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At least 163 records · Page 9

Dynamics of Quantum Adiabatic Evolution Algorithm for Number Partitioning

We have developed a general technique to study the dynamics of the quantum adiabatic evolution algorithm applied to random combinatorial optimization problems in the asymptotic limit of large problem size n. We use as an example the NP-complete Number Partitioning problem and map the algorithm dynamics to that of an auxiliary quantum spin glass system with the slowly varying Hamiltonian. We use a Green function method to obtain the adiabatic eigenstates and the minimum excitation gap. g min, = O(n 2(exp -n/2), corresponding to the exponential complexity of the algorithm for Number Partitioning. The key element of the analysis is the conditional energy distribution computed for the set of all spin configurations generated from a given (ancestor) configuration by simultaneous flipping of a fixed number of spins. For the problem in question this distribution is shown to depend on the ancestor spin configuration only via a certain parameter related to 'the energy of the configuration. As the result, the algorithm dynamics can be described in terms of one-dimensional quantum diffusion in the energy space. This effect provides a general limitation of a quantum adiabatic computation in random optimization problems. Analytical results are in agreement with the numerical simulation of the algorithm.

Smelyanskiy, V. N.↗

Plasma Enhanced Growth of Carbon Nanotubes For Ultrasensitive Biosensors

The multitude of considerations facing nanostructure growth and integration lends itself to combinatorial optimization approaches. Rapid optimization becomes even more important with wafer-scale growth and integration processes. Here we discuss methodology for developing plasma enhanced CVD growth techniques for achieving individual, vertically aligned carbon nanostructures that show excellent properties as ultrasensitive electrodes for nucleic acid detection. We utilize high throughput strategies for optimizing the upstream and downstream processing and integration of carbon nanotube electrodes as functional elements in various device types. An overview of ultrasensitive carbon nanotube based sensor arrays for electrochemical bio-sensing applications and the high throughput methodology utilized to combine novel electrode technology with conventional MEMS processing will be presented.

Cassell, Alan M.↗

Plasma Enhanced Growth of Carbon Nanotubes For Ultrasensitive Biosensors

The multitude of considerations facing nanostructure growth and integration lends itself to combinatorial optimization approaches. Rapid optimization becomes even more important with wafer-scale growth and integration processes. Here we discuss methodology for developing plasma enhanced CVD growth techniques for achieving individual, vertically aligned carbon nanostructures that show excellent properties as ultrasensitive electrodes for nucleic acid detection. We utilize high throughput strategies for optimizing the upstream and downstream processing and integration of carbon nanotube electrodes as functional elements in various device types. An overview of ultrasensitive carbon nanotube based sensor arrays for electrochemical biosensing applications and the high throughput methodology utilized to combine novel electrode technology with conventional MEMS processing will be presented.

Cassell, Alan M.↗

Flight Test of ASAC Aircraft Interior Noise Control System

A flight test is described in which an active structural/acoustic control system reduces turboprop induced interior noise on a Raytheon Aircraft Company 1900D airliner. Control inputs to 21 inertial force actuators were computed adaptively using a transform domain version of the multichannel filtered-X LMS algorithm to minimize the mean square response of 32 microphones. A combinatorial search algorithm was employed to optimize placement of the force actuators on the aircraft frame. Both single frequency and multi-frequency results are presented. Reductions of up to 15 dB were obtained at the blade passage frequency (BPF) during single frequency control tests. Simultaneous reductions of the BPF and next 2 harmonics of 10 dB, 2.5 dB and 3.0 dB, were obtained in a multi-frequency test.

Palumbo, Dan↗

Chance and necessity in the selection of nucleic acid catalysts

In Tom Stoppard's famous play [Rosencrantz and Guildenstern are Dead], the ill-fated heroes toss a coin 101 times. The first 100 times they do so the coin lands heads up. The chance of this happening is approximately 1 in 10(30), a sequence of events so rare that one might argue that it could only happen in such a delightful fiction. Similarly rare events, however, may underlie the origins of biological catalysis. What is the probability that an RNA, DNA, or protein molecule of a given random sequence will display a particular catalytic activity? The answer to this question determines whether a collection of such sequences, such as might result from prebiotic chemistry on the early earth, is extremely likely or unlikely to contain catalytically active molecules, and hence whether the origin of life itself is a virtually inevitable consequence of chemical laws or merely a bizarre fluke. The fact that a priori estimates of this probability, given by otherwise informed chemists and biologists, ranged from 10(-5) to 10(-50), inspired us to begin to address the question experimentally. As it turns out, the chance that a given random sequence RNA molecule will be able to catalyze an RNA polymerase-like phosphoryl transfer reaction is close to 1 in 10(13), rare enough, to be sure, but nevertheless in a range that is comfortably accessible by experiment. It is the purpose of this Account to describe the recent advances in combinatorial biochemistry that have made it possible for us to explore the abundance and diversity of catalysts existing in nucleic acid sequence space.

