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t an algorithm for summarizing the metric resource requirements of an abstract activity based on the resource usages of its potential refinements.
This approach provides the agent with a causal structure, the spreading activation network, relating goals to the actions that can achieve those goals. This enables the agent to select actions relative to the goal priorities.
Topics covered include: Improved Instrument for Detecting Water and Ice in Soil; Real-Time Detection of Dust Devils from Pressure Readings; Determining Surface Roughness in Urban Areas Using Lidar Data; DSN Data Visualization Suite; Hamming and Accumulator Codes Concatenated with MPSK or QAM; Wide-Angle-Scanning Reflectarray Antennas Actuated by MEMS; Biasable Subharmonic Membrane Mixer for 520 to 600 GHz; Hardware Implementation of Serially Concatenated PPM Decoder; Symbolic Processing Combined with Model-Based Reasoning; Presentation Extensions of the SOAP; Spreadsheets for Analyzing and Optimizing Space Missions; Processing Ocean Images to Detect Large Drift Nets; Alternative Packaging for Back-Illuminated Imagers; Diamond Machining of an Off-Axis Biconic Aspherical Mirror; Laser Ablation Increases PEM/Catalyst Interfacial Area; Damage Detection and Self-Repair in Inflatable/Deployable Structures; Polyimide/Glass Composite High-Temperature Insulation; Nanocomposite Strain Gauges Having Small TCRs; Quick-Connect Windowed Non-Stick Penetrator Tips for Rapid Sampling; Modeling Unsteady Cavitation and Dynamic Loads in Turbopumps; Continuous-Flow System Produces Medical-Grade Water; Discrimination of Spore-Forming Bacilli Using spoIVA; nBn Infrared Detector Containing Graded Absorption Layer; Atomic References for Measuring Small Accelerations; Ultra-Broad-Band Optical Parametric Amplifier or Oscillator; Particle-Image Velocimeter Having Large Depth of Field; Enhancing SERS by Means of Supramolecular Charge Transfer; Improving 3D Wavelet-Based Compression of Hyperspectral Images; Improved Signal Chains for Readout of CMOS Imagers; SOI CMOS Imager with Suppression of Cross-Talk; Error-Rate Bounds for Coded PPM on a Poisson Channel; Biomorphic Multi-Agent Architecture for Persistent Computing; and Using Covariance Analysis to Assess Pointing Performance.
A family of fluorescent dye molecules has been developed for use in on-off fluorescence detection of specific chemicals. By themselves, these molecules do not fluoresce. However, when exposed to certain chemical analytes in liquid or vapor forms, they do fluoresce (see figure). These compounds are amenable to fixation on or in a variety of substrates for use in fluorescence-based detection devices: they can be chemically modified to anchor them to porous or non-porous solid supports or can be incorporated into polymer films. Potential applications for these compounds include detection of chemical warfare agents, sensing of acidity or alkalinity, and fluorescent tagging of proteins in pharmaceutical research and development. These molecules could also be exploited for use as two-photon materials for photodynamic therapy in the treatment of certain cancers and other diseases. A molecule in this family consists of a fluorescent core (such as an anthracene or pyrene) attached to two end groups that, when the dye is excited by absorption of light, transfer an electron to the core, thereby quenching the fluorescence. The end groups can be engineered so that they react chemically with certain analytes. Upon reaction, electrons on the end groups are no longer available for transfer to the core and, consequently, the fluorescence from the core is no longer quenched. The chemoselectivity of these molecules can be changed by changing the end groups. For example, aniline end groups afford a capability for sensing acids or acid halides (including those contained in chemical warfare agents). Pyridine or bipyridyl end groups would enable sensing of metal ions. Other chemicals that can be selectively detected through suitable choice of end groups include glucose and proteins. Moreover, the fluorescent cores can be changed to alter light-absorption and -emission characteristics: anthracene cores fluoresce at wavelengths around 500 nm, whereas perylene cores absorb and emit at wavelengths of about 600 nm.
