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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 1,387 records · Page 77

Creation of discrete active site domains via mesoporous silica poly(styrene) composite materials for incompatible acid–base cascade reactions

This work highlights the design and synthesis of bifunctional mesoporous silicate – polymer composite dual acid–base supported cascade catalysts. Compartmentalization of the two incompatible active sites is sought by segregating acid sites on the silica surface, and base sites within polymer chains and/or polymer domains. The ability to isolate and segregate active sites via control of the mesoporous silica pore size and polymer molecular weight is probed with silica samples functionalized by a grafting-to process. Supplemental activator and reducing agent (SARA) atom transfer radical polymerization is used to synthesize random copolymers containing protected primary amines. Thiol–ene ‘click’ chemistry facilitates silica functionalization via a convergent approach, with the ene-functionalized polymer end group and silica-grafted thiols forming SBA/MCM-SH-poly(styrene-co-2-(4-vinylbenzyl)isoindoline-1,3-dione). Polymer deprotection and thiol oxidation produces primary amine/sulfonic acid containing composite catalysts. With the polymer supported Lewis base and silica grafted Brønsted acid, the two-step deacetalization – Knoevenagel condensation cascade is explored to assess the ability of these polymer/silica hybrids to segregate active sites, allowing both acid and base site accessibility. Six composite catalysts are synthesized and tested in individual and cascade reactions with kinetic results demonstrating that lower molecular weight SBA-15-P1 and MCM-41-P1 catalysts outperform (higher turnover frequencies and initial rates) their higher molecular weight analogues, as well as a polymer-free system containing molecular active sites dispersed on the silica surface. Higher molecular weight composite catalysts perform more poorly due to limited chain solubility, mass transfer limitations, and poor catalyst accessibility. In many cases, the polymer chains effectively thread into the mesopores, with higher molecular weight polymers leading to pore blockage and inhibited mass transfer.

36 MATERIALS SCIENCE↗

Differentiation and classification of bacterial endotoxins based on surface enhanced Raman scattering and advanced machine learning

Bacterial endotoxin, a major component of the Gram-negative bacterial outer membrane leaflet, is a lipopolysaccharide shed from bacteria during their growth and infection and can be utilized as a biomarker for bacterial detection. Here, the surface enhanced Raman scattering (SERS) spectra of eleven bacterial endotoxins with an average detection amount of 8.75 pg per measurement have been obtained based on silver nanorod array substrates, and the characteristic SERS peaks have been identified. With appropriate spectral pre-processing procedures, different classical machine learning algorithms, including support vector machine, k-nearest neighbor, random forest, etc., and a modified deep learning algorithm, RamanNet, have been applied to differentiate and classify these endotoxins. It has been found that most conventional machine learning algorithms can attain a differentiation accuracy of >99%, while RamanNet can achieve 100% accuracy. Such an approach has the potential for precise classification of endotoxins and could be used for rapid medical diagnoses and therapeutic decisions for pathogenic infections.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrostatic rogue-waves in relativistically degenerate plasmas

In this paper, we investigate the modulational instability and the possibility of electrostatic rogue-wave propagations in a completely degenerate plasma with arbitrary degree of degeneracy, i.e., relativistically degenerate plasma, ranging from solid density to the astrophysical compact stars. The hydrodynamic approach along with the perturbation method is used to reduce the governing equations to the nonlinear Schrödinger equation from which the modulational instability, the growth rate of envelope excitations and the occurrence of rogue as well as super-rogue waves in the plasma, is evaluated. It is observed that the modulational instability in a fully degenerate plasma can be quite sensitive to the plasma number-density and the wavenumber of envelop excitations. It is further revealed that the relativistically degeneracy plasmas (R{sub 0} > 1) are almost always modulationally unstable. It is found, however, that the highly energetic sharply localized electrostatic rogue as well as super-rogue waves can exist in the astrophysical compact objects like white dwarfs and neutron star crusts. The later may provide a link to understand many physical processes in such stars and it may lead us to the origin of the random-localized intense short gamma-ray bursts, which “appear from nowhere and disappear without a trace” quite similar to oceanic rogue structures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Disentangling direct from indirect relationships in association networks

