Results for “relational databases” — Page 63

NASA NTRSDate not supplied

ARCTRON: A Rapid Experimental Proving Ground for TPS Experiments and Arcjet Technology Development

Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.

experimental diagnostics↗

NASA NTRSDate not supplied

ARCTRON: A Rapid Experimental Proving Ground for TPS Experiments and Arcjet Technology Development

Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.

experimental diagnostics↗

NASA NTRS2016

The Quality Control Algorithms Used in the Creation of NASA Kennedy Space Center Lightning Protection System Towers Meteorological Database

An accurate database of meteorological data is essential for designing any aerospace vehicle and for preparing launch commit criteria. Meteorological instrumentation were recently placed on the three Lightning Protection System (LPS) towers at Kennedy Space Center (KSC) launch complex 39B (LC-39B), which provide a unique meteorological dataset existing at the launch complex over an extensive altitude range. Data records of temperature, dew point, relative humidity, wind speed, and wind direction are produced at 40, 78, 116, and 139 m at each tower. The Marshall Space Flight Center Natural Environments Branch (EV44) received an archive that consists of one-minute averaged measurements for the period of record of January 2011 - April 2015. However, before the received database could be used EV44 needed to remove any erroneous data from within the database through a comprehensive quality control (QC) process. The QC process applied to the LPS towers' meteorological data is similar to other QC processes developed by EV44, which were used in the creation of meteorological databases for other towers at KSC. The QC process utilized in this study has been modified specifically for use with the LPS tower database. The QC process first includes a check of each individual sensor. This check includes removing any unrealistic data and checking the temporal consistency of each variable. Next, data from all three sensors at each height are checked against each other, checked against climatology, and checked for sensors that erroneously report a constant value. Then, a vertical consistency check of each variable at each tower is completed. Last, the upwind sensor at each level is selected to minimize the influence of the towers and other structures at LC-39B on the measurements. The selection process for the upwind sensor implemented a study of tower-induced turbulence. This paper describes in detail the QC process, QC results, and the attributes of the LPS towers meteorological database.

Orcutt, John M.↗

DOE OSTI2018

KM-IT Mobile Platform for D and D - 18300

Knowledge management (KM) is the practice or process responsible for gathering, analyzing, storing and sharing insights, experiences, knowledge, and information within an organization or community. The main focus of the Knowledge Management Information Tool (KM-IT) for the deactivation and decommissioning (D and D) community is to enhance safety through improved efficiencies (e.g., by reducing the need to rediscover the knowledge and experience gained over time and to promote the reuse of the existing knowledge). KM-IT serves as a centralized information repository and a common interface for D and D related activities. It facilitates the gathering, analysis, storage and sharing of knowledge and information within the D and D community. FIU has developed eight active modules as part of the web-based mobile application for the KM-IT, which can be accessed from m.dndkm.org: Vendor, Specialist Directory, Technology, Picture Library, Hotline, Lessons Learned, Best Practices and Fixatives. All of the mobile modules are scaled-down versions of the desktop module available at www.dndkm.org and publish data from the KM-IT database to the D and D community. FIU has recently developed a native mobile application for Android mobile devices for selecting D and D fixatives. This application runs natively on mobile devices and displays data through the fixative services which uses REST-based API for communication across mobile platforms. Xamarin Forms are used to develop the front-end application for the Android operating system (OS) and will be used for future platforms (iOS and Windows) as well. The native fixative application can be installed on mobile devices to search information related to fixatives, decontamination gels and strippable coatings applicable to D and D. The KM-IT platform includes a comprehensive database of commercially available fixatives and other contamination control products. Search functionality allows the user to filter and sort these products according to the search criteria or keyword. Three levels of refinement are available via a drill down menu for the criteria. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Radiation Therapy Research: A Global Analysis 2001-2015

