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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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NASA/DOD Aerospace Knowledge Diffusion Research Project. Report 29: A comparison of the technical communications practices of Japanese and US aerospace engineers and scientists

As part of Phase 4 of the NASA/DoD Aerospace Knowledge Diffusion Research Project, two studies were conducted that investigated the technical communications practices of Japanese and U.S. aerospace engineers and scientists. Both studies have the same seven objectives: first, to solicit the opinions of aerospace engineers and scientists regarding the importance of technical communications to their profession; second, to determine the use and production of technical communications by aerospace engineers and scientists; third; to seek their views about the appropriate content of an undergraduate course in technical communications; fourth, to determine aerospace engineers' and scientists' use of libraries, technical information centers, and on-line data bases; fifth, to determine the use and importance of computer and information technology to them; sixth, to determine their use of electronic networks; and seventh, to determine their use of foreign and domestically produced technical reports. A self-administered questionnaire was distributed to aerospace engineers and scientists in Japan and at the NASA Ames Research Center and the NASA Langley Research Center. The completion rates for the Japanese and U.S. surveys were 85 and 61 percent, respectively. Responses of the Japanese and U.S. participants to selected questions are presented in this report.

Pinelli, Thomas E.↗

Accessing Data Federations with CVMFS

Data federations have become an increasingly common tool for large collaborations such as CMS and Atlas to efficiently distribute large data files. Unfortunately, these typically are implemented with weak namespace semantics and a non-POSIX API. On the other hand, CVMFS has provided a POSIX-compliant read-only interface for use cases with a small working set size (such as software distribution). The metadata required for the CVMFS POSIX interface is distributed through a caching hierarchy, allowing it to scale to the level of about a hundred thousand hosts. In this paper, we will describe our contributions to CVMFS that merges the data scalability of XRootD-based data federations (such as AAA) with metadata scalability and POSIX interface of CVMFS. We modified CVMFS so it can serve unmodified files without copying them to the repository server. CVMFS 2.2.0 is also able to redirect requests for data files to servers outside of the CVMFS content distribution network. Finally, we added the ability to manage authorization and authentication using security credentials such as X509 proxy certificates. We combined these modifications with the OSGs StashCache regional XRootD caching infrastructure to create a cached data distribution network. Here, we will show performance metrics accessing the data federation through CVMFS compared to direct data federation access. Additionally, we will discuss the improved user experience of providing access to a data federation through a POSIX filesystem.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

A Compositional Relevance Model for Adaptive Information Retrieval

There is a growing need for rapid and effective access to information in large electronic documentation systems. Access can be facilitated if information relevant in the current problem solving context can be automatically supplied to the user. This includes information relevant to particular user profiles, tasks being performed, and problems being solved. However most of this knowledge on contextual relevance is not found within the contents of documents, and current hypermedia tools do not provide any easy mechanism to let users add this knowledge to their documents. We propose a compositional relevance network to automatically acquire the context in which previous information was found relevant. The model records information on the relevance of references based on user feedback for specific queries and contexts. It also generalizes such information to derive relevant references for similar queries and contexts. This model lets users filter information by context of relevance, build personalized views of documents over time, and share their views with other users. It also applies to any type of multimedia information. Compared to other approaches, it is less costly and doesn't require any a priori statistical computation, nor an extended training period. It is currently being implemented into the Computer Integrated Documentation system which enables integration of various technical documents in a hypertext framework.

Mathe, Nathalie↗

A Step Beyond Simple Keyword Searches: Services Enabled by a Full Content Digital Journal Archive

The problems of managing and searching large archives of scientific journal articles can potentially be addressed through data mining and statistical techniques matured primarily for quantitative scientific data analysis. A journal paper could be represented by a multivariate descriptor, e.g., the occurrence counts of a number key technical terms or phrases (keywords), perhaps derived from a controlled vocabulary ( e . g . , the American Meteorological Society's Glossary of Meteorology) or bootstrapped from the journal archive itself. With this technique, conventional statistical classification tools can be leveraged to address challenges faced by both scientists and professional societies in knowledge management. For example, cluster analyses can be used to find bundles of "most-related" papers, and address the issue of journal bifurcation (when is a new journal necessary, and what topics should it encompass). Similarly, neural networks can be trained to predict the optimal journal (within a society's collection) in which a newly submitted paper should be published. Comparable techniques could enable very powerful end-user tools for journal searches, all premised on the view of a paper as a data point in a multidimensional descriptor space, e.g.: "find papers most similar to the one I am reading", "build a personalized subscription service, based on the content of the papers I am interested in, rather than preselected keywords", "find suitable reviewers, based on the content of their own published works", etc. Such services may represent the next "quantum leap" beyond the rudimentary search interfaces currently provided to end-users, as well as a compelling value-added component needed to bridge the print-to-digital-medium gap, and help stabilize professional societies' revenue stream during the print-to-digital transition.