Networks are vital tools for understanding and modeling interactions in complex systems in science and engineering, and direct and indirect interactions are pervasive in all types of networks. However, quantitatively disentangling direct and indirect relationships in networks remains a formidable task. Here, we present a framework, called iDIRECT (Inference of Direct and Indirect Relationships with Effective Copula-based Transitivity), for quantitatively inferring direct dependencies in association networks. Using copula-based transitivity, iDIRECT eliminates/ameliorates several challenging mathematical problems, including ill-conditioning, self-looping, and interaction strength overflow. With simulation data as benchmark examples, iDIRECT showed high prediction accuracies. Application of iDIRECT to reconstruct gene regulatory networks in Escherichia coli also revealed considerably higher prediction power than the best-performing approaches in the DREAM5 (Dialogue on Reverse Engineering Assessment and Methods project, #5) Network Inference Challenge. In addition, applying iDIRECT to highly diverse grassland soil microbial communities in response to climate warming showed that the iDIRECT-processed networks were significantly different from the original networks, with considerably fewer nodes, links, and connectivity, but higher relative modularity. Further analysis revealed that the iDIRECT-processed network was more complex under warming than the control and more robust to both random and target species removal ( P < 0.001). As a general approach, iDIRECT has great advantages for network inference, and it should be widely applicable to infer direct relationships in association networks across diverse disciplines in science and engineering.

59 BASIC BIOLOGICAL SCIENCES↗

ERRATUM: “Automated Transient Identification in the Dark Energy Survey” (2015, AJ, 150, 82)

Here, we describe an algorithm for identifying point-source transients and moving objects on reference-subtracted optical images containing artifacts of processing and instrumentation. The algorithm makes use of the supervised machine learning technique known as Random Forest. We present results from its use in the Dark Energy Survey Supernova program (DES-SN), where it was trained using a sample of 898,963 signal and background events generated by the transient detection pipeline. After reprocessing the data collected during the first DES-SN observing season (2013 September through 2014 February) using the algorithm, the number of transient candidates eligible for human scanning decreased by a factor of 13.4, while only 1.0% of the artificial Type Ia supernovae (SNe) injected into search images to monitor survey efficiency were lost, most of which were very faint events. Here we characterize the algorithm's performance in detail, and we discuss how it can inform pipeline design decisions for future time-domain imaging surveys, such as the Large Synoptic Survey Telescope and the Zwicky Transient Facility. An implementation of the algorithm and the training data used in this paper are available at at http://portal.nersc.gov/project/dessn/autoscan.

79 ASTRONOMY AND ASTROPHYSICS↗

Deep-learning-based image registration for nano-resolution tomographic reconstruction

Nano-resolution full-field transmission X-ray microscopy has been successfully applied to a wide range of research fields thanks to its capability of non-destructively reconstructing the 3D structure with high resolution. Due to constraints in the practical implementations, the nano-tomography data is often associated with a random image jitter, resulting from imperfections in the hardware setup. Without a proper image registration process prior to the reconstruction, the quality of the result will be compromised. Here a deep-learning-based image jitter correction method is presented, which registers the projective images with high efficiency and accuracy, facilitating a high-quality tomographic reconstruction. This development is demonstrated and validated using synthetic and experimental datasets. We report the method is effective and readily applicable to a broad range of applications. Together with this paper, the source code is published and adoptions and improvements from our colleagues in this field are welcomed.

deep learning↗

Noninvasive differential diagnosis of dental periapical lesions in cone-beam CT scans

Purpose: This paper proposes a novel application of computer-aided diagnosis (CAD) to an everyday clinical dental challenge: the noninvasive differential diagnosis of periapical lesions between periapical cysts and granulomas. A histological biopsy is the most reliable method currently available for this differential diagnosis; however, this invasive procedure prevents the lesions from healing noninvasively despite a report that they may heal without surgical treatment. A CAD using cone-beam computed tomography (CBCT) offers an alternative noninvasive diagnostic tool which helps to avoid potentially unnecessary surgery and to investigate the unknown healing process and rate for the lesions. Methods: The proposed semiautomatic solution combines graph-based random walks segmentation with machine learning-based boosted classifiers and offers a robust clinical tool with minimal user interaction. As part of this CAD framework, the authors provide two novel technical contributions: (1) probabilistic extension of the random walks segmentation with likelihood ratio test and (2) LDA-AdaBoost: a new integration of weighted linear discriminant analysis to AdaBoost. Results: A dataset of 28 CBCT scans is used to validate the approach and compare it with other popular segmentation and classification methods. The results show the effectiveness of the proposed method with 94.1% correct classification rate and an improvement of the performance by comparison with the Simon’s state-of-the-art method by 17.6%. The authors also compare classification performances with two independent ground-truth sets from the histopathology and CBCT diagnoses provided by endodontic experts. Conclusions: Experimental results of the authors show that the proposed CAD system behaves in clearer agreement with the CBCT ground-truth than with histopathology, supporting the Simon’s conjecture that CBCT diagnosis can be as accurate as histopathology for differentiating the periapical lesions.

60 APPLIED LIFE SCIENCES↗

Prediction skill of tropical synoptic scale transients from ECMWF and NCEP ensemble prediction systems

The prediction skill of tropical synoptic scale transients (SSTR) such as monsoon low and depression during the boreal summer of 2007–2009 are assessed using high resolution ECMWF and NCEP TIGGE forecasts data. By analyzing 246 forecasts for lead times up to 10 days, it is found that the models have good skills in forecasting the planetary scale means but the skills of SSTR remain poor, with the latter showing no skill beyond 2 days for the global tropics and Indian region. Consistent forecast skills among precipitation, velocity potential, and vorticity provide evidence that convection is the primary process responsible for precipitation. The poor skills of SSTR can be attributed to the larger random error in the models as they fail to predict the locations and timings of SSTR. Strong correlation between the random error and synoptic precipitation suggests that the former starts to develop from regions of convection. As the NCEP model has larger biases of synoptic scale precipitation, it has a tendency to generate more random error that ultimately reduces the prediction skill of synoptic systems in that model. Finally, the larger biases in NCEP may be attributed to the model moist physics and/or coarser horizontal resolution compared to ECMWF.

54 ENVIRONMENTAL SCIENCES↗

Multipath induced errors in meteorological Doppler/interferometer location systems

One application of an RF interferometer aboard a low-orbiting spacecraft to determine the location of ground-based transmitters is in tracking high-altitude balloons for meteorological studies. A source of error in this application is reflection of the signal from the sea surface. Through propagating and signal analysis, the magnitude of the reflection-induced error in both Doppler frequency measurements and interferometer phase measurements was estimated. The theory of diffuse scattering from random surfaces was applied to obtain the power spectral density of the reflected signal. The processing of the combined direct and reflected signals was then analyzed to find the statistics of the measurement error. It was found that the error varies greatly during the satellite overpass and attains its maximum value at closest approach. The maximum values of interferometer phase error and Doppler frequency error found for the system configuration considered were comparable to thermal noise-induced error.

Wallace, R. G.↗

Research in the design of high-performance reconfigurable systems

An initial design for the Bit Processor (BP) referred to in prior reports as the Processing Element or PE has been completed. Eight BP's, together with their supporting random-access memory, a 64 k x 9 ROM to perform addition, routing logic, and some additional logic, constitute the components of a single stage. An initial stage design is given. Stages may be combined to perform high-speed fixed or floating point arithmetic. Stages can be configured into a range of arithmetic modules that includes bit-serial one or two-dimensional arrays; one or two dimensional arrays fixed or floating point processors; and specialized uniprocessors, such as long-word arithmetic units. One to eight BP's represent a likely initial chip level. The Stage would then correspond to a first-level pluggable module. As both this project and VLSI CAD/CAM progress, however, it is expected that the chip level would migrate upward to the stage and, perhaps, ultimately the box level. The BP RAM, consisting of two banks, holds only operands and indices. Programs are at the box (high-level function) and system level. At the system level initial effort has been concentrated on specifying the tools needed to evaluate design alternatives.