Review, Tutorial↗

Performance of Optimized Actuator and Sensor Arrays in an Active Noise Control System

Experiments have been conducted in NASA Langley s Acoustics and Dynamics Laboratory to determine the effectiveness of optimized actuator/sensor architectures and controller algorithms for active control of harmonic interior noise. Tests were conducted in a large scale fuselage model - a composite cylinder which simulates a commuter class aircraft fuselage with three sections of trim panel and a floor. Using an optimization technique based on the component transfer functions, combinations of 4 out of 8 piezoceramic actuators and 8 out of 462 microphone locations were evaluated against predicted performance. A combinatorial optimization technique call tabu search was employed to select the optimum transducer arrays. Three test frequencies represent the cases of a strong acoustic and strong structural response, a weak acoustic and strong structural response and a strong acoustic and weak structural response. Noise reduction was obtained using a Time Averaged/Gradient Descent (TAGD) controller. Results indicate that the optimization technique successfully predicted best and worst case performance. An enhancement of the TAGD control algorithm was also evaluated. The principal components of the actuator/sensor transfer functions were used in the PC-TAGD controller. The principal components are shown to be independent of each other while providing control as effective as the standard TAGD.

Palumbo, D. L.↗

Cardiac tissue enriched factors serum response factor and GATA-4 are mutual coregulators

Combinatorial interaction among cardiac tissue-restricted enriched transcription factors may facilitate the expression of cardiac tissue-restricted genes. Here we show that the MADS box factor serum response factor (SRF) cooperates with the zinc finger protein GATA-4 to synergistically activate numerous myogenic and nonmyogenic serum response element (SRE)-dependent promoters in CV1 fibroblasts. In the absence of GATA binding sites, synergistic activation depends on binding of SRF to the proximal CArG box sequence in the cardiac and skeletal alpha-actin promoter. GATA-4's C-terminal activation domain is obligatory for synergistic coactivation with SRF, and its N-terminal domain and first zinc finger are inhibitory. SRF and GATA-4 physically associate both in vivo and in vitro through their MADS box and the second zinc finger domains as determined by protein A pullout assays and by in vivo one-hybrid transfection assays using Gal4 fusion proteins. Other cardiovascular tissue-restricted GATA factors, such as GATA-5 and GATA-6, were equivalent to GATA-4 in coactivating SRE-dependent targets. Thus, interaction between the MADS box and C4 zinc finger proteins, a novel regulatory paradigm, mediates activation of SRF-dependent gene expression.

NASA Discipline Musculoskeletal↗

Constructing high complexity synthetic libraries of long ORFs using in vitro selection

We present a method that can significantly increase the complexity of protein libraries used for in vitro or in vivo protein selection experiments. Protein libraries are often encoded by chemically synthesized DNA, in which part of the open reading frame is randomized. There are, however, major obstacles associated with the chemical synthesis of long open reading frames, especially those containing random segments. Insertions and deletions that occur during chemical synthesis cause frameshifts, and stop codons in the random region will cause premature termination. These problems can together greatly reduce the number of full-length synthetic genes in the library. We describe a strategy in which smaller segments of the synthetic open reading frame are selected in vitro using mRNA display for the absence of frameshifts and stop codons. These smaller segments are then ligated together to form combinatorial libraries of long uninterrupted open reading frames. This process can increase the number of full-length open reading frames in libraries by up to two orders of magnitude, resulting in protein libraries with complexities of greater than 10(13). We have used this methodology to generate three types of displayed protein library: a completely random sequence library, a library of concatemerized oligopeptide cassettes with a propensity for forming amphipathic alpha-helical or beta-strand structures, and a library based on one of the most common enzymatic scaffolds, the alpha/beta (TIM) barrel. Copyright 2000 Academic Press.