Boccippio, Dennis J.↗

Glass formation and short-range order structures in the BaS + La 2 S 3 + GeS 2 system

Infrared (IR) optical materials have enabled a broad range of optical sensing and measurement applications in the mid-wave and long-wave IR. Many IR transmitting glasses are based on covalently-bonded selenides and tellurides, such as As 2 Se 3 and GeTe 2 , which typically have relatively low glass transition temperatures (T g ) on the order of 200 to 350 °C. Many applications have working temperatures above the T g of these materials, which compels the development of new IR materials. This work studies the underlying short-range order (SRO) structure and glass formability of a new family of ionically-bonded sulfide glasses, xBaS + yLa 2 S 3 + (1-x-y)GeS 2 , to develop high T g optical materials with a broad IR transmission range. These sulfide glasses were produced by melting sulfide materials inside evacuated and sealed carbon-coated silica ampoules at 1150 °C for 12 hours and quenching to room temperature to form glass. Glass samples were then characterized by IR and Raman spectroscopies and differential thermal analysis (DTA). It was found that by increasing the modifier concentration, the predominantly Ge 4 SRO units, the superscript defines the number of bridging sulfur (BS) ions in the tetrahedral network found in GeS 2 glasses, are ultimately converted to Ge 0 units at > 40 mol% network modifier content through the generation of non-bridging sulfur (NBS) ions. These molecular ionic units still form a glassy network, with some of the highest reported T g values to date for a pure sulfide glass. This suggests that this composition has strong ionic bonds between negatively-charged tetrahedral SRO units and the positively-charged modifier cations. While the glass network is depolymerized in the high modifier content glasses though the formation of a high concentration of molecular ionic Ge 0 SRO groups, they are, nevertheless, homogeneous glassy materials that exhibit the largest T g and ΔT (difference between crystallization temperature, T c , and T g ) values of glasses in this system, making them the optimal glasses for high T g IR optical components, including, potentially, refractory IR optical fibers.

non-crystalline solids, glass formation↗

SpaceOps 2012 Plus 2: Social Tools to Simplify ISS Flight Control Communications and Log Keeping

A paper written for the SpaceOps 2012 Conference (Simplify ISS Flight Control Communications and Log Keeping via Social Tools and Techniques) identified three innovative concepts for real time flight control communications tools based on social mechanisms: a) Console Log Tool (CoLT) - A log keeping application at Marshall Space Flight Center's (MSFC) Payload Operations Integration Center (POIC) that provides "anywhere" access, comment and notifications features similar to those found in Social Networking Systems (SNS), b) Cross-Log Communication via Social Techniques - A concept from Johnsson Space Center's (JSC) Mission Control Center Houston (MCC-H) that would use microblogging's @tag and #tag protocols to make information/requests visible and/or discoverable in logs owned by @Destination addressees, and c) Communications Dashboard (CommDash) - A MSFC concept for a Facebook-like interface to visually integrate and manage basic console log content, text chat streams analogous to voice loops, text chat streams dedicated to particular conversations, generic and position-specific status displays/streams, and a graphically based hailing display. CoLT was deployed operationally at nearly the same time as SpaceOps 2012, the Cross- Log Communications idea is currently waiting for a champion to carry it forward, and CommDash was approved as a NASA Iinformation Technoloby (IT) Labs project. This paper discusses lessons learned from two years of actual CoLT operations, updates CommDash prototype development status, and discusses potential for using Cross-Log Communications in both MCC-H and/or POIC environments, and considers other ways for synergizing console applcations.