Radiation therapy is a core modality of cancer treatment; however, concerns have been expressed regarding its underutilization and its lack of prioritization as a research domain relative to other cancer treatment modalities, despite its rapid technical evolution. It is therefore important to understand, from a public policy perspective, the evolution of global radiation therapy research, to identify strengths, weaknesses, and opportunities. This study used a bibliometric approach to undertake a quantitative analysis of global radiation therapy research published between 2001 and 2015 and available in the Web of Science (Wos) database, with particular focus on the 25 leading research-active countries. A total of 62,550 radiation therapy research articles from 127 countries, published in 2531 international journals, were analyzed. The United States was responsible for 32.3% of these outputs, followed by Japan (8.0%) and Germany (7.7%). Nearly half of all publications related to preparation and delivery of radiation therapy, combined-modality regimens, and dose fractionation studies. Health services research, palliative care, and quality of life studies represented only 2%, 5%, and 4% of all research outputs, respectively. Countries varied significantly in their commitment to different research domains, and trial-related publications represented only 5.1% of total output. Research impact was analyzed according to 3 different citation scores, with research outputs from Denmark, The Netherlands, and the United States consistently the highest ranked. Globally, radiation therapy publication outputs continue to increase but lag behind other spheres of cancer management. The types of radiation therapy research undertaken appear to be regionally patterned, and there is a clear disconcordance between the volume of research output from individual countries and its citation impact. Greater support for radiation therapy research in low- and middle-income countries is required, including international collaboration. The study findings are expected to provide the requisite knowledge to guide future radiation therapy research programs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2015

DNS and LES of turbulent flow in a closed channel featuring a pattern of hemispherical roughness elements

Three mesh adaptivity algorithms were developed to facilitate and expedite the use of the CADIS and FW-CADIS hybrid Monte Carlo/deterministic techniques in accurate full-scale neutronics simulations of fusion energy systems with immense sizes and complicated geometries. First, a macromaterial approach enhances the fidelity of the deterministic models without changing the mesh. Second, a deterministic mesh refinement algorithm generates meshes that capture as much geometric detail as possible without exceeding a specified maximum number of mesh elements. Finally, a weight window coarsening algorithm decouples the weight window mesh and energy bins from the mesh and energy group structure of the deterministic calculations in order to remove the memory constraint of the weight window map from the deterministic mesh resolution. The three algorithms were used to enhance an FW-CADIS calculation of the prompt dose rate throughout the ITER experimental facility and resulted in a 23.3% increase in the number of mesh tally elements in which the dose rates were calculated in a 10-day Monte Carlo calculation. Additionally, because of the significant increase in the efficiency of FW-CADIS simulations, the three algorithms enabled this difficult calculation to be accurately solved on a regular computer cluster, eliminating the need for a world-class super computer.

Nuclear Science & Technology↗

DOE OSTI2013

Use of genomic data in risk assessment case study: I. Evaluation of the dibutyl phthalate male reproductive development toxicity data set

A case study was conducted, using dibutyl phthalate (DBP), to explore an approach to using toxicogenomic data in risk assessment. The toxicity and toxicogenomic data sets relative to DBP-related male reproductive developmental outcomes were considered conjointly to derive information about mode and mechanism of action. In this manuscript, we describe the case study evaluation of the toxicological database for DBP, focusing on identifying the full spectrum of male reproductive developmental effects. The data were assessed to 1) evaluate low dose and low incidence findings and 2) identify male reproductive toxicity endpoints without well-established modes of action (MOAs). These efforts led to the characterization of data gaps and research needs for the toxicity and toxicogenomic studies in a risk assessment context. Further, the identification of endpoints with unexplained MOAs in the toxicity data set was useful in the subsequent evaluation of the mechanistic information that the toxicogenomic data set evaluation could provide. The extensive analysis of the toxicology data set within the MOA context provided a resource of information for DBP in attempts to hypothesize MOAs (for endpoints without a well-established MOA) and to phenotypically anchor toxicogenomic and other mechanistic data both to toxicity endpoints and to available toxicogenomic data. This case study serves as an example of the steps that can be taken to develop a toxicological data source for a risk assessment, both in general and especially for risk assessments that include toxicogenomic data.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Negative linear compressibility in common materials

Negative linear compressibility (NLC) is still considered an exotic property, only observed in a few obscure crystals. The vast majority of materials compress axially in all directions when loaded in hydrostatic compression. However, a few materials have been observed which expand in one or two directions under hydrostatic compression. At present, the list of materials demonstrating this unusual behaviour is confined to a small number of relatively rare crystal phases, biological materials, and designed structures, and the lack of widespread availability hinders promising technological applications. Using improved representations of elastic properties, this study revisits existing databases of elastic constants and identifies several crystals missed by previous reviews. More importantly, several common materials-drawn polymers, certain types of paper and wood, and carbon fibre laminates-are found to display NLC. We show that NLC in these materials originates from the misalignment of polymers/fibres. Using a beam model, we propose that maximum NLC is obtained for misalignment of 26°. The existence of such widely available materials increases significantly the prospects for applications of NLC.

