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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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Extraction of Tumor Site from Cancer Pathology Reports using Deep Filters
Purpose: Pathology reports are the primary source of information concerning the millions of cancer cases across the United States. Cancer registries manually process the pathology reports to extract the pertinent information including primary tumor site, behavior, histology, laterality, and grade. Processing a large volume of the pathology reports in a timely manner is a continuing challenge for cancer registries. The purpose of this study is to develop an information extraction pipeline to reliably and efficiently extract reportable information. Method: We have developed a novel inverse-regression (IR) based information extraction pipeline. The inverse-regression based supervised filter has been successfully applied to many application domains. However, its application to the information extraction from unstructured text is hindered primarily by the extreme high-dimensionality of n-gram representations of text. In this study, we attempt to overcome the obstacles by a novel bootstrapping strategy. First, we use an information-theoretic mutual information based filter to discard the excessive and redundant n-gram features. This step reduces the size and improves the condition number of the sample covariance matrix, thus reducing the computational cost and improving the numerical stability of the subsequent inverse-regression step. Then we use localized sliced inverse-regression (LSIR) to learn a low-dimensional discriminatory subspace for information inference. In particular, we use the k-nearest neighbors of an unlabeled pathology report in the learned representation to infer the desired information from the labeled data in a supervised manner. Results: The experiments were conducted on a set of de-identified pathology reports with human expert labels as the ground truth. Our pipeline consistently performed better than or comparable to the best performing state-of-the-art methods while reducing the training and inference times substantially. Conclusion: Our results demonstrate the potential of inverse-regression based information extraction pipeline for reliable and efficient information extraction from unstructured text. The information extracted from the pathology reports can be used along with clinical information, medical imaging, and genomic information to instigate discoveries in cancer research.
Low-Power Deep Learning Inference using the SpiNNaker Neuromorphic Platform.
Abstract not provided.
Deep materials informatics: Applications of deep learning in materials science
Abstract
Deep Vadose Zone Respiration Contributions to Carbon Dioxide Fluxes from a Semiarid Floodplain
Core Ideas A significant fraction of CO 2 fluxes from a semiarid floodplain originates from below the root zone. Measured and calculated field CO 2 fluxes are consistent. Laboratory‐measured respiration rates are consistent with field results. Although CO 2 fluxes from soils are often assumed to originate within shallow soil horizons (<1‐m depth), relatively little is known about respiration rates at greater depths. We compared measured and calculated CO 2 fluxes at the Rifle floodplain along the Colorado River and measured CO 2 production rates of floodplain sediments to determine the relative importance of deeper vadose zone respiration. Calculations based on measured CO 2 gradients and estimated effective diffusion coefficients yielded fluxes that are generally consistent with measurements obtained at the soil surface (326 g C m −2 yr −1 ). Carbon dioxide production from the 2.0‐ to 3.5‐m depth interval was calculated to contribute 17% of the total floodplain respiration, with rates that were larger than some parts of the shallower vadose zone and underlying aquifer. Microbial respiration rates determined from laboratory incubation tests of the sediments support this conclusion. The deeper unsaturated zone typically maintains intermediate water and air saturations, lacks extreme temperatures and salinities, and is annually resupplied with organic carbon from snowmelt‐driven recharge and by water table decline. This combination of favorable conditions supports deeper unsaturated zone microbial respiration throughout the year.
Deep morphological and spectral study of the SNR RCW 86 with Fermi-LAT
RCW 86 is a young supernova remnant (SNR) showing a shell-type structure at several wavelengths and is thought to be an efficient cosmic-ray (CR) accelerator. Earlier Fermi Large Area Telescope results reported the detection of γ-ray emission coincident with the position of RCW 86 but its origin (leptonic or hadronic) remained unclear due to the poor statistics. Thanks to 6.5 years of data acquired by the Fermi-LAT and the new event reconstruction Pass 8, we report the significant detection of spatially extended emission coming from RCW 86. The spectrum is described by a power-law function with a very hard photon index (Γ=1.42±0.1{sub stat}±0.06{sub syst}) in the 0.1–500 GeV range and an energy flux above 100 MeV of (2.91±0.8{sub stat}±0.12{sub syst}) × 10{sup −11} erg cm{sup −2} s{sup −1}. Gathering all the available multiwavelength (MWL) data, we perform a broadband modeling of the nonthermal emission of RCW 86 to constrain parameters of the nearby medium and bring new hints about the origin of the γ-ray emission. For the whole SNR, the modeling favors a leptonic scenario in the framework of a two-zone model with an average magnetic field of 10.2 ± 0.7 μG and a limit on the maximum energy injected into protons of 2 × 10{sup 49} erg for a density of 1 cm{sup −3}. In addition, parameter values are derived for the north–east and south–west (SW) regions of RCW 86, providing the first indication of a higher magnetic field in the SW region.
Contribution of deep-level defects to decreasing radiative efficiency of InGaN/GaN quantum wells with increasing emission wavelength
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A Deep Imaging Survey of NGC 6475 and a Deep Survey of the Young Open Cluster Alpha Persei
We have published three papers directly related to the x-ray data (see below), and one other paper directly related to the optical photometry obtained in connection to the ROSAT data analysis (also listed below). In addition, we have used the x-ray data in combination with the optical photometry and with high resolution optical spectra that we have obtained (to derive spectroscopic rotational velocities) to address questions related to the dependence of coronal activity on the rotation rate, mass, and other characteristics of the target stars. The overall goal of our ROSAT projects has been to determine the time evolution of coronal activity in low mass stars, and from that behavior place constraints on the physical processes involved in generating coronal activity. NGC 6475 and Alpha Persei are important parts of that process. We are now beginning to address how these data constrain theoretical models of angular momentum evolution and dynamo magnetic field generation (see paper by Stauffer et al. and Krishnamurthi et al. listed below in the "related papers" section). We are still working on two papers pertaining to this grant (rotational velocities and chromospheric activity of Alpha Persei x-ray sources and rotational velocities and lithium abundances of NGC 6475 sources), but we will publish those papers using funds from other grants.
Environmental Effects on Volcanic Eruptions:From Deep Ocean to Deep Space. Chapter 3. Volcanism and Ice Interactions on Earth and Mars
CONCLUSION Volcano/ice interactions produce meltwater. Meltwater can enter the groundwater cycle and under the influence of hydrothermal systems, it can be later discharged to form channels and valleys or cycled upward to melt permafrost. Water or ice-saturated ground can erupt into phreatic craters when covered by lava. Violent mixing of meltwater and volcanic material and rapid release can generate lahars or jokulhlaups, that have the ability to freight coarse material, great distances downslope from the vent. Eruption into meltwater generate unique appearing edifices, that are definitive indicators of volcano/ice interaction. These features are hyaloclastic ridges or mounds and if capped by lava, tuyas. On Earth, volcano/ice interactions are limited to alpine regions and ice-capped polar and temperate regions. On Mars, where precipitation may be an ancient phenomenon, these interactions may be limited to areas of ground ice accumulation or the northern lowlands where water may have ponded fairly late in martian history. The recognition of features caused by volcano/ice interactions could provide strong constraints for the history of volatiles on Mars.
Space Weather and the Tracking of Deep Space Probes by the NASA Deep Space Network (DSN): The Galileo and SOHO LASCO Experience
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Deep Space Network (DSN): Mission Services and Operations Interface for Small Deep Space Missions
No abstract available
Testing and Maturing a Mass Translating Mechanism for a Deep Space CubeSat Mechanism for a Deep Space CubeSat
No abstract available