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At least 199 records · Page 11

Using Natural Language Processing of Free-Text Radiology Reports to Identify Type 1 Modic Endplate Changes

Electronic medical record (EMR) systems provide easy access to radiology reports and offer great potential to support quality improvement efforts and clinical research. Harnessing the full potential of the EMR requires scalable approaches such as natural language processing (NLP) to convert text into variables used for evaluation or analysis. Our goal was to determine the feasibility of using NLP to identify patients with Type 1 Modic endplate changes using clinical reports of magnetic resonance (MR) imaging examinations of the spine. Identifying patients with Type 1 Modic change who may be eligible for clinical trials is important as these findings may be important targets for intervention. Four annotators identified all reports that contained Type 1 Modic change, using N = 458 randomly selected lumbar spine MR reports. We then implemented a rule-based NLP algorithm in Java using regular expressions. The prevalence of Type 1 Modic change in the annotated dataset was 10%. Results were recall (sensitivity) 35/50 = 0.70 (95% confidence interval (C.I.) 0.52–0.82), specificity 404/408 = 0.99 (0.97–1.0), precision (positive predictive value) 35/39 = 0.90 (0.75–0.97), negative predictive value 404/419 = 0.96 (0.94–0.98), and F1-score 0.79 (0.43–1.0). Our evaluation shows the efficacy of rule-based NLP approach for identifying patients with Type 1 Modic change if the emphasis is on identifying only relevant cases with low concern regarding false negatives. As expected, our results show that specificity is higher than recall. This is due to the inherent difficulty of eliciting all possible keywords given the enormous variability of lumbar spine reporting, which decreases recall, while availability of good negation algorithms improves specificity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Department of Energy – Office of Science: Pacific Northwest Site Office Environmental Monitoring Plan for the DOE-SC PNNL Site

The Pacific Northwest Site Office (PNSO) manages the contract for operations at the U.S. Department of Energy Office of Science (DOE-SC) Pacific Northwest National Laboratory (PNNL) Site in Richland, Washington. Radiological operations at the DOE-SC PNNL Site expanded in 2010 with the completion of facilities at the Physical Sciences Facility. As a result of the expanded radiological work at the site, the Washington State Department of Health (WDOH) has required that offsite environmental surveillance be conducted as part of the PNNL Site Radioactive Air Emissions License. The environmental monitoring and surveillance requirements of various orders, regulations, and guidance documents consider emission levels and subsequent risk of negative human and environmental impacts. This Environmental Monitoring Plan (EMP) describes air surveillance activities at the DOE-SC PNNL Site. The determination of offsite environmental surveillance needs evolved out of a Data Quality Objectives process (Barnett et al. 2010) and Implementation Plan (Snyder et al. 2010). The entire EMP is a compilation of several documents, which include: - the Main Document, this text, (PNNL-20919), - Attachment 1, Sampling and Analysis Plan (SAP) (PNNL-20919-1), - Attachment 2, Data Management Plan (DMP) (PNNL-20919-2), and - Attachment 3, Dose Assessment Guidance (DAG) (PNNL-20919-3). Although the EMP is considered the compilation of these documents, each covers topics that can be updated independently. As a result, each may have different publication dates. Current version dates can be verified with Effluent Management staff. The procedures, forms, and data management activities described herein may change with radiological research projects at the DOE-SC PNNL Site. The scope of this EMP will evolve as needed, during routine reviews or in response to changes in facility operations. This document provides the SAP, DMP, and DAG effective at the time of publication. Updates to this document will be published at the discretion of the Effluent Management group of PNNL.

54 ENVIRONMENTAL SCIENCES↗

User's Manual for RESRAD-BUILD Code Version 4: Vol. 2 - User's Guide for RESRAD-BUILD Code Version 4

The RESRAD-BUILD computer code is designed to assess radiological doses to individuals who live or work in a building contaminated with radioactive material. The code is equipped with a user-friendly interface that has many features to facilitate using the computer code and understanding the results. The design of the interface provides various options, from entering data and performing calculations to displaying calculation results. General and context-specific help are available, providing information on editing and viewing the radionuclide database, the definitions of input parameters and their use in the calculations, and the selection of the calculation results for placement into other applications. Two types of sensitivity analysis are supported by the code, i.e., deterministic and probabilistic, that can be used to study the influence of input parameters on the calculation results. This user’s guide provides instructions to help users on how to install the RESRAD-BUILD code, navigate the interface, and use the various features to set up a dose/risk analysis and to view/print the results in text and graphical outputs.