Changes in surface albedo represent one of the main forcing agents that can counteract, to some extent, the positive forcing from increasing greenhouse gas concentrations. Here, we report on enhanced ocean reflectance from ship wakes over the Pacific Ocean near the California coast, where we determined, based on airborne radiation measurements that ship wakes can increase reflected sunlight by more than 100%. We assessed the importance of this increase to climate forcing, where we estimated the global radiative forcing of ship wakes to be -0.00014 plus or minus 53% Watts per square meter assuming a global distribution of 32331 ships of size of greater than or equal to 100000 gross tonnage. The forcing is smaller than the forcing of aircraft contrails (-0.007 to +0.02 Watts per square meter), but considering that the global shipping fleet has rapidly grown in the last five decades and this trend is likely to continue because of the need of more inter-continental transportation as a result of economic globalization, we argue that the radiative forcing of wakes is expected to be increasingly important especially in harbors and coastal regions.
The influence of preannealing treatments on the polymorphic crystallization of lithium disilicate glasses is examined. As expected, glasses heated at different rates through the temperature range where there is significant nucleation develop widely different numbers of nuclei. This can dramatically influence the stability and transformation characteristics of the annealed glass. Non-isothermal differential scanning calorimetry (DSC) and differential thermal analysis (DTA) measurements are demonstrated to be useful to probe the nucleation behavior. The first systematic investigations of particle size effects on the non-isothermal transformation behavior are presented and discussed. Based on DTA and microscopy experiments, we show that small particles of lithium disilicate glasses crystallize primarily by surface crystallization. The relative importance of surface versus volume crystallization is examined by varying particle size, by introducing nucleating agents and by exposing glasses to atmospheres of different water content. These data are analyzed quantitatively using a numerical model developed in a second paper following in this volume.
An error budget is a commonly used tool in design of complex aerospace systems. It represents system performance requirements in terms of allowable errors and flows these down through a hierarchical structure to lower assemblies and components. The requirements may simply be 'allocated' based upon heuristics or experience, or they may be designed through use of physics-based models. This paper presents a basis for developing an error budget for models of the system, as opposed to the system itself. The need for model error budgets arises when system models are a principle design agent as is increasingly more common for poorly testable high performance space systems.
The maritime environment poses a number of challenges for autonomous operation of surface boats. Among these challenges are the highly dynamic nature of the environment, the onboard sensing and reasoning requirements for obeying the navigational rules of the road, and the need for robust day/night hazard detection and avoidance. Development of full mission level autonomy entails addressing these challenges, coupled with inference of the tactical and strategic intent of possibly adversarial vehicles in the surrounding environment. This paper introduces PACIFIC (Process Algebra Capture of Intent From Information Content), an onboard system based on formal process algebras that is capable of extracting actions/activities from sensory inputs and reasoning within a mission context to ensure proper responses. PACIFIC is part of the Behavior Engine in CARACaS (Cognitive Architecture for Robotic Agent Command and Sensing), a system that is currently running on a number of U.S. Navy unmanned surface and underwater vehicles. Results from a series of experimental studies that demonstrate the effectiveness of the system are also presented.
Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.
Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.
Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.
A candidate scrubber media, alpha-ketoglutaric acid (aKGA) adsorbed onto a silica-based substrate was examined as a potential alternative to the hydrazine-family hypergolic fuel neutralization techniques currently utilized at NASA/Kennedy Space Center (KSC). Helvenson et. al. has indicated that aKGA will react with hydrazines to produce non-hazardous, possibly biodegradable products. Furthermore, the authors have previously tested and demonstrated the use of aKGA aqueous solutions as a replacement neutralizing agent for citric acid, which is currently used as a scrubbing agent in liquid scrubbers at KSC. Specific properties examined include reaction efficiency, the loading capacity of aKGA onto various silica substrates, and the comparison of aKGA media performance to that of the citric acid vapor scrubber systems at KSC and a commercial vapor scrubber media. Preliminary investigations showed hydrophobic aerogel particles to be an ideal substrate for the deposition of the aKGA. Current studies have shown that the laboratory produced aKGA-Aerogel absorbent media are more efficient and cost effective than a commercially available fixed bed scrubber media, although much less cost effective than liquid-based citric acid scrubbers (although possibly safer and less labor intensive). A comparison of all three alternative scrubber technologies (liquid aKGA, solid-phase aKGA, and commercially available sorbent materials) is given considering both hypergolic neutralization capabilities and relative costs (as compared to the current citric acid scrubbing technology in use at NASA/KSC).