Non-NASA Center↗

Magnetic microspheres and tissue model studies for therapeutic applications

The use of magnetic fluids and magnetic particles in combinatorial hyperthermia therapy for cancer treatment is reviewed. The investigation approach adopted for producing thermoregulating particles and tissue model studies for studying particle retention and heating characteristics is discussed.

Review↗

Development of the Architectural Simulation Model for Future Launch Systems and its Application to an Existing Launch Fleet

A significant portion of lifecycle costs for launch vehicles are generated during the operations phase. Research indicates that operations costs can account for a large percentage of the total life-cycle costs of reusable space transportation systems. These costs are largely determined by decisions made early during conceptual design. Therefore, operational considerations are an important part of vehicle design and concept analysis process that needs to be modeled and studied early in the design phase. However, this is a difficult and challenging task due to uncertainties of operations definitions, the dynamic and combinatorial nature of the processes, and lack of analytical models and the scarcity of historical data during the conceptual design phase. Ultimately, NASA would like to know the best mix of launch vehicle concepts that would meet the missions launch dates at the minimum cost. To answer this question, we first need to develop a model to estimate the total cost, including the operational cost, to accomplish this set of missions. In this project, we have developed and implemented a discrete-event simulation model using ARENA (a simulation modeling environment) to determine this cost assessment. Discrete-event simulation is widely used in modeling complex systems, including transportation systems, due to its flexibility, and ability to capture the dynamics of the system. The simulation model accepts manifest inputs including the set of missions that need to be accomplished over a period of time, the clients (e.g., NASA or DoD) who wish to transport the payload to space, the payload weights, and their destinations (e.g., International Space Station, LEO, or GEO). A user of the simulation model can define an architecture of reusable or expendable launch vehicles to achieve these missions. Launch vehicles may belong to different families where each family may have it own set of resources, processing times, and cost factors. The goal is to capture the required resource levels of the major launch elements and their required facilities. The model s output can show whether or not a certain architecture of vehicles can meet the launch dates, and if not, how much the delay cost would be. It will also produce aggregate figures of missions cost based on element procurement cost, processing cost, cargo integration cost, delay cost, and mission support cost. One of the most useful features of this model is that it is stochastic where it accepts statistical distributions to represent the processing times mimicking the stochastic nature of real systems.

Rabadi, Ghaith↗

Overall Traveling-Wave-Tube Efficiency Improved By Optimized Multistage Depressed Collector Design

Depressed Collector Design The microwave traveling wave tube (TWT) is used widely for space communications and high-power airborne transmitting sources. One of the most important features in designing a TWT is overall efficiency. Yet, overall TWT efficiency is strongly dependent on the efficiency of the electron beam collector, particularly for high values of collector efficiency. For these reasons, the NASA Glenn Research Center developed an optimization algorithm based on simulated annealing to quickly design highly efficient multistage depressed collectors (MDC's). Simulated annealing is a strategy for solving highly nonlinear combinatorial optimization problems. Its major advantage over other methods is its ability to avoid becoming trapped in local minima. Simulated annealing is based on an analogy to statistical thermodynamics, specifically the physical process of annealing: heating a material to a temperature that permits many atomic rearrangements and then cooling it carefully and slowly, until it freezes into a strong, minimum-energy crystalline structure. This minimum energy crystal corresponds to the optimal solution of a mathematical optimization problem. The TWT used as a baseline for optimization was the 32-GHz, 10-W, helical TWT developed for the Cassini mission to Saturn. The method of collector analysis and design used was a 2-1/2-dimensional computational procedure that employs two types of codes, a large signal analysis code and an electron trajectory code. The large signal analysis code produces the spatial, energetic, and temporal distributions of the spent beam entering the MDC. An electron trajectory code uses the resultant data to perform the actual collector analysis. The MDC was optimized for maximum MDC efficiency and minimum final kinetic energy of all collected electrons (to reduce heat transfer). The preceding figure shows the geometric and electrical configuration of an optimized collector with an efficiency of 93.8 percent. The results show the improvement in collector efficiency from 89.7 to 93.8 percent, resulting in an increase of three overall efficiency points. In addition, the time to design a highly efficient MDC was reduced from a month to a few days. All work was done in-house at Glenn for the High Rate Data Delivery Program. Future plans include optimizing the MDC and TWT interaction circuit in tandem to further improve overall TWT efficiency.

