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At least 451 records · Page 25

Combining Speed Information Across Space

We used speed discrimination tasks to measure the ability of observers to combine speed information from multiple stimuli distributed across space. We compared speed discrimination thresholds in a classical discrimination paradigm to those in an uncertainty/search paradigm. Thresholds were measured using a temporal two-interval forced-choice design. In the discrimination paradigm, the n gratings in each interval all moved at the same speed and observers were asked to choose the interval with the faster gratings. Discrimination thresholds for this paradigm decreased as the number of gratings increased. This decrease was not due to increasing the effective stimulus area as a control experiment that increased the area of a single grating did not show a similar improvement in thresholds. Adding independent speed noise to each of the n gratings caused thresholds to decrease at a rate similar to the original no-noise case, consistent with observers combining an independent sample of speed from each grating in both the added- and no-noise cases. In the search paradigm, observers were asked to choose the interval in which one of the n gratings moved faster. Thresholds in this case increased with the number of gratings, behavior traditionally attributed to an input bottleneck. However, results from the discrimination paradigm showed that the increase was not due to observers' inability to process these gratings. We have also shown that the opposite trends of the data in the two paradigms can be predicted by a decision theory model that combines independent samples of speed information across space. This demonstrates that models typically used in classical detection and discrimination paradigms are also applicable to search paradigms. As our model does not distinguish between samples in space and time, it predicts that discrimination performance should be the same regardless of whether the gratings are presented in two spatial intervals or two temporal intervals. Our last experiment largely confirmed this prediction.

Verghese, Preeti↗

Sputtering

This paper primarily reviews the potential of using the sputtering process as a deposition technique; however, the manufacturing and sputter etching aspects are also discussed. Since sputtering is not regulated by classical thermodynamics, new multicomponent materials can be developed in any possible chemical composition. The basic mechanism for dc and rf sputtering is described. Sputter-deposition is described in terms of the unique advantageous features it offers such as versatility, momentum transfer, stoichiometry, sputter-etching, target geometry (coating complex surfaces), precise controls, flexibility, ecology, and sputtering rates. Sputtered film characteristics, such as strong adherence and coherence and film morphology, are briefly evaluated in terms of varying the sputtering parameters. Also described are some of the specific industrial areas which are turning to sputter-deposition techniques.

Spalvins, T.↗

Tackling a Hot Paradox: Laminar Soot Processes-2 (LSP-2)

The last place you want to be in traffic is behind the bus or truck that is belching large clouds of soot onto your freshly washed car. Besides looking and smelling bad, soot is a health hazard. Particles range from big enough to see to microscopic and can accumulate in the lungs, potentially leading to debilitating or fatal lung diseases. Soot is wasted energy, and therein lies an interesting paradox: Soot forms in a flame's hottest regions where you would expect complete combustion and no waste. Soot enhances the emissions of other pollutants (carbon monoxide and polyaromatic hydrocarbons, etc.) from flames and radiates unwanted heat to combustion chambers (a candle's yellowish glow is soot radiating heat), among other effects. The mechanisms of soot formation are among the most important unresolved problems of combustion science because soot affects contemporary life in so many ways. Although we have used fire for centuries, many fundamental aspects of combustion remain elusive, in part because of limits imposed by the effects of gravity on Earth. Hot or warm air rises quickly and draws in fresh cold air behind it, thus giving flames the classical teardrop shape. Reactions occur in a very small zone, too fast for scientists to observe, in detail, what is happening inside the flame. The Laminar Soot Processes (LSP-2) experiments aboard STS-107 will use the microgravity environment of space to eliminate buoyancy effects and thus slow the reactions inside a flame so they can be more readily studied. 'Laminar' means a simple, smooth fuel jet burning in air, somewhat like a butane lighter. This classical flame approximates combustion in diesel engines, aircraft jet propulsion engines, and furnaces and other devices. LSP-2 will expand on surprising results developed from its first two flights in 1997. The data suggest the existence of a universal relationship, the soot paradigm, that, if proven, will be used to model and control combustion systems on Earth. STS-107 experiments also will help set the stage for extended combustion experiments aboard the International Space Station.

