also demonstrated that the time spent in the non-distributable parts of the algorithm and the attendant cross-processor communication may have a very detrimental effect on the efficient utilization of the multiprocessor machine and on the number of processors that can be used effectively in a concurrent manner. Three techniques were devised and tested to mitigate that effect, resulting in efficiency increasing to exceed 99 percent.

Plassman, Gerald E.↗
NASA NTRS2000

Experience with a Genetic Algorithm Implemented on a Multiprocessor Computer

Numerical experiments were conducted to find out the extent to which a Genetic Algorithm (GA) may benefit from a multiprocessor implementation, considering, on one hand, that analyses of individual designs in a population are independent of each other so that they may be executed concurrently on separate processors, and, on the other hand, that there are some operations in a GA that cannot be so distributed. The algorithm experimented with was based on a gaussian distribution rather than bit exchange in the GA reproductive mechanism, and the test case was a hub frame structure of up to 1080 design variables. The experimentation engaging up to 128 processors confirmed expectations of radical elapsed time reductions comparing to a conventional single processor implementation. It also demonstrated that the time spent in the non-distributable parts of the algorithm and the attendant cross-processor communication may have a very detrimental effect on the efficient utilization of the multiprocessor machine and on the number of processors that can be used effectively in a concurrent manner. Three techniques were devised and tested to mitigate that effect, resulting in efficiency increasing to exceed 99 percent.

Plassman, Gerald E.↗
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 NTRS2000

Genetic Network Inference: From Co-Expression Clustering to Reverse Engineering

Advances in molecular biological, analytical, and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-duster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e., who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting, and bioengineering.

Dhaeseleer, Patrik↗
NASA NTRS2000

PDE Nozzle Optimization Using a Genetic Algorithm

Genetic algorithms, which simulate evolution in natural systems, have been used to find solutions to optimization problems that seem intractable to standard approaches. In this study, the feasibility of using a GA to find an optimum, fixed profile nozzle for a pulse detonation engine (PDE) is demonstrated. The objective was to maximize impulse during the detonation wave passage and blow-down phases of operation. Impulse of each profile variant was obtained by using the CFD code Mozart/2.0 to simulate the transient flow. After 7 generations, the method has identified a nozzle profile that certainly is a candidate for optimum solution. The constraints on the generality of this possible solution remain to be clarified.

Billings, Dana↗