Cowart, Hugh S.↗

A novel targeted plugging and fracture‐adaptable gel used as a diverting agent in fracturing

Abstract Diverting agents that could plug a targeted location and fill different shapes of fractures have attracted an increasing attention in the field of fracturing. In this study, a series of novel diverting agents were prepared by mixing aldehyde sodium alginate (ASA) and amino gelatin (AG) through a Schiff base reaction to form a primary network, polylactic acid (PLA) fibers were added to produce a 3D network, and Ca 2+ was mixed in as an ionic cross‐linking agent to strengthen the cross‐linking points. It was found that gelation time, swelling behavior, and mechanical performance could be controlled by varying the content of aldehyde groups and amino groups. Gelation time could be controlled in 1‐10 minutes. Plugging behavior and degradation tests demonstrated that the hydrogel could suit fractures with various shapes and plug effectively under high temperatures and pressures, and it could eventually become acidic fluid to help clean the wellbore. This novel ASA/AG/PLA hydrogel constitutes a promising environmentally friendly diverting agent in the application of diversion fracturing.

Zhang, Yuyuan↗

Compression Analytics for Classification and Anomaly Detection within Network Communication

Here, the flexibility of network communication within Internet protocols is fundamental to network function, yet this same flexibility permits the possibility of malicious use. In particular, malicious behavior can masquerade as benign traffic, thus evading systems designed to catch misuse of network resources. However, perfect imitation of benign traffic is difficult, meaning that small unintentional deviations from normal can occur. Identifying these deviations requires that the defenders know what features reveal malicious behavior. Herein we present an application of compression-based analytics to network communication that can reduce the need for defenders to know a priori what features they need to examine. Motivating the approach is the idea that compression relies on the ability to discover and make use of predictable elements in information, thereby highlighting any deviations between expected and received content. We introduce a so-called “slice compression” score to identify malicious or anomalous communication in two ways. First, we apply normalized compression distances (NCDs) to classification problems and discuss methods for reducing the noise by excising application content (as opposed to protocol features) using slice compression. Second, we present a new technique for anomaly detection, referred to as slice compression for anomaly detection (SCADe). A diverse collection of datasets are analyzed to illustrate the efficacy of the proposed approaches. While our focus is network communication, other types of data are also considered to illustrate the generality of the method.

97 MATHEMATICS AND COMPUTING↗

Evaluation and Application of Remotely Sensed Soil Moisture Products

Whereas in-situ measurements of soil moisture are very accurate, achieving accurate regional soil moisture estimates derived solely from point measurements is difficult because of the dependence upon the density of the gauge network and the proper upkeep of these instruments, which can be costly. Microwave remote sensing is the only technology capable of providing timely direct measurements of regional soil moisture in areas that are lacking in-situ networks. Soil moisture remote sensing technology is well established has been successfully applied in many fashions to Earth Science applications. Since the microwave emission from the soil surface has such a high dependency upon the moisture content within the soil, we can take advantage of this relationship and combined with physically-based models of the land surface, derive accurate regional estimates of the soil column water content from the microwave brightness temperature observed from satellite-based remote sensing instruments. However, there still remain many questions regarding the most efficient methodology for evaluating and applying satellite-based soil moisture estimates. As discussed below, we to use satellite-based estimates of soil moisture dynamics to improve the predictive capability of an optimized hydrologic model giving more accurate root-zone soil moisture estimates.

Bolten, J.↗

Synthesis of Bio-Based Repairable Polyimines with Tailored Properties by Lignin Fractionation

Developing sustainable polymers with low-value lignin remains a challenge. Herein, lignin-containing repairable polyimines were synthesized with tailored properties using lignin fractionation. First, softwood Kraft lignin is fractionated into a more homogeneous fraction with a lower molecular weight and a higher OH content. Next, Kraft lignin and its fraction are esterified by levulinic acid to introduce active ketone groups and subsequently condensed with oleylamine (OAm) and bis(3-aminopropyl)-terminated polydimethylsiloxane (PDMS) via a catalyst-free Schiff-base reaction to form grafted lignin-OAm copolymers and cross-linked lignin-PDMS polymer networks (MKL-P and MFL-P), respectively. Results show that lignin-OAm polyimines can be self-repaired and hot reprocessed under pressure, while lignin-PDMS polyimines can be repaired with the assistance of a healing agent, heat, and pressure. Dynamic mechanical analyses demonstrate that the stress–relaxation behaviors of the polyimines follow the Arrhenius law under thermal-stress activation, indicating the occurrence of transimination. Moreover, compared with Kraft lignin, the lignin fraction ameliorates the grafting density of ketones and enhances the cross-linking density of lignin-PDMS polyimine networks. The higher cross-linking density of MFL-P leads to superior stress–relaxation activation energy, thermal stability, hydrophobicity, and light-shielding ability but inferior repairability and translucency. Finally, this work provides insights into the polymerization of lignin-based polymer networks and the potential application of lignin-PDMS polyimines for repairable, translucent, anti-UV, and hydrophobic coatings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The effect of ZnO ↔ Ta{sub 2}O{sub 5} substitution on the structural and thermal properties of SiO{sub 2}-ZnO-SrO-CaO-P{sub 2}O{sub 5} glasses

