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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A study of examiner accuracy in cartridge case comparisons. Part 1: Examiner error rates

This report describes a study undertaken to estimate examiner (not laboratory) error rates for false Identifications and false Eliminations when comparing an unknown to a collection of three known cartridge cases. Volunteer active examiners with Association of Firearm and Toolmark Examiners (AFTE) membership or working in laboratories that participate in the Association of Crime Laboratory Directors (ASCLD) were provided with 15 sets of three known and one questioned cartridge cases fired from a collection of 25 new Ruger SR9 handguns. Remington 9-mm Luger (manufacturer designation L9MM3) ammunition was used and comparison sets were made up of cartridge cases fired within 100 cartridges of each other for each gun. Examiners were provided with a background survey, an answer sheet allowing for the AFTE Range of Conclusions, and return shipping materials. In addition to determining whether the known and questioned cartridge cases were fired with the same handgun, examiners were also asked to assess how many of the three knowns in each set were suitable for comparison, providing an estimated rate of how often each firearm used in the study produces useable, quality marks. The participating examiners were provided with both same-source and different-source comparison sets allowing the study to assess both error rates. Responses were received from 218 participating examiners. The overall rate of false Eliminations was estimated as 0.367% from comparisons known to be from the same firearm but reported as Eliminations. The overall rate of false Identifications was estimated as 1.01% from comparisons known to be from different firearms but reported as Identifications. The rates are not uniform across the sample population with a few examiners providing most of the false Identification responses. Rates of poor-quality mark production varied across the 25 sample handguns; those rates were 2.3% (±1.4%). Both false Elimination and false Identification rates are comparable to or lower than the rate of production of poor-quality marks by the firearms used in this study.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

A Eulerian three-fluid flow framework for the study of fuel dispersal behavior under loss-of-coolant accident conditions

As the nuclear industry explores new fuel designs to accommodate increased burnup, studying fuel behavior during loss-of-coolant accidents is essential for ensuring the safe operation of light-water reactors. Here, this study presents a computational model to simulate the intricate three-phase flow dynamics of fuel dispersal following cladding breach, where solid fuel particles and carrier fission gases interact with the surrounding liquid or gas medium. The model utilizes a Eulerian three-fluid framework to depict the phase interaction within interpenetrating continua, treating fragmented fuel as granular material. Closure relationships for bulk-flow properties of the solid phase and detailed interfacial exchange terms in high-temperature, high-speed gas-solid-liquid flow scenarios are proposed. The model was validated using adiabatic experimental results in the literature, focusing on characterizing fuel dispersal behavior during loss-of-coolant accidents conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched probability density functions reported in experimental studies. Key highlights of this study include the theoretical description of a coupled three-phase flow with phase change, interpretation of the high-pressure boundary conditions and insights into the transient behavior of gas-solid-liquid phase dynamics during a simulated high-speed dispersal event.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Moon, Mars and Minds: Evaluating Parkinson’s disease mortality among U.S. radiation workers and veterans in the million person study of low-dose effects

Background: Radiation is one of the most important stressors related to missions in space beyond Earth’s orbit. Epidemiologic studies of exposed workers have reported elevated rates of Parkinson’s disease. The importance of cognitive dysfunction related to low-dose rate radiation in humans is not defined. A meta-analysis was conducted of six cohorts in the Million Person Study (MPS) of low-dose health effects to learn whether there is consistent evidence that Parkinson’s disease is associated with radiation dose to brain. Materials and methods: The MPS evaluates all causes of death among U.S. radiation workers and veterans, including Parkinson’s disease. Systematic and consistent methods are applied to study all categories of workers including medical radiation workers, industrial radiographers, nuclear power plant workers, atomic veterans, and Manhattan Projects workers at the Los Alamos National Laboratory and at Rocky Flats. Consistent methods for all cohorts are used to estimate organ-specific doses and to obtain vital status and cause of death. Results: The meta-analysis include 6 cohorts within the MPS, consisting of 517,608 workers and 17,219,001 person-years of observation. The mean dose to brain ranged from 6.9 to 47.6 mGy and the maximum dose from 0.76 to 2.7 Gy. Five of the 6 cohorts revealed positive associations with Parkinson’s disease. The overall summary estimate from the meta-analysis was statistically significant based on 1573 deaths due to Parkinson’s disease. The summary excess relative risk at 100 mGy was 0.17 (95% CI: 0.05; 0.29). Conclusions: Parkinson’s disease was positively associated with radiation in the MPS cohorts indicating the need for careful evaluation as to causality in other studies, delineation of possible mechanisms, and assessing possible implications for space travel as well as radiation protection guidance for terrestrial workers.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

The kinetics of SARS-CoV-2 infection based on a human challenge study

Studying the early events that occur after viral infection in humans is difficult unless one intentionally infects volunteers in a human challenge study. Here, we use data about severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in such a study in combination with mathematical modeling to gain insights into the relationship between the amount of virus in the upper respiratory tract and the immune response it generates. We propose a set of dynamic models of increasing complexity to dissect the roles of target cell limitation, innate immunity, and adaptive immunity in determining the observed viral kinetics. We introduce an approach for modeling the effect of humoral immunity that describes a decline in infectious virus after immune activation. We fit our models to viral load and infectious titer data from all the untreated infected participants in the study simultaneously. We found that a power-law with a power h < 1 describes the relationship between infectious virus and viral load. Viral replication at the early stage of infection is rapid, with a doubling time of ~2 h for viral RNA and ~3 h for infectious virus. We estimate that adaptive immunity is initiated ~7 to 10 d postinfection and appears to contribute to a multiphasic viral decline experienced by some participants; the viral rebound experienced by other participants is consistent with a decline in the interferon response. Altogether, we quantified the kinetics of SARS-CoV-2 infection, shedding light on the early dynamics of the virus and the potential role of innate and adaptive immunity in promoting viral decline during infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Package Performance Study: A Historical Perspective and Planning for a Path Forward

The topic of spent nuclear fuel (SNF) transportation often draws public attention and concerns regarding safety, and with large-scale shipping campaigns expected in the future, public interest is anticipated to substantially increase. In 1999, the U.S. Nuclear Regulatory Commission (NRC) began an initiative called the Package Performance Study (PPS) that initially focused on SNF transportation cask responses to severe transportation accidents. A public participation approach was to be used to help guide the scope and parameters of the study, which was also to consider using full-scale physical testing of a SNF transportation cask, where appropriate. In 2010, the NRC decided not to go forward with physical testing as proposed. In 2006, the National Academy of Sciences (NAS) conducted a study on SNF and high-level radioactive waste transportation in the United States. The NAS study recommended that full-scale cask testing, as well as other accepted methodologies, continue to be used as part of the package performance evaluation. In 2012, the Blue Ribbon Commