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At least 685 records · Page 38

Relating OGO-5 H(+) Plasmapause Transitions to Mid-Latitude Topside-Ionospheric Signatures

Plasmapause transitions, as seen in the H + and He+ density gradients measured by the Orbiting Geophysical Observatory 5 (OGO 5) ion spectrometer [Sharp, IEE Trans. in Geosci. Elect., 1969], have been investigated in an attempt to relate them to their topside ionospheric signatures as seen in the Alouette-1 & 2 and ISIS-1 data. The satellite data were obtained from the National Space Science Data Center (NSSDC). A search of the OGO-5 data revealed 54 sharp plasmapause crossings as evaluated from the H+ density. The ionospheric footprints (at 1400 km altitude) of the magnetic-field lines through the locations of these plasmapause crossings were then used to search for topside ionospheric electron-density profiles from the NSSDC. No profiles corresponding to these projections were identified. A similar search of the topside-sounder 35-mm ionogram-film database, however, identified 17 cases of candidate "conjunctions" involving Alouette l & 2 and ISIS 1. We will present samples of the plasmapause OGO-5 ion transitions and the related topside ionospheric signatures and discuss the observations in relation to the recent similar study based on Explorer-45 and ISIS-2 data [Grebowsky et al., JASTP, 2009].

Truhlik, Vladimir↗

Aviation Trends Related to Atmospheric Environment Safety Technologies Project Technical Challenges

Current and future aviation safety trends related to the National Aeronautics and Space Administration's Atmospheric Environment Safety Technologies Project's three technical challenges (engine icing characterization and simulation capability; airframe icing simulation and engineering tool capability; and atmospheric hazard sensing and mitigation technology capability) were assessed by examining the National Transportation Safety Board (NTSB) accident database (1989 to 2008), incidents from the Federal Aviation Administration (FAA) accident/incident database (1989 to 2006), and literature from various industry and government sources. The accident and incident data were examined for events involving fixed-wing airplanes operating under Federal Aviation Regulation (FAR) Parts 121, 135, and 91 for atmospheric conditions related to airframe icing, ice-crystal engine icing, turbulence, clear air turbulence, wake vortex, lightning, and low visibility (fog, low ceiling, clouds, precipitation, and low lighting). Five future aviation safety risk areas associated with the three AEST technical challenges were identified after an exhaustive survey of a variety of sources and include: approach and landing accident reduction, icing/ice detection, loss of control in flight, super density operations, and runway safety.

Reveley, Mary S.↗

Data management for community research projects: A JGOFS case study

Since the mid 1980s, much of the marine science research effort in the United Kingdom has been focused into large scale collaborative projects involving public sector laboratories and university departments, termed Community Research Projects. Two of these, the Biogeochemical Ocean Flux Study (BOFS) and the North Sea Project incorporated large scale data collection to underpin multidisciplinary modeling efforts. The challenge of providing project data sets to support the science was met by a small team within the British Oceanographic Data Centre (BODC) operating as a topical data center. The role of the data center was to both work up the data from the ship's sensors and to combine these data with sample measurements into online databases. The working up of the data was achieved by a unique symbiosis between data center staff and project scientists. The project management, programming and data processing skills of the data center were combined with the oceanographic experience of the project communities to develop a system which has produced quality controlled, calibrated data sets from 49 research cruises in 3.5 years of operation. The data center resources required to achieve this were modest and far outweighed by the time liberated in the scientific community by the removal of the data processing burden. Two online project databases have been assembled containing a very high proportion of the data collected. As these are under the control of BODC their long term availability as part of the UK national data archive is assured. The success of the topical data center model for UK Community Research Project data management has been founded upon the strong working relationships forged between the data center and project scientists. These can only be established by frequent personal contact and hence the relatively small size of the UK has been a critical factor. However, projects covering a larger, even international scale could be successfully supported by a network of topical data centers managing online databases which are interconnected by object oriented distributed data management systems over wide area networks.