A series of glasses based on the system 48SiO{sub 2}-(36-X) ZnO-6CaO-8SrO-2P{sub 2}O{sub 5}-XTa{sub 2}O{sub 5} with X varying from 0 mol% (Ta0) to 8 mol% (Ta4) were fabricated. The structural features as a function of Ta{sub 2}O{sub 5} content were investigated by network connectivity (NC) calculations, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR). The thermal properties of the glasses were obtained by performing simultaneous thermal analysis (STA). XRD showed that all compositions were predominantly amorphous, however the incorporation of tantalum pentoxide (Ta{sub 2}O{sub 5}) resulted in a small degree of crystallinity within the sample. Replacing ZnO with Ta{sub 2}O{sub 5} increases the glass transition, crystallization and melting temperatures. Further, Ta{sub 2}O{sub 5} incorporation results in higher thermal stability suggesting a greater glass forming tendency and the insertion of Ta in the glass network. XPS and FTIR spectroscopy revealed that Ta behaves as a glass former and that Zn has an intermediary role in the vitreous network. - Highlights: • ZnO substitution for Ta{sub 2}O{sub 5} in the glass system SiO{sub 2}-ZnO-CaO-SrO-P{sub 2}O{sub 5} is presented. • ZnO substitution results in greater glass forming tendency. • Ta{sub 2}O{sub 5} addition results in the formation of Si−O−Ta and Ta−O−Ta linkages. • Ta{sub 2}O{sub 5} addition increases the glass thermal stability. • ZnO behaves as an intermediate in this glass system.

36 MATERIALS SCIENCE↗

Efficiency Improvement in a Busy Radiology Practice: Determination of Musculoskeletal Magnetic Resonance Imaging Protocol Using Deep-Learning Convolutional Neural Networks

The purposes of this study are to evaluate the feasibility of protocol determination with a convolutional neural networks (CNN) classifier based on short-text classification and to evaluate the agreements by comparing protocols determined by CNN with those determined by musculoskeletal radiologists. Following institutional review board approval, the database of a hospital information system (HIS) was queried for lists of MRI examinations, referring department, patient age, and patient gender. These were exported to a local workstation for analyses: 5258 and 1018 consecutive musculoskeletal MRI examinations were used for the training and test datasets, respectively. The subjects for pre-processing were routine or tumor protocols and the contents were word combinations of the referring department, region, contrast media (or not), gender, and age. The CNN Embedded vector classifier was used with Word2Vec Google news vectors. The test set was tested with each classification model and results were output as routine or tumor protocols. The CNN determinations were evaluated using the receiver operating characteristic (ROC) curves. The accuracies were evaluated by a radiologist-confirmed protocol as the reference protocols. The optimal cut-off values for protocol determination between routine protocols and tumor protocols was 0.5067 with a sensitivity of 92.10%, a specificity of 95.76%, and an area under curve (AUC) of 0.977. The overall accuracy was 94.2% for the ConvNet model. All MRI protocols were correct in the pelvic bone, upper arm, wrist, and lower leg MRIs. Deep-learning-based convolutional neural networks were clinically utilized to determine musculoskeletal MRI protocols. CNN-based text learning and applications could be extended to other radiologic tasks besides image interpretations, improving the work performance of the radiologist.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

L-band radar scattering from grass

A radar system based on a network analyzer has been developed to study the backscatter from vegetation. The radar is operated at L-band. Radar measurements of a grass field were made in 1991. The radar returns from the grass were measured at three incidence angles. Ground truth and canopy parameters such as blade and stem dimensions, moisture content of the grass and the soil, and blade and stem density, were measured. These parameters are used in a distorted Born approximation model to compute the backscatter coefficients from the grass layer. The model results are compared with the radar data.