In this report, we present a robotic platform, the Shapeshifter, that allows multi-domain and redundant mobility on Saturn's moon Titan - and potentially other bodies with atmospheres. The Shapeshifter is a collection of simple and a affordable robotic units, called Cobots, comparable to personal palm-size quadcopters. By attaching and detaching with each other, multiple Cobots can shape-shift into novel structures, capable of (a) rolling on a at surface, to increase the traverse range, (b) flying in a flight array formation, and (c) swimming on or under liquid. A ground station, called the Home-base, complements the robotic platform, hosting science instrumentation and providing power to recharge the batteries of the Cobots. Our Phase I study had the objective of providing an initial assessment of the feasibility of the proposed robotic platform architecture, and in particular (a) to characterize the expected science return of a mission to the Sotra-Patera region on Titan; (b) to verify the mechanical and algorithmic feasibility of building a multi-agent platform capable of flying, docking, rolling and un-docking; (c) to evaluate the increased range and efficiency of rolling on Titan w.r.t to flying; (d) to define a case-study of a mission for the exploration of the cryovolcano Sotra-Patera on Titan, whose expected variety of geological features challenges conventional mobility platforms.
A method for accurately determining urinary tract infections in man is introduced. The method is based on adenosine triphosphate (ATP) concentration in urine samples after removing nonbacterial ATP. Adenosine triphosphate concentration is measured from the bioluminescent reaction of luciferase when mixed with ATP. An examination was also made of the effectiveness of rupturing agents on monkey kidney cells Candia albicans, a Rhodotorula species, and a Streptomyces species in determining whether these cells could contribute ATP to the bacterial ATP value of a urine sample.
Tests were conducted on Wistar rats by using 3 control choleretic agents: 1-phenyl-1-hydroxy n-pentane, dehydrocholic acid, and phenyl-dimethylacetic acid. The effects of these agents were compared in different experimental conditions. The comparative study of choleretic agents in anesthetized rats, in restrained and unrestrained rats, with or without compensation for biliary loss by the biliary secretion of restrained or unrestrained rats does not show, in systematic pharmecodynamic investigations, an obvious superiority over the methods based on the simple technique.
Single walled carbon nanotubes represent the future of structural aerospace vehicle systems due to their unparalleled strength characteristics and demonstrated multifunctionality. This multifunctionality rises from the CNT's unique capabilities for both metallic and semiconducting electron transport, electron spin polarizability, and band gap modulation under strain. By incorporating the use of electric field alignment and various lithography techniques, a single wall carbon nanotube (SWNT) test bed for measurement of conductivity/strain relationships has been developed. Nanotubes are deposited at specified locations through dielectrophoresis. The circuit is designed such that the central, current carrying section of the nanotube is exposed to enable atomic force microscopy and manipulation in situ while the transport properties of the junction are monitored. By applying this methodology to sensor development a flexible single wall carbon nanotube (SWNT) based strain sensitive device has been developed. Studies of tensile testing of the flexible SWNT device vs conductivity are also presented, demonstrating the feasibility of using single walled HiPCO (high-pressure carbon monoxide) carbon nanotubes as strain sensing agents in a multi-functional materials system.
A new class polyimide and polyimide precursors based on diaryl oxyalkylene diamines, such as 1,3-bis[4-aminophenoxy]-2,2-dimethyl propane, a process for their preparation and their use as the continuous phase for the manufacture of composites and composite laminates reinforced by reinforcing agents such as carbon fibers, Kevlar.TM., and other similar high strength reinforcing agents. The polyimides and molecular composites obtained from the diamines according to the invention show thermoplastic properties, excellent flex fatigue and fracture resistance, and excellent thermal and oxidative stability.
This study examined the feasibility of repeated self-administration of a newly developed battery of mental acuity tests. Researchers developed this battery to be used to screen the fitness for duty of persons in at-risk occupations (astronauts, race car drivers), or those who may be exposed to environmental stress, toxic agents, or disease. The menu under study contained cognitive and motor tests implemented on a portable microcomputer including: a five-test core battery, lasting six minutes, which had demonstrable reliabilities and stability from several previous repeated-measures studies, and also 13 new tests, lasting 42 minutes, which had appeared in other batteries but had not yet been evaluated for repeated-measures implementation in this medium. Sixteen subjects self-administered the battery over 10 repeated sessions. The hardware performed well throughout the study and the tests appeared to be easily self-administered. Stabilities and reliabilities of the test from the core battery were comparable to those obtained previously under more controlled experimental conditions. Analyses of metric properties of the remaining 13 tests produced eight additional tests with satisfactory properties. Although the average retest reliability was high, cross-correlations between tests were low, indicating factorial richness. The menu can be used to form batteries of flexible total testing time which are likely to tap different mental processes and functions.