Lowry, Roy K.↗

Forward Modeling of Atmospheric Carbon Dioxide in GEOS-5: Uncertainties Related to Surface Fluxes and Sub-Grid Transport

Forward GEOS-5 AGCM simulations of CO2, with transport constrained by analyzed meteorology for 2009-2010, are examined. The CO2 distributions are evaluated using AIRS upper tropospheric CO2 and ACOS-GOSAT total column CO2 observations. Different combinations of surface C02 fluxes are used to generate ensembles of runs that span some uncertainty in surface emissions and uptake. The fluxes are specified in GEOS-5 from different inventories (fossil and biofuel), different data-constrained estimates of land biological emissions, and different data-constrained ocean-biology estimates. One set of fluxes is based on the established "Transcom" database and others are constructed using contemporary satellite observations to constrain land and ocean process models. Likewise, different approximations to sub-grid transport are employed, to construct an ensemble of CO2 distributions related to transport variability. This work is part of NASA's "Carbon Monitoring System Flux Pilot Project,"

Pawson, Steven↗

K-RET: knowledgeable biomedical relation extraction system

Abstract Motivation Relation extraction (RE) is a crucial process to deal with the amount of text published daily, e.g. to find missing associations in a database. RE is a text mining task for which the state-of-the-art approaches use bidirectional encoders, namely, BERT. However, state-of-the-art performance may be limited by the lack of efficient external knowledge injection approaches, with a larger impact in the biomedical area given the widespread usage and high quality of biomedical ontologies. This knowledge can propel these systems forward by aiding them in predicting more explainable biomedical associations. With this in mind, we developed K-RET, a novel, knowledgeable biomedical RE system that, for the first time, injects knowledge by handling different types of associations, multiple sources and where to apply it, and multi-token entities. Results We tested K-RET on three independent and open-access corpora (DDI, BC5CDR, and PGR) using four biomedical ontologies handling different entities. K-RET improved state-of-the-art results by 2.68% on average, with the DDI Corpus yielding the most significant boost in performance, from 79.30% to 87.19% in F-measure, representing a P-value of 2.91×10−12. Availability and implementation https://github.com/lasigeBioTM/K-RET.

Sousa, Diana F. (ORCID:0000000305979273)↗

Obstructive Sleep Apnea Among Army Aircrew

INTRODUCTION: Obstructive sleep apnea (OSA) is a condition characterized by disrupted sleep and excessive daytime fatigue. Associated cognitive and psychomotor decrements pose a threat to aviators’ performance and flight safety. Additionally, the longer term health effects associated with the disease can jeopardize an aviator’s career and negatively impact operational outputs. This study reviews OSA prevalence, related comorbid conditions in Army aviators, and analyzes the aeromedical dispositions of affected individuals. METHODS: The U.S. Army Aeromedical Electronic Resource Office (AERO) database was interrogated for all cases of OSA from June 2005 through June 2015 using ICD-9 code 327.23. Prevalence rates for OSA and other comorbid conditions were then calculated using the total number of aviators in the AERO database. RESULTS: A total of 663 unique instances of OSA were found among the aviator population ( N = 24,568), giving a point prevalence of 2.69%. Four cases affected women. Mean age of initial presentation was 42.62 yr and mean Body Mass Index was 28.69. The top five most prevalent comorbid conditions were hypertension, lumbago, degeneration of a lumbar or lumbosacral intervertebral disc, PTSD, and testicular hypofunction. DISCUSSION: Prevalence of OSA among aviators is lower than the general population but is not uncommon. A positive diagnosis requires a waiver or can result in suspension if not managed effectively, potentially leading to a reduction in aviator numbers. Aggressive health promotion and robust medical surveillance and aeromedical disposition management by the aeromedical community is essential to reduce OSA numbers, maintain aviator health, and maximize flight safety. Goldie C, Stork B, Bernhardt K, Gaydos SJ, Kelley AM. Obstructive sleep apnea among army aircrew . Aerosp Med Hum Perform. 2022; 93(5):415–420.