61 RADIATION PROTECTION AND DOSIMETRY↗

Constraints on neutrino lifetime from the Sudbury Neutrino Observatory

The long baseline between Earth and the Sun makes solar neutrinos an excellent test beam for exploring possible neutrino decay. The signature of such decay would be an energy-dependent distortion of the traditional survival probability which can be fit for using well-developed and high-precision analysis methods. Here a model including neutrino decay is fit to all three phases of $^{8}\mathrm{B}$ solar neutrino data taken by the Sudbury Neutrino Observatory (SNO). This fit constrains the lifetime of neutrino mass state ${{\nu}}_{2}$ to be > $8.08\times{}{10}^{{-}5}\text{ }\text{ }\mathrm{s}/\mathrm{eV}$ at 90% confidence. An analysis combining this SNO result with those from other solar neutrino experiments results in a combined limit for the lifetime of mass state ${{\nu}}_{2}$ of > $1.92\times{}{10}^{{-}3}\text{ }\text{ }\mathrm{s}/\mathrm{eV}$ at 90% confidence.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DeepPDF: A Deep Learning Approach to Extracting Text from PDFs

Scientific publications contain a plethora of important information, not only for researchers but also for their managers and institutions. Many researchers try to collect and extract this information in large enough quantities that it requires machine automation, but because publications were historically intended for print and not machine consumption, the digital document formats used today (primarily PDF) have created many hurdles for text extraction. Primarily, tools have relied on trying to convert PDF's to plain text documents for machine processing by reverse engineering the PDF standard. A complex process because once a PDF is created it is more closely related to an image file than a document markup language. In this paper we explore the feasibility of treating these PDF documents as images as opposed to a proprietary markup language. We believe that by using deep learning and image analysis we can create more accurate PDF to text extraction tools than those that currently exist. \\ \newline \Keywords{deep learning, text extraction, information extraction, PDF extraction, scholarly publications.

Stahl, Christopher↗

MacPASCO - A Macintosh-based, interactive graphic preprocessor for structural analysis and sizing

MacPASCO, an interactive, graphic preprocessor for panel design is described. MacPASCO creates input for PASCO, an existing computer code for structural analysis and optimization of longitudinal stiffened composite panels. By using a graphical user interface, MacPASCO simplifies the specification of panel geometry and reduces user input errors, thus making the modeling and analysis of panel designs more efficient. The user draws the initial structural geometry on the computer screen, then uses a combination of graphic and text inputs to: refine the structural geometry, specify information required for analysis such as panel load conditions, and define design variables and constraints for minimum-mass optimization. Composite panel design is an ideal application because the graphical user interface can: serve as a visual aid, eliminate the tedious aspects of text-based input, and eliminate many sources of input errors.

Lucas, S. H.↗

Measurement of $\tau _\text {L}$ using the ${B} _s^0 \rightarrow J/\psi \eta$ decay mode

Using a proton–proton collision data sample collected by the LHCb detector and corresponding to an integrated luminosity of $5.7~\text {fb}^{-1}$ , the lifetime of the light ${{B} ^0_{s}}$ mass eigenstate, $\tau _{L}$ , is measured using the $B^0_s \rightarrow J/\psi \eta$ decay mode to be $\begin{aligned} \tau _{\text {L}} = 1.445 \pm 0.016 \text {(stat)} \pm 0.008 \text {(syst)} \,\text {ps}. \end{aligned}$ A combination of this result with a previous LHCb analysis using an independent dataset corresponding to 3 fb –1 of integrated luminosity gives $\begin{aligned} \tau _{\text {L}} = 1.452 \pm 0.014 \pm 0.007 \pm 0.002 \,\text {ps}, \end{aligned}$ where the first uncertainty is statistical, the second due to the uncorrelated part of the systematic uncertainty and the third due to the correlated part of the systematic uncertainty.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Classification of Notices to Airmen using Natural Language Processing

This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.

Aiden C. Szeto↗

Classification of Notices to Airmen using Natural Language Processing

This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.