Vaden, Karl R.↗

A Method for Aircraft Concept Selection Using Multicriteria Interactive Genetic Algorithms

The problem of aircraft concept selection has become increasingly difficult in recent years as a result of a change from performance as the primary evaluation criteria of aircraft concepts to the current situation in which environmental effects, economics, and aesthetics must also be evaluated and considered in the earliest stages of the decision-making process. This has prompted a shift from design using historical data regression techniques for metric prediction to the use of physics-based analysis tools that are capable of analyzing designs outside of the historical database. The use of optimization methods with these physics-based tools, however, has proven difficult because of the tendency of optimizers to exploit assumptions present in the models and drive the design towards a solution which, while promising to the computer, may be infeasible due to factors not considered by the computer codes. In addition to this difficulty, the number of discrete options available at this stage may be unmanageable due to the combinatorial nature of the concept selection problem, leading the analyst to arbitrarily choose a sub-optimum baseline vehicle. These concept decisions such as the type of control surface scheme to use, though extremely important, are frequently made without sufficient understanding of their impact on the important system metrics because of a lack of computational resources or analysis tools. This paper describes a hybrid subjective/quantitative optimization method and its application to the concept selection of a Small Supersonic Transport. The method uses Genetic Algorithms to operate on a population of designs and promote improvement by varying more than sixty parameters governing the vehicle geometry, mission, and requirements. In addition to using computer codes for evaluation of quantitative criteria such as gross weight, expert input is also considered to account for criteria such as aeroelasticity or manufacturability which may be impossible or too computationally expensive to consider explicitly in the analysis. Results indicate that concepts resulting from the use of this method represent designs which are promising to both the computer and the analyst, and that a mapping between concepts and requirements that would not otherwise be apparent is revealed.

Buonanno, Michael↗

Update On the Status of the FLUKA Monte Carlo Transport Code*

The FLUKA Monte Carlo transport code is a well-known simulation tool in High Energy Physics. FLUKA is a dynamic tool in the sense that it is being continually updated and improved by the authors. We review the progress achieved since the last CHEP Conference on the physics models, some technical improvements to the code and some recent applications. From the point of view of the physics, improvements have been made with the extension of PEANUT to higher energies for p, n, pi, pbar/nbar and for nbars down to the lowest energies, the addition of the online capability to evolve radioactive products and get subsequent dose rates, upgrading of the treatment of EM interactions with the elimination of the need to separately prepare preprocessed files. A new coherent photon scattering model, an updated treatment of the photo-electric effect, an improved pair production model, new photon cross sections from the LLNL Cullen database have been implemented. In the field of nucleus-- nucleus interactions the electromagnetic dissociation of heavy ions has been added along with the extension of the interaction models for some nuclide pairs to energies below 100 MeV/A using the BME approach, as well as the development of an improved QMD model for intermediate energies. Both DPMJET 2.53 and 3 remain available along with rQMD 2.4 for heavy ion interactions above 100 MeV/A. Technical improvements include the ability to use parentheses in setting up the combinatorial geometry, the introduction of pre-processor directives in the input stream. a new random number generator with full 64 bit randomness, new routines for mathematical special functions (adapted from SLATEC). Finally, work is progressing on the deployment of a user-friendly GUI input interface as well as a CAD-like geometry creation and visualization tool. On the application front, FLUKA has been used to extensively evaluate the potential space radiation effects on astronauts for future deep space missions, the activation dose for beam target areas, dose calculations for radiation therapy as well as being adapted for use in the simulation of events in the ALICE detector at the LHC.

Ferrari, A.↗

The four-gate transistor

The four-gate transistor or G4-FET combines MOSFET and JFET principles in a single SOI device. Experimental results reveal that each gate can modulate the drain current. Numerical simulations are presented to clarify the mechanisms of operation. The new device shows enhanced functionality, due to the combinatorial action of the four gates, and opens rather revolutionary applications.

neuro-prosthetic devices cortical signals↗

Some Mathematical Problems of Satellite Networks

Economic forces and technology development have made low-earth-orbit satellite constellations extremely attractive to the emergent personal communications industry. These constellations range from 2 to nearly 1000 satellites. Even though none of the constellations are as yet completely deployed, design on second generation constellations have already begun. The satellite coverage and network links provide some interesting mathematical problems. We examine some of the geometric and combinatorial problems associated with these networks.

Satellite Networks↗