Faeth, Gerard M.↗

Three-Gorge Reservoir: A 'Controlled Experiment' for Calibration/Validation of Time-Variable Gravity Signals Detected from Space

With the advances of measurements, modern space geodesy has become a new type of remote sensing for the Earth dynamics, especially for mass transports in the geophysical fluids on large spatial scales. A case in point is the space gravity mission GRACE (Gravity Recovery And Climate Experiment) which has been in orbit collecting gravity data since early 2002. The data promise to be able to detect changes of water mass equivalent to sub-cm thickness on spatial scale of several hundred km every month or so. China s Three-Gorge Reservoir has already started the process of water impoundment in phases. By 2009,40 km3 of water will be stored behind one of the world s highest dams and spanning a section of middle Yangtze River about 600 km in length. For the GRACE observations, the Three-Gorge Reservoir would represent a geophysical controlled experiment , one that offers a unique opportunity to do detailed geophysical studies. -- Assuming a complete documentation of the water level and history of the water impoundment process and aided with a continual monitoring of the lithospheric loading response (such as in area gravity and deformation), one has at hand basically a classical forwardinverse modeling problem of surface loading, where the input and certain output are known. The invisible portion of the impounded water, i.e. underground storage, poses either added values as an observable or a complication as an unknown to be modeled. Wang (2000) has studied the possible loading effects on a local scale; we here aim for larger spatial scales upwards from several hundred km, with emphasis on the time-variable gravity signals that can be detected by GRACE and follow-on missions. Results using the Green s function approach on the PREM elastic Earth model indicate the geoid height variations reaching several millimeters on wavelengths of about a thousand kilometers. The corresponding vertical deformations have amplitude of a few centimeters. In terms of long-wavelength spherical harmonics, the induced geoid height variations are very close to the accuracy of GRACE- recoverable gravity field, while the low-degree (2 to 5) harmonics should be detectable. With a large regional time-variable gravity signal, the Three-Gorge experiment can serve as a useful calibration/verification for GRACE (including the elastic loading effects), and future gravity missions (especially for visco-elastic yielding as well as underground water variations).

Chao, Benjamin F.↗

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Deep-learning↗

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-ofthe-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Hesham ElAbd↗

Airborne Visible/Infrared Imaging Spectrometer 3 (AVIRIS-3)

The Airborne Visible/Infrared Imaging Spectrometer 3 (AVIRIS-3) is the third of the NASA AVIRIS spectrometer series and is being developed in parallel with the Compact Wide-swath Imaging Spectrometer II (CWIS-II) for the University of Zurich, Switzerland. The core spectrometer of AVIRIS-3 is a copy of the optically fast, F/1.8 Dyson imaging spectrometer used by the Earth Surface Mineral Dust Source Investigation (EMIT) that is in development and scheduled for launch to the International Space Station (ISS) in 2022. AVIRIS-3 is intended to provide state-of-the-art imaging spectroscopy measurements for NASA science and application through the next decade and beyond. AVIRIS-3 uses the EMIT spectrometer design interfaced with a scaled two mirror telescope enclosed in a portable vacuum vessel to enable measurements from airborne platforms ranging from a Twin Otter to a business jet or a NASA ER-2. AVIRIS-3 is a cryogenic instrument with advanced system control and real-time onboard spectroscopic data processing algorithms evolved from AVIRIS-NG. The spectral range of AVIRIS-3 is 380 to 2500 nm with 7.4 nm sampling. The radiometric range is from 0 to max terrestrial Lambertian radiance with higher signal-to-noise ratio performance than AVIRIS-Classic or AVIRIS-Next Generation. The spatial field-of-view is 39.5 degrees with 0.56 milliradian sampling. This paper describes the design and development of AVIRIS-3 and presents its characteristics in comparison to the previous generation imaging spectrometers.

Helmlinger, Mark↗

Satellite Ocean-Color Validation Using Ships of Opportunity

The investigation s main objective is to collect from platforms of opportunity (merchant ships, research vessels) concomitant normalized water-leaving radiance and aerosol optical thickness data over the world s oceans. A global, long-term data set of these variables is needed to verify whether satellite retrievals of normalized water-leaving radiance are within acceptable error limits and, eventually, to adjust atmospheric correction schemes. To achieve this objective, volunteer officers, technicians, and scientists onboard the selected ships collect data from portable SIMBAD and Advanced SIMBAD (SIMBADA) radiometers. These instruments are specifically designed for evaluation of satellite-derived ocean color. They measure radiance in spectral bands typical of ocean-color sensors. The SIMBAD version measures in 5 spectral bands centered at 443, 490, 560, 670, and 870 nm, and the Advanced SIMBAD version in 11 spectral bands centered at 350, 380, 412, 443, 490, 510, 565, 620, 670, 750, and 870 nm. Aerosol optical thickness is obtained by viewing the sun disk like a classic sun photometer. Normalized water-leaving radiance, or marine reflectance, is obtained by viewing the ocean surface through a vertical polarizer in a specific geometry (nadir angle of 45o and relative azimuth angle of 135deg) to minimize direct sun glint and reflected sky radiation. The SIMBAD and SIMBADA data, after proper quality control and processing, are delivered to the SIMBIOS project office for inclusion in the SeaBASS archive. They complement data collected in a similar way by the Laboratoire d'Optique Atmospherique of the University of Lille, France. The SIMBAD and SIMBADA data are used to check the radiometric calibration of satellite ocean-color sensors after launch and to evaluate derived ocean-color variables (i.e., normalized water-leaving radiance, aerosol optical thickness, and aerosol type). Analysis of the SIMBAD and SIMBADA data provides information on the accuracy of satellite retrievals of normalized water-leaving radiance, an understanding of the discrepancies between satellite and in situ data, and algorithms that reduce the discrepancies, contributing to more accurate and consistent global ocean color data sets.