Chauhan, N.↗

Assimilative modeling of low latitude ionosphere

In this paper we present an observation system simulation experiment for modeling low-latitude ionosphere using a 3-dimensional (3-D) global assimilative ionospheric model (GAIM). The experiment is conducted to test the effectiveness of GAIM with a 4-D variational approach (4DVAR) in estimation of the ExB drift and thermospheric wind in the magnetic meridional planes simultaneously for all longitude or local time sectors. The operational Global Positioning System (GPS) satellites and the ground-based global GPS receiver network of the International GPS Service are used in the experiment as the data assimilation source. 'The optimization of the ionospheric state (electron density) modeling is performed through a nonlinear least-squares minimization process that adjusts the dynamical forces to reduce the difference between the modeled and observed slant total electron content in the entire modeled region. The present experiment for multiple force estimations reinforces our previous assessment made through single driver estimations conducted for the ExB drift only.

data assimilation↗

Information-rich localization microscopy through machine learning

Recent years have witnessed the development of single-molecule localization microscopy as a generic tool for sampling diverse biologically relevant information at the super-resolution level. While current approaches often rely on the target-specific alteration of the point spread function to encode the multidimensional contents of single fluorophores, the details of the point spread function in an unmodified microscope already contain rich information. Here we introduce a data-driven approach in which artificial neural networks are trained to make a direct link between an experimental point spread function image and its underlying, multidimensional parameters, and compare results with alternative approaches based on maximum likelihood estimation. To demonstrate this concept in real systems, we decipher in fixed cells both the colors and the axial positions of single molecules in regular localization microscopy data.

42 ENGINEERING↗

Quantum Key Distribution for Critical Infrastructures: Towards Cyber-Physical Security for Hydropower and Dams

Hydropower facilities are often remotely monitored or controlled from a centralized remote control room. Additionally, major component manufacturers monitor the performance of installed components, increasingly via public communication infrastructures. While these communications enable efficiencies and increased reliability, they also expand the cyber-attack surface. Communications may use the internet to remote control a facility’s control systems, or it may involve sending control commands over a network from a control room to a machine. The content could be encrypted and decrypted using a public key to protect the communicated information. These cryptographic encoding and decoding schemes become vulnerable as more advances are made in computer technologies, such as quantum computing. In contrast, quantum key distribution (QKD) and other quantum cryptographic protocols are not based upon a computational problem, and offer an alternative to symmetric cryptography in some scenarios. Although the underlying mechanism of quantum cryptogrpahic protocols such as QKD ensure that any attempt by an adversary to observe the quantum part of the protocol will result in a detectable signature as an increased error rate, potentially even preventing key generation, it serves as a warning for further investigation. In QKD, when the error rate is low enough and enough photons have been detected, a shared private key can be generated known only to the sender and receiver. We describe how this novel technology and its several modalities could benefit the critical infrastructures of dams or hydropower facilities. The presented discussions may be viewed as a precursor to a quantum cybersecurity roadmap for the identification of relevant threats and mitigation.

97 MATHEMATICS AND COMPUTING↗

Data and programs in support of network analysis of genes and their association with diseases

The network-based approaches that were employed in order to depict the relationships between human genetic diseases and their associated genes are described. Towards this direction, monopartite disease-disease and gene-gene networks were constructed from bipartite gene-disease association networks. The latter were created by collecting and integrating data from three diverse resources, each one with different content, covering from rare monogenic disorders to common complex diseases. Moreover, topological and clustering graph analyses were performed. The methodology and the programs presented in this article are related to the research article entitled “Network analysis of genes and their association with diseases”.

Disease-disease networks↗

RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows

While in-situ workflow formulations have addressed some of the data-related challenges associated with extreme-scale scientific workflows, these workflows involve complex interactions and different modes of data exchange. In the context of increasing system complexity, such workflows present significant resource management challenges, requiring complex cost-performance tradeoffs. This paper presents RISE, an intelligent staging-based data management middleware, which builds on the DataSpaces framework and performs intelligent scheduling of data management operations to reduce I/O contention. In RISE, data are always written immediately to local buffers to reduce the effect of the transfer impact upon application performance. RISE identifies applications’ data access patterns and moves data towards data consumers only when the network is expected to be idle, reducing the impact of asynchronous background data movement upon critical data read/write requests. Here, we experimentally demonstrate that RISE can take advantage of staging nodes to offload data during writes without degrading application data movement performance.

97 MATHEMATICS AND COMPUTING↗