Biophysics↗

Periodicity of the earth's magnetic reversals

Results are presented from an attempt to perform a relatively comprehensive analysis of the evidence for a periodicity, with harmonics, of the observed regular reversals of the earth's magnetic field. The database considered covers 296 reversals over the past 165 Myr. Histograms with bins 1 Myr apart reveal only 30 Myr reversal patterns. The reversal dates are fitted to a linear periodic function and a spectrum is computed for the residuals at the adopted dates. The possible presence of multiple periodicities is evaluated and over various time intervals. The analysis shows that a recently observed 15 Myr periodicity is probably a harmonic of the 29.5-30.5 Myr period. The calculations do not confirm an inherent magnetic reversal property of the earth. The reversals may arise from tectonic events or from impacts from extraterrestrial objects.

Stothers, R. B.↗

Constraining Clouds and Convective Parameterizations in A Climate Model Using Paleoclimate Data

Cloud and convective parameterizations strongly influence uncertainties in equilibrium climate sensitivity. We provide a proof-of-concept study to constrain these parameterizations in a perturbed parameter ensemble of the atmosphere-only version of the Goddard Institute for Space Studies Model E2.1 simulations by evaluating model biases in the present-day runs using multiple satellite climatologies and by comparing simulated δ 18 O of precipitation (δ 18 O p ), known to be sensitive to parameterization schemes, with a global database of speleothem δ 18 O records covering the Last Glacial Maximum (LGM), mid-Holocene (MH) and pre-industrial (PI) periods. Relative to modern interannual variability, paleoclimate simulations show greater sensitivity to parameter changes, allowing for an evaluation of model uncertainties over a broader range of climate forcing and the identification of parts of the world that are parameter sensitive. Certain simulations reproduced absolute δ 18 O p values across all time periods, along with LGM and MH δ 18 O p anomalies relative to the PI, better than the default parameterization. No single set of parameterizations worked well in all climate states, likely due to the non-stationarity of cloud feedbacks under varying boundary conditions. Future work that involves varying multiple parameter sets simultaneously with coupled ocean feedbacks will likely provide improved constraints on cloud and convective parameterizations.

cloud and convective parameterization↗

Assessment Framework of Marine Hydrokinetic Technologies for Microgrid Applications

Communities in Alaska that are not connected to a regional grid (referred to hereafter as grid-islanded Alaskan communities) rely heavily on stand-alone generators with imported diesel fuel as the primary source of energy. Several of these grid-islanded Alaskan communities have the potential to harness significant wave, tidal, and hydrokinetic power; many also have hydropower or wind potential that could complement these resources. The implementation of marine and hydrokinetic energy focused microgrids in these communities would diversify their energy profiles, with the potential in many communities to keep costs flat while reducing dependance on diesel. This would enhance resilience and reduce environmental impacts. This seedling proposal will systematically identify grid-islanded coastal communities in Alaska with wave, tidal, and hydrokinetic energy potential to add fuel diversity to generation, applying microgrid integration methods and strategies that will meet the community’s needs. This proposal is in partnership with the Alaska Center for Energy and Power (ACEP) and XENDEE Corporation who bring extensive expertise in Alaskan communities and microgrid technoeconomic assessment, respectively. This project will deliver: (1) a database of grid-islanded communities that are candidates for MHK based microgrids, (2) an assessment of possible microgrid integration methods and strategies related to tidal, wave, and hydrokinetic technologies, and (3) a MHK development plan for the XENDEE Microgrid design platform and planning tool that can serve these grid-islanded communities and project developers. In the final stage, the planning tool will allow for the comprehensive comparison between diesel based and MHK based renewable generation.

16 TIDAL AND WAVE POWER↗

Information access in a dual-task context: testing a model of optimal strategy selection

Pilots were required to access information from a hierarchical aviation database by navigating under single-task conditions (Experiment 1) and when this task was time-shared with an altitude-monitoring task of varying bandwidth and priority (Experiment 2). In dual-task conditions, pilots had 2 viewports available, 1 always used for the information task and the other to be allocated to either task. Dual-task strategy, inferred from the decision of which task to allocate to the 2nd viewport, revealed that allocation was generally biased in favor of the monitoring task and was only partly sensitive to the difficulty of the 2 tasks and their relative priorities. Some dominant sources of navigational difficulties failed to adaptively influence selection strategy. The implications of the results are to provide tools for jumping to the top of the database, to provide 2 viewports into the common database, and to provide training as to the optimum viewport management strategy in a multitask environment.