Frouin, Robert↗

A new approach for designing self-organizing systems and application to adaptive control

There is tremendous interest in the design of intelligent machines capable of autonomous learning and skillful performance under complex environments. A major task in designing such systems is to make the system plastic and adaptive when presented with new and useful information and stable in response to irrelevant events. A great body of knowledge, based on neuro-physiological concepts, has evolved as a possible solution to this problem. Adaptive resonance theory (ART) is a classical example under this category. The system dynamics of an ART network is described by a set of differential equations with nonlinear functions. An approach for designing self-organizing networks characterized by nonlinear differential equations is proposed.

Ramamoorthy, P. A.↗

Monocrystalline silicon gradiometer for gravity experiments in space

A very important research effort has been made in the last decade in the field of high precision measurement with laser instrumentation. The development of a space borne gradiometer operating at a high sensitivity level using laser measurement of the distance between proof mass over a short base line of order one meter is discussed. Two aspects of laser technology make it a promising tool for gradiometry measurements: quantum limited accuracy and absolute distance measurements. The quantum limit associated with laser instrumentation was formulated. The relevant quantum and classical sources of errors in laser measurements were reviewed and corresponding laser performance requirements for gradient measurements were evaluated. Some mechanical quality factor measurements were made on simple resonant monocrystalline silicon suspensions. It was discovered that the use of zero derivative restoring forces to position the gradiometer test masses will dramatically reduce the gradiometer temperature control requirements. A laser beam side injection scheme was discovered which permits rejection of common mode accelerations. These concepts are briefly discussed.

Richard, Jean-Paul↗

Heritability of markers of bone metabolism

Several classic twin studies show genetic effects on markers of bone health, including bone mineral density and parathyroid hormone (PTH). This study was performed to assess the relative contribution of genetics to biochemical markers of bone metabolism. Fifteen sets of identical twins (8 male, 7 female) were housed in a clinical research center where diet was controlled (15% protein, 55% carbohydrate, 30% fat) for 3 consecutive days. Each day, 24-h urine pools were collected and N-telopeptide (NTX), deoxypyridinoline (DPD), calcium, and serum PTH were measured. The broad-sense heritability factor (H2) is an estimation of the portion of the total variance of a given phenotype that is attributable to genetic variance. H2 was estimated from the correlation coefficient of the phenotype data. H2 for NTX was 94% for males and 80% for females, DPD was 88% for males and 97% for females, urinary calcium excretion was 97% for males and 90% for females, and PTH was 92% for males and 79% for females. Since environmental variability was minimized for the 3 days of data collection, these heritability factors are likely overestimated. Nonetheless, the data support the concept that PTH is a predominantly heritable trait, and suggest that NTX, DPD, and calcium excretion are as well. These biochemical data support the previously documented heritability of bone health.

Smith, Scott M.↗

Phase-field model for isothermal phase transitions in binary alloys

A new phase field model is described which models isothermal phase transitions between ideal binary alloy solution phases. Equations are developed for the temporal and spatial variation of the phase field, which describes the identity of the phase, and of the composition. An asymptotic analysis, as the gradient energy coefficient of the phase field becomes small, was conducted. From the analysis, it is shown that the model recovers classical sharp interface models of this situation when the interfacial layers are thin, and they show how to relate the parameters appearing in the phase field model to material and growth parameters in real systems. Further, three stages of temporal evolution are identified: the first corresponding to interfacial genesis which occurs very rapidly; the second to interfacial motion controlled by the local energy difference across the interface and diffusion; the last taking place on a long time scale in which curvature effects are important and which correspond to Ostwald ripening. The results of the numerical calculations are presented.

Wheeler, A. A.↗

Estimating the Inertia Matrix of a Spacecraft

A paper presents a method of utilizing some flight data, aboard a spacecraft that includes reaction wheels for attitude control, to estimate the inertia matrix of the spacecraft. The required data are digitized samples of (1) the spacecraft attitude in an inertial reference frame as measured, for example, by use of a star tracker and (2) speeds of rotation of the reaction wheels, the moments of inertia of which are deemed to be known. Starting from the classical equations for conservation of angular momentum of a rigid body, the inertia-matrix-estimation problem is formulated as a constrained least-squares minimization problem with explicit bounds on the inertia matrix incorporated as linear matrix inequalities. The explicit bounds reflect physical bounds on the inertia matrix and reduce the volume of data that must be processed to obtain a solution. The resulting minimization problem is a semidefinite optimization problem that can be solved efficiently, with guaranteed convergence to the global optimum, by use of readily available algorithms. In a test case involving a model attitude platform rotating on an air bearing, it is shown that, relative to a prior method, the present method produces better estimates from few data.