36 MATERIALS SCIENCE↗

DOE OSTI2016

SU-F-J-100: Standardized Biodistribution Template for Nuclear Medicine Dosimetry Collection and Reporting

Purpose: As the field of Nuclear Medicine moves forward with efforts to integrate radiation dosimetry into clinical practice we can identify the challenge posed by the lack of standardized dose calculation methods and protocols. All personalized internal dosimetry is derived by projecting biodistribution measurements into dosimetry calculations. In an effort to standardize organization of data and its reporting, we have developed, as a sequel to the EANM recommendation of “Good Dosimetry Reporting”, a freely available biodistribution template, which can be used to create a common point of reference for dosimetry data. It can be disseminated, interpreted, and used for method development widely across the field. Methods: A generalized biodistribution template was built in a comma delineated format (.csv) to be completed by users performing biodistribution measurements. The template is available for free download. The download site includes instructions and other usage details on the template. Results: This is a new resource developed for the community. It is our hope that users will consider integrating it into their dosimetry operations. Having biodistribution data available and easily accessible for all patients processed is a strategy for organizing large amounts of information. It may enable users to create their own databases that can be analyzed for multiple aspects of dosimetry operations. Furthermore, it enables population data to easily be reprocessed using different dosimetry methodologies. With respect to dosimetry-related research and publications, the biodistribution template can be included as supplementary material, and will allow others in the community to better compare calculations and results achieved. Conclusion: As dosimetry in nuclear medicine become more routinely applied in clinical applications, we, as a field, need to develop the infrastructure for handling large amounts of data. Our organ level biodistribution template can be used as a standard format for data collection, organization, as well as for dosimetry research and software development.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

DCIS with Microinvasion: Is It In Situ or Invasive Disease?

Background: Ductal carcinoma in situ (DCIS) with microinvasion (DCISM) can be challenging in balancing the risks of overtreatment versus undertreatment. We compared DCISM, pure DCIS, and small volume (T1a) invasive ductal carcinoma (IDC) as related to histopathology, treatment patterns, and survival outcomes. Methods: Women ages 18–90 years who underwent breast surgery for DCIS, DCISM, or T1a IDC were selected from the SEER Database (2004–2015). Multivariate logistic regression and Cox proportional hazards models were used to estimate the association of diagnosis with treatment and survival, respectively. Results: A total of 134,569 women were identified: 3.2% DCISM, 70.9% DCIS, and 25.9% with T1a IDC. Compared with invasive disease, DCISM was less likely to be ER+ or PR+ and more likely to be HER2+. After adjustment, DCIS and invasive patients were less likely to undergo mastectomy than DCISM patients (DCIS: OR 0.53, 95% CI 0.49–0.56; invasive: OR 0.86, CI 0.81–0.92). For those undergoing lumpectomy, the likelihood of receiving radiation was similar for DCISM and invasive patients but lower for DCIS patients (OR 0.57, CI 0.52–0.63). After adjustment, breast-cancer-specific survival was significantly different between DCISM and the other two groups (DCIS: HR 0.59, CI 0.43–0.8; invasive: HR 1.43, CI 1.04–1.96). However, overall survival was not significantly different between DCISM and invasive disease, whereas patients with DCIS had improved OS (HR 0.83, CI 0.75–0.93). Conclusions: Although DCISM is a distinct entity, current treatment patterns and prognosis are comparable to those with small volume IDC. These findings may help providers counsel patients and determine appropriate treatment plans.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

Synthetic Aperture Radar Image Geolocation Using Fiducial Images

Synthetic Aperture Radar (SAR) creates imagery of the earth’s surface from airborne or spaceborne radar platforms. However, the nature of any radar is to geolocate its echo data, i.e., SAR images, relative to its own measured radar location. Acceptable accuracy and precision of such geolocation can be quite difficult to achieve, and is limited by any number of parameters. However, databases of geolocated earth imagery do exist, often using other imaging modalities, with Google Earth being one such example. These can often be much more accurate than what might be achievable by the radar itself. Consequently, SAR images may be aligned to some higher accuracy database, thereby improving the geolocation of features in the SAR image. Examples offer anecdotal evidence of the viability of such an approach.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Mining Thermophile Photosynthesis Genes: A Synthetic Operon Expressing Chloroflexota Species Reaction Center Genes in Rhodobacter sphaeroides

Photosynthesis is the foundation of the vast majority of life systems, and is therefore the most important bioenergetic process on earth. The greatest diversity of photosynthetic systems is found in microorganisms. However, our understanding of the biophysical and biochemical processes that transduce light into chemical energy is derived from a relatively small subset of proteins from microbes that are amenable to cultivation, in contrast to the huge number of predicted proteins that catalyze the initial photochemical reactions deposited in databases, such as from metagenomics. We describe the use of a Rhodobacter sphaeroides laboratory strain for the expression of heterologous photosynthesis genes to demonstrate the feasibility of mining this resource, focusing on hot spring Chloroflexota gene sequences. Using a synthetic operon of genes, we produced a photochemically active complex of reaction center proteins in our biological system. We also present bioinformatic analyses of anoxygenic type II reaction center sequences from metagenomic samples collected from hot (42–90 °C) springs available through the JGI IMG database, to generate a resource of diverse sequences that are potentially adapted to photosynthesis at such temperatures. These data provide a view into the natural diversity of anoxygenic photosynthesis, through a lens focused on high-temperature environments. The approach we took to express such genes can be applied for potential biotechnology purposes as well as for studies of fundamental catalytic properties of these heretofore inaccessible protein complexes.

Chloroflexota↗

DOE OSTI2016

gPhoton: THE GALEX PHOTON DATA ARCHIVE

gPhoton is a new database product and software package that enables analysis of GALEX ultraviolet data at the photon level. The project’s stand-alone, pure-Python calibration pipeline reproduces the functionality of the original mission pipeline to reduce raw spacecraft data to lists of time-tagged, sky-projected photons, which are then hosted in a publicly available database by the Mikulski Archive at Space Telescope. This database contains approximately 130 terabytes of data describing approximately 1.1 trillion sky-projected events with a timestamp resolution of five milliseconds. A handful of Python and command-line modules serve as a front end to interact with the database and to generate calibrated light curves and images from the photon-level data at user-defined temporal and spatial scales. The gPhoton software and source code are in active development and publicly available under a permissive license. We describe the motivation, design, and implementation of the calibration pipeline, database, and tools, with emphasis on divergence from prior work, as well as challenges created by the large data volume. We summarize the astrometric and photometric performance of gPhoton relative to the original mission pipeline. For a brief example of short time-domain science capabilities enabled by gPhoton, we show new flares from the known M-dwarf flare star CR Draconis. The gPhoton software has permanent object identifiers with the ASCL (ascl:1603.004) and DOI (doi:10.17909/T9CC7G). This paper describes the software as of version v1.27.2.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

The Yale–Potsdam Stellar Isochrones

We introduce the Yale–Potsdam Stellar Isochrones (YaPSI), a new grid of stellar evolution tracks and isochrones of solar-scaled composition. In an effort to improve the Yonsei–Yale database, special emphasis is placed on the construction of accurate low-mass models (M{sub ∗}<0.6 M{sub ⊙}), and in particular on their mass–luminosity and mass–radius relations, both crucial for characterizing exoplanet-host stars, and, in turn, their planetary systems. The YaPSI models cover the mass range 0.15–5.0 M{sub ⊙} densely enough to permit detailed interpolation in mass, and the metallicity and helium abundance ranges [Fe/H] = −1.5 to +0.3 and Y {sub 0} = 0.25–0.37 are specified independently of each other (i.e., no fixed ΔY/ΔZ relation is assumed). The evolutionary tracks are calculated from the pre-main sequence up to the tip of the red giant branch. The isochrones, with ages between 1 Myr and 20 Gyr, provide UBVRI colors in the Johnson–Cousins system, and JHK colors in the homogenized Bessell and Brett system, derived from two different semi-empirical T{sub eff}–color calibrations from the literature. We also provide utility codes, such as an isochrone interpolator, in age, metallicity, and helium content, and an interface of the tracks with an open-source Monte Carlo Markov-Chain tool for the analysis of individual stars. Finally, we present comparisons of the YaPSI models with the best empirical mass–luminosity and mass–radius relations available to date, as well as isochrone fitting of well-studied stellar clusters.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Working Party on International Nuclear Data Evaluation Cooperation (WPEC)

The OECD Nuclear Energy Agency (NEA) is organizing the cooperation between the major nuclear data evaluation projects in the world. The NEA Working Party on International Nuclear Data Evaluation Cooperation (WPEC) was established to promote the exchange of information on nuclear data evaluation, measurement, nuclear model calculation, validation, and related topics, and to provide a framework for cooperative activities between the participating projects. The working party assesses nuclear data improvement needs and addresses these needs by initiating joint activities in the framework of dedicated WPEC subgroups. Studies recently completed comprise a number of works related to nuclear data covariance and associated processing issues, as well as more specific studies related to the resonance parameter representation in the unresolved resonance region, the gamma production from fission-product capture reactions, the U-235 capture cross-section, the EXFOR database, and the improvement of nuclear data for advanced reactor systems. Ongoing activities focus on the evaluation of Pu-239 in the resonance region, scattering angular distribution in the fast energy range, and reporting/usage of experimental data for evaluation in the resolved resonance region. New activities include two new subgroups on improved fission product yield evaluation methodologies and on modern nuclear database structures. Future activities under discussion include a pilot project of a Collaborative International Evaluated Library (CIELO) and methods to provide feedback from nuclear and covariance data adjustment for improvement of nuclear data. In addition to the above mentioned short-term, task-oriented subgroups, the WPEC also hosts a longer-term subgroup charged with reviewing and compiling the most important nuclear data requirements in a high priority request list (HPRL).

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

A Knowledge Network-Based Approach to Facilitate Annotation of Clinical Pathway Component Clusters

Mining electronic health records (EHRs) to identify contextually related clinical concept clusters that tend to co-occur temporarily and consistently could improve data-driven clinical pathway (CP) construction. However, the automatic extraction of contextually related clinical concept clusters contains a vast amount of irrelevant information. Hence, this paper proposes a knowledge network-enabled literature-based discovery (LBD) approach to remove noise from clusters. The authors used published literature to filter spurious concepts from the clusters and used data from the US Department of Veterans Affairs’s major depressive disorder (MDD) cohort of Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF) for their experimentation. The approach was applied to 2,967 clusters extracted from the MDD OEF/OIF database. The experimental results demonstrate that the proposed approach can filter 94% of the irrelevant information. Moreover, the authors applied various network mining algorithms to analyze the clusters and demonstrated that LBD, along with network mining techniques, is a useful method for finding accurate contextually related clinical concept clusters. This could help domain researchers perform advanced analytics in CPs.

Hasan, S M Shamimul↗

NASA NTRS1990

Information analysis of a spatial database for ecological land classification

An ecological land classification was developed for a complex region in southern California using geographic information system techniques of map overlay and contingency table analysis. Land classes were identified by mutual information analysis of vegetation pattern in relation to other mapped environmental variables. The analysis was weakened by map errors, especially errors in the digital elevation data. Nevertheless, the resulting land classification was ecologically reasonable and performed well when tested with higher quality data from the region.

Davis, Frank W.↗

DOE OSTI2018

A mathematical discussion concerning the performance of multilayer perceptron-type artificial neural networks through use of orthogonal bipolar vectors

This work proposes the use of orthogonal bipolar vectors (OBV) as targets for multilayer perceptron (MLP) Artificial neural networks pertaining to the pattern recognition field. Implications involving this proposal are supported by a proper mathematical discussion. This study shows that the use of OBV as targets improves the class identification performance of MLP networks for pattern recognition with more than two classes when compared to the widely used conventional target bipolar vector (CBV). In addition to the overall performance improvement, it is possible to obtain high recognition rates with fewer training epochs, while keeping a feasible generalization with other data. This behavior is related to the Euclidean distance of the points in the output space, which is much higher in the case of OBVs. Therefore, with a greater distance between the points in the output space, the MLP network becomes less prone to associate trained outputs with incorrect targets. The mathematical discussion in this study is based on the backpropagation training algorithm. In addition to the mathematical discussion, results from experiments with real data are presented. These results follow those obtained by mathematical derivations. Real data sets used in the experiments are available from: (a) the Semeion Handwritten Digit of Machine Learning Repository, international repository; (b) Iris Image Database from the Chinese Academy of Sciences—CASIA; (c) Australian Sign Language, signs of Machine Learning Repository, international repository. Experiments were conducted to measure the mean Euclidean distance between the MLP network output subjected to a given input pattern and outputs related to other pattern classifications. Experimental results show that MLP networks trained with OBVs were able to ensure a Euclidean distance between the output and incorrect targets greater than MLP networks trained with CBVs (by up to 4 times for handwritten, by up to 12 times for iris images and by up to 10 times for Auslan signs language). As such, the adoption of OBVs as target vectors for MLPs reduces the computational effort for training the network.

97 MATHEMATICS AND COMPUTING↗