Slotnick, D. L.↗

A generalization of the near-optimum binary coherent state receiver concept

The structure of a maximum a posteriori decoder is derived for binary optical fields processed according to Kennedy's near-optimum scheme, but operating in the presence of random optical phase-error and interfering background fields. An exact expression is found for the error probability, and examples to illustrate decoder performance under various operating conditions of interest are provided.

Vilnrotter, V. A.↗

Automated mesoscale winds determined from satellite imagery

A new automated technique for extracting mesoscale fields from GOES visible/infrared satellite imagery was developed. Quality control parameters were defined to allow objective editing of the wind fields. The system can produce equivalent or superior cloud wind estimates compared to the time consuming manual methods used on various interactive meteorological processing systems. Analysis of automated mesoscale cloud wind for a test case yields an estimated random error value one meter per second and produces both regional and mesoscale vector wind field structure and divergence patterns that are consistent in time and highly correlated with subsequent severe thunderstorm development.

Source record↗

Acceleration techniques for dependability simulation

As computer systems increase in complexity, the need to project system performance from the earliest design and development stages increases. We have to employ simulation for detailed dependability studies of large systems. However, as the complexity of the simulation model increases, the time required to obtain statistically significant results also increases. This paper discusses an approach that is application independent and can be readily applied to any process-based simulation model. Topics include background on classical discrete event simulation and techniques for random variate generation and statistics gathering to support simulation.

Barnette, James David↗

Data Processing for NASA's TDRSS DAMA Channel

A concept for the addition of a Demand Assignment Multiple Access (DAMA) service to NASA's current Space Network (SN) is developed. Specifically, the design of a receiver for the DAMA channel is outlined. Also, an outline of the procedures taken to process the received service request is presented. The modifications to the (SN) system are minimal. The post reception processing is accomplished using standard commercial off the shelf (COTS) packages. The result is a random access system capable of receiving requests for service.

Long, Christopher C.↗

Microgravity and Charge Transfer in the Neuronal Membrane: Implications for Computational Neurobiology

Evidence from natural and artificial membranes indicates that the neural membrane is a liquid crystal. A liquid-to-gel phase transition caused by the application of superposed electromagnetic fields to the outer membrane surface releases spin-correlated electron pairs which propagate through a charge transfer complex. The propagation generates Rydberg atoms in the lipid bilayer lattice. In the present model, charge density configurations in promoted orbitals interact as cellular automata and perform computations in Hilbert space. Due to the small binding energies of promoted orbitals, their automata are highly sensitive to microgravitational perturbations. It is proposed that spacetime is classical on the Rydberg scale, but formed of contiguous moving segments, each of which displays topological equivalence. This stochasticity is reflected in randomized Riemannian tensor values. Spacetime segments interact with charge automata as components of a computational process. At the termination of the algorithm, an orbital of high probability density is embedded in a more stabilized microscopic spacetime. This state permits the opening of an ion channel and the conversion of a quantum algorithm into a macroscopic frequency code.

Wallace, Ron↗

Microfabricated Segmented-Involute-Foil Regenerator for Stirling Engines

An involute-foil regenerator was designed, microfabricated, and tested in an oscillating-flow test rig. The concept consists of stacked involute-foil nickel disks (see figure) microfabricated via a lithographic process. Test results yielded a performance of about twice that of the 90-percent random-fiber currently used in small Stirling converters. The segmented nature of the involute- foil in both the axial and radial directions increases the strength of the structure relative to wrapped foils. In addition, relative to random-fiber regenerators, the involute-foil has a reduced pressure drop, and is expected to be less susceptible to the release of metal fragments into the working space, thus increasing reliability. The prototype nickel involute-foil regenerator was adequate for testing in an engine with a 650 C hot-end temperature. This is lower than that required by larger engines, and high-temperature alloys are not suited for the lithographic microfabrication approach.

Ibrahim, Mounir↗