Acikmese, Behcet↗

Random field estimation approach to robot dynamics

The difference equations of Kalman filtering and smoothing recursively factor and invert the covariance of the output of a linear state-space system driven by a white-noise process. Here it is shown that similar recursive techniques factor and invert the inertia matrix of a multibody robot system. The random field models are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. They are easier to describe than the models based on classical mechanics, which typically require extensive derivation and manipulation of equations of motion for complex mechanical systems. With the spatially random models, more primitive locally specified computations result in a global collective system behavior equivalent to that obtained with deterministic models. The primary goal of applying random field estimation is to provide a concise analytical foundation for solving robot control and motion planning problems.

Rodriguez, Guillermo↗

Heat pipes for spacecraft temperature control: Their usefulness and limitations

Heat pipes are used in spacecraft to equalize the temperature of structures and maintain temperature control of electronic components. Information is provided for a designer on: (1) a typical mounting technique, (2) choices available in wick geometries and fluids, (3) tests involved in flight-qualifying the design, and (4) heat pipe limitations. An evaluation of several heat pipe designs showed that the behavior of heat pipes at room temperature does not necessarily correlate with the classic equations used to predict their performance. They are sensitive to such parameters as temperature, fluid inventory, orientation, and noncondensable gases.

Ollendorf, S.↗

Carbon Nanotube Bonding Strength Enhancement Using Metal "Wicking" Process

Carbon nanotubes grown from a surface typically have poor bonding strength at the interface. A process has been developed for adding a metal coat to the surface of carbon nano tubes (CNTs) through a wicking process, which could lead to an enhanced bonding strength at the interface. This process involves merging CNTs with indium as a bump-bonding enhancement. Classical capillary theory would not normally allow materials that do not wet carbon or graphite to be drawn into the spacings by capillary action because the contact angle is greater than 90 degrees. However, capillary action can be induced through JPL's ability to fabricate oriented CNT bundles to desired spacings, and through the use of deposition techniques and temperature to control the size and mobility of the liquid metal streams and associated reservoirs. A reflow and plasma cleaning process has also been developed and demonstrated to remove indium oxide, and to obtain smooth coatings on the CNT bundles.

Lamb, James L.↗

America's Next Great Ship: Space Launch System Core Stage Transitioning from Design to Manufacturing

The Space Launch System (SLS) Program is essential to achieving the Nation's and NASA's goal of human exploration and scientific investigation of the solar system. As a multi-element program with emphasis on safety, affordability, and sustainability, SLS is becoming America's next great ship of exploration. The SLS Core Stage includes avionics, main propulsion system, pressure vessels, thrust vector control, and structures. Boeing manufactures and assembles the SLS core stage at the Michoud Assembly Facility (MAF) in New Orleans, LA, a historical production center for Saturn V and Space Shuttle programs. As the transition from design to manufacturing progresses, the importance of a well-executed manufacturing, assembly, and operation (MA&O) plan is crucial to meeting performance objectives. Boeing employs classic techniques such as critical path analysis and facility requirements definition as well as innovative approaches such as Constraint Based Scheduling (CBS) and Cirtical Chain Project Management (CCPM) theory to provide a comprehensive suite of project management tools to manage the health of the baseline plan on both a macro (overall project) and micro level (factory areas). These tools coordinate data from multiple business systems and provide a robust network to support Material & Capacity Requirements Planning (MRP/CRP) and priorities. Coupled with these tools and a highly skilled workforce, Boeing is orchestrating the parallel buildup of five major sub assemblies throughout the factory. Boeing and NASA are transforming MAF to host state of the art processes, equipment and tooling, the most prominent of which is the Vertical Assembly Center (VAC), the largest weld tool in the world. In concert, a global supply chain is delivering a range of structural elements and component parts necessary to enable an on-time delivery of the integrated Core Stage. SLS is on plan to launch humanity into the next phase of space exploration.

Birkenstock, Benjamin↗

Combined homogeneous and heterogeneous crystal nucleation in glasses

The temperature dependence of combined homogeneous and heterogeneous crystal nucleation is examined within the framework of the classical theory. It is demonstrated that nucleation can have a local maximum rate at one or two temperatures. The physical parameters which cause large changes in the structure of the nucleation curve are elucidated. Also, the influence of saturation effects on the structure of nucleation curves is illustrated. The utilization of these results for the interpretation of experiments and for the production of controlled crystal nucleation in glass is considered.

Weinberg, Michael C.↗