User-Computer Interface↗

Survey of standards applicable to a database management system

Industry, government, and NASA standards, and the status of standardization activities of standards setting organizations applicable to the design, implementation and operation of a data base management system for space related applications are identified. The applicability of the standards to a general purpose, multimission data base management system is addressed.

Urena, J. L.↗

A rule-free workflow for the automated generation of databases from scientific literature

Abstract In recent times, transformer networks have achieved state-of-the-art performance in a wide range of natural language processing tasks. Here we present a workflow based on the fine-tuning of BERT models for different downstream tasks, which results in the automated extraction of structured information from unstructured natural language in scientific literature. Contrary to existing methods for the automated extraction of structured compound-property relations from similar sources, our workflow does not rely on the definition of intricate grammar rules. Hence, it can be adapted to a new task without requiring extensive implementation efforts and knowledge. We test our data-extraction workflow by automatically generating a database for Curie temperatures and one for band gaps. These are then compared with manually curated datasets and with those obtained with a state-of-the-art rule-based method. Furthermore, in order to showcase the practical utility of the automatically extracted data in a material-design workflow, we employ them to construct machine-learning models to predict Curie temperatures and band gaps. In general, we find that, although more noisy, automatically extracted datasets can grow fast in volume and that such volume partially compensates for the inaccuracy in downstream tasks.

36 MATERIALS SCIENCE↗

What Machine Learning Can and Cannot Do for Inertial Confinement Fusion

Machine learning methodologies have played remarkable roles in solving complex systems with large data, well-defined input–output pairs, and clearly definable goals and metrics. The methodologies are effective in image analysis, classification, and systems without long chains of logic. Recently, machine-learning methodologies have been widely applied to inertial confinement fusion (ICF) capsules and the design optimization of OMEGA (Omega Laser Facility) capsule implosion and NIF (National Ignition Facility) ignition capsules, leading to significant progress. As machine learning is being increasingly applied, concerns arise regarding its capabilities and limitations in the context of ICF. ICF is a complicated physical system that relies on physics knowledge and human judgment to guide machine learning. Additionally, the experimental database for ICF ignition is not large enough to provide credible training data. Most researchers in the field of ICF use simulations, or a mix of simulations and experimental results, instead of real data to train machine learning models and related tools. They then use the trained learning model to predict future events. This methodology can be successful, subject to a careful choice of data and simulations. However, because of the extreme sensitivity of the neutron yield to the input implosion parameters, physics-guided machine learning for ICF is extremely important and necessary, especially when the database is small, the uncertain-domain knowledge is large, and the physical capabilities of the learning models are still being developed. In this work, we identify problems in ICF that are suitable for machine learning and circumstances where machine learning is less likely to be successful. This study investigates the applications of machine learning and highlights fundamental research challenges and directions associated with machine learning in ICF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Target–decoy false discovery rate estimation using Crema

Assigning statistical confidence estimates to discoveries produced by a tandem mass spectrometry proteomics experiment is critical to enabling principled interpretation of the results and assessing the cost/benefit ratio of experimental follow-up. The most common technique for computing such estimates is to use target-decoy competition (TDC), in which observed spectra are searched against a database of real (target) peptides and a database of shuffled or reversed (decoy) peptides. TDC procedures for estimating the false discovery rate (FDR) at a given score threshold have been developed for application at the level of spectra, peptides, or proteins. Although these techniques are relatively straightforward to implement, it is common in the literature to skip over the implementation details or even to make mistakes in how the TDC procedures are applied in practice. Here we present Crema, an open-source Python tool that implements several TDC methods of spectrum-, peptide- and protein-level FDR estimation. Crema is compatible with a variety of existing database search tools and provides a straightforward way to obtain robust FDR estimates.

59 BASIC BIOLOGICAL SCIENCES↗

Near-Earth Solar Wind Flows and Related Geomagnetic Activity During more than Four Solar Cycles (1963-2011)

In past studies, we classified the near-Earth solar wind into three basic flow types based on inspection of solar wind plasma and magnetic field parameters in the OMNI database and additional data (e.g., geomagnetic indices, energetic particle, and cosmic ray observations). These flow types are: (1) High-speed streams associated with coronal holes at the Sun, (2) Slow, interstream solar wind, and (3) Transient flows originating with coronal mass ejections at the Sun, including interplanetary coronal mass ejections and the associated upstream shocks and post-shock regions. The solar wind classification in these previous studies commenced with observations in 1972. In the present study, as well as updating this classification to the end of 2011, we have extended the classification back to 1963, the beginning of near-Earth solar wind observations, thereby encompassing the complete solar cycles 20 to 23 and the ascending phase of cycle 24. We discuss the cycle-to-cycle variations in near-Earth solar wind structures and l1e related geomagnetic activity over more than four solar cycles, updating some of the results of our earlier studies.

Richardson, Ian G.↗

A method for generating quantitative vapor-phase infrared spectra of solids: results for phenol, camphor, menthol, syringol, dicyclopentadiene and naphthalene

Here, a method is presented to generate quantitative vapor-phase infrared spectra from substances that naturally occur as solids with moderate volatility. The solid is gravimetrically dissolved into a solvent that has few infrared spectral features, typically CS 2 and CCl 4 separately. The solution is flowed at a constant rate from a linearly pumped syringe into a metered stream of nitrogen carrier gas regulated by a mass flow controller. The analyte/solvent mix is flash vaporized by volatilizing the solution across a heated stainless-steel surface as it emanates from the syringe tip. The N 2 gas-solution mixture is flowed into a long-path White cell thermostatted at a desired temperature, the long optical path compensating for the modest analyte mixing ratio. A composite spectrum is generated from typically ten or more 760-Torr pressure-broadened spectra over the 600 to 6500 cm -1 spectral range at 0.1 cm -1 spectral resolution. The solid analytes reported here using this novel technique include dicyclopentadiene, menthol, syringol, phenol, camphor, and naphthalene.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Global patterns of terrestrial nitrogen and phosphorus limitation

Nitrogen (N) and phosphorus (P) limitation constrains the magnitude of terrestrial carbon uptake in response to elevated carbon dioxide and climate change. However, global maps of nutrient limitation are still lacking. Here we examined global N and P limitation using the ratio of site-averaged leaf N and P resorption efficiencies of the dominant species across 171 sites. We evaluated our predictions using a global database of N- and P-limitation experiments based on nutrient additions at 106 and 53 sites, respectively. Globally, we found a shift from relative P to N limitation for both higher latitudes and precipitation seasonality and lower mean annual temperature, temperature seasonality, mean annual precipitation and soil clay fraction. Excluding cropland, urban and glacial areas, we estimate that 18% of the natural terrestrial land area is significantly limited by N, whereas 43% is relatively P limited. The remaining 39% of the natural terrestrial land area could be co-limited by N and P or weakly limited by either nutrient alone. This work provides both a new framework for testing nutrient limitation and a benchmark of N and P limitation for models to constrain predictions of the terrestrial carbon sink.

58 GEOSCIENCES↗

Quality Assurance of the Irradiated EBR-II Metallic Fuels Data

The U.S. DOE-NE’s Advanced Reactor Technologies (ART) Fast Reactor Program (FRP) and the NE-4 Advanced Fuels Campaign (AFC) have jointly undertaken efforts to qualify post-irradiation examination (PIE) data for Experimental Breeder Reactor II (EBR-II) and Fast Flux Test Facility (FFTF) metallic fuels. Among the thousands of PIE datasets in the Metallic Fuels Irradiation & Physics Database (FIPD), data from selected EBR-II experiments have been prioritized as the most valuable to the U.S. nuclear industry for licensing activities related to metallic fuel-based advanced fast reactors. This report summarizes the general data qualification progress of the EBR-II and FFTF experiments, with focus on the selected EBR-II experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