Aiden Szeto↗

Database tomography for commercial application

Database tomography is a method for extracting themes and their relationships from text. The algorithms, employed begin with word frequency and word proximity analysis and build upon these results. When the word 'database' is used, think of medical or police records, patents, journals, or papers, etc. (any text information that can be computer stored). Database tomography features a full text, user interactive technique enabling the user to identify areas of interest, establish relationships, and map trends for a deeper understanding of an area of interest. Database tomography concepts and applications have been reported in journals and presented at conferences. One important feature of the database tomography algorithm is that it can be used on a database of any size, and will facilitate the users ability to understand the volume of content therein. While employing the process to identify research opportunities it became obvious that this promising technology has potential applications for business, science, engineering, law, and academe. Examples include evaluating marketing trends, strategies, relationships and associations. Also, the database tomography process would be a powerful component in the area of competitive intelligence, national security intelligence and patent analysis. User interests and involvement cannot be overemphasized.

Kostoff, Ronald N.↗

Decay Curve Correction Analysis Report

The decay curve analysis that is done on the short-lived radionuclide gas samples is used to differentiate between gaseous radionuclides that have the same characteristic gamma decay energy, 511 kiloelectron-volts (keV). A sample of stack gas is isolated and the total counts in the 511 keV peak are counted repeatedly in 10-second intervals to evaluate the decay rate of the sample over time. Analysis of this decay data required a series of steps. First, a raw data report is generated by the gamma acquisition system, based on an analysis template within the acquisition software. The data report file was then loaded into Microsoft Word, and a macro was used to perform minor formatting (remove colons and insert tabs between data columns) to allow analysis within Excel. The file is then saved as a text file at this point. The text file is then uploaded into Excel and a series of macros are used to add labels, calculate radioactive decay constants, and analyze the gamma decay data using linear regression techniques. The analysis template has been used since 1998 for stack 53000303 (TA-53, building 0003, exhaust stack 03) and 2000 for stack 53000702. The overall process, including the gamma report format and the macros used in Word and Excel for processing the report, had remained unchanged until 2015. In October of 2015, staff made a change to the report template in the gamma acquisition software which resulted in an error in the calculations later performed by the Excel macro. This error was not caught until a more in-depth review of the analysis took place regarding 2020 data. This report covers a much more complete review of the issue that occurred regarding the decay curve analysis, a review of the calculations completed to correct the issue, a review of the updated decay curve analysis process, and recommendations for moving forward.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cosmological constraints from the Planck cluster catalogue with DES shear profiles and Chandra observations

We present cosmological constraints from the Planck PSZ2 cosmological cluster sample, using weak-lensing shear profiles from Dark Energy Survey (DES) data and X-ray observations from the Chandra telescope for the mass calibration. We compute hydrostatic mass estimates for all clusters in the PSZ2 sample with a scaling relation between their Sunyaev-Zeldovich signal and X-ray derived hydrostatic mass, calibrated with the Chandra data. We introduce a method to correct these masses with a hydrostatic mass bias using shear profiles from wide-field galaxy surveys. We simultaneously fit the number counts of the PSZ2 sample and the mass calibration with the DES data, finding $Ω_\text{m}=0.312^{+0.018}_{-0.024}$, $σ_8=0.777\pm 0.024$, $S_8\equiv σ_8 \sqrt{Ω_\text{m} / 0.3}=0.791^{+0.023}_{-0.021}$, and $(1-b)=0.844^{+0.055}_{-0.062}$ for our baseline analysis when combined with BAO data. When considering a hydrostatic mass bias evolving with mass, we find $Ω_\text{m}=0.353^{+0.025}_{-0.031}$, $σ_8=0.751\pm 0.023$, and $S_8=0.814^{+0.019}_{-0.020}$. We verify the robustness of our results by exploring a variety of analysis settings, with a particular focus on the definition of the halo centre used for the extraction of shear profiles. We compare our results with a number of other analyses, in particular two recent analyses of cluster samples obtained from SPT and eROSITA data that share the same mass calibration data set. We find that our results are in overall agreement with most late-time probes, in very mild tension with CMB results (1.6$σ$), and in significant tension with results from eROSITA clusters (2.9$σ$). We confirm that our mass calibration is consistent with the eROSITA analysis by comparing masses for clusters present in both Planck and eROSITA samples, eliminating it as a potential cause of tension.

Aymerich, G. [Orsay, IAS; AIM, Saclay] (ORCID:0009↗

Oxidation potentials of phenols and anilines: correlation analysis of electrochemical and theoretical values

As described in the main text, we classified our voltammograms into four types. For phenols, most compounds were type I or type II, except four phenols that were type III (4-nitrophenol, 4-cyanophenol, DNOC, and 4-hydroxyacetphenone); and two phenols that were type IV (4-aminophenol and dopamine). Almost all of the compounds gave the same type by SCV and SWV, except for 2,4-dinitrophenol (whose current went up and down and therefore could be considered a type II or III), 4-cyanophenol (which fell into a type III for SCV, but whose current went up and down in SWV (type II or III)), and 4-hydroxyacetophenone (which was a type III in SCV, but a type II in SWV). The majority of the anilines were type I except for p-toluidine (type II) and 4-methyl-3-nitroaniline and 2-methoxy-5-nitroaniline (both were type I for SWV, but for SCV fell into type III and type II respectively).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigation of ion and electron heat transport of high- T e ECH heated discharges in the large helical device

An analysis of the radial electric field and heat transport, both for ions and electrons, is presented for a high-${{T}_{\text{e}}}$ electron cyclotron heated (ECH) discharge on the large helical device (LHD). Transport analysis is done using the task3d transport suite utilizing experimentally measured profiles for both ions and electrons. Ion temperature and perpendicular flow profiles are measured using the recently installed x-ray imaging crystal spectrometer diagnostic (XICS), while electron temperature and density profiles are measured using Thomson scattering. The analysis also includes calculated ECH power deposition profiles as determined through the travis ray-tracing code. This is the first time on LHD that this type of integrated transport analysis with measured ion temperature profiles has been performed without NBI, allowing the heat transport properties of plasmas with only ECH heating to be more clearly examined. For this study, a plasma discharge is chosen which develops a high central electron temperature (${{T}_{\text{eo}}}=9$ keV) at moderately low densities (${{n}_{\text{eo}}}=1.5\times {{10}^{19}}$ m-3). The experimentally determined transport properties from task3d are compared to neoclassical predictions as calculated by the gsrake and fortec-3d codes. The predicted electron fluxes are seen to be an order of magnitude less than the measured fluxes, indicating that electron transport is largely anomalous, while the neoclassical and measured ion heat fluxes are of the same magnitude. Neoclassical predictions of a strong positive ambipolar electric field (${{E}_{\text{r}}}$ ) in the plasma core are validated through comparisons to perpendicular flow measurements from the XICS diagnostic. Furthermore, this provides confidence that the predictions are producing physically meaningful results for the particle fluxes and radial electric field, which are a key component in correctly predicting plasma confinement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

In Vitro Sugar Interference Testing With Amperometric Glucose Oxidase Sensors

Background: Electrochemical enzymatic glucose sensors are intended to measure blood or interstitial fluid glucose concentrations. One class of these glucose sensors are continuous glucose monitors (CGMs), indicated for tracking and trending of glucose concentrations in interstitial fluid and as an adjunct to blood glucose testing. Currently approved CGMs employ a glucose oxidase (GOx) electrochemical detection scheme. Potential interfering agents can impact the accuracy of results obtained by glucose sensors, including CGMs. Methods: Seven sugars, seven sugar alcohols, and three artificial sweeteners were in vitro screened for interference with amperometric glucose oxidase (GOx) sensors at concentrations greater than physiologic concentrations. Galactose was investigated further at physiologically relevant concentrations using a custom amperometric system. Furthermore, glucose and galactose calibration experiments were conducted to facilitate multiple enzyme kinetic analysis approaches (Michaelis-Menten and Hill equation) to understand the potential source and mechanism of interference from galactose. Results: Under in vitro testing, except for galactose, xylose and mannose, all screened compounds exhibited interference bias, expressed in mean absolute relative difference (MARD), of ⩽ 20% even at concentrations significantly higher than normal physiologic concentrations. Galactose exhibited, CGM-dependent, MARD of 47-72% and was subjected to further testing. The highest recorded mean relative difference (MRD) was 6.9 ± 1.3% when testing physiologically relevant galactose concentrations (0.1-10 mg/dL). Enzyme kinetic analysis provided calculations of maximum reaction rates ([Formula: see text]), apparent Michaelis constants ([Formula: see text]), and Hill equation h parameters for glucose and galactose substrates for the enzymes in the CGMs. Conclusion: Under the conditions of in vitro screening, 14 of the 17 compounds did not exhibit measuarable interference. Galactose exhibited the highest interference during screening, but did not substantially interfere with CGMs under the conditions of in vitro testing at physiologically relevant concentrations. Enzyme kinetic analysis conducted with galactose supported the notion that (1) the reactivity of GOx enzyme toward nonglucose sugars and (2) the presence of enzymatic impurities (such as galactose oxidase) are two potential sources for sugar interference with GOx glucose sensors, and thus, should be considered during device development.

Boehm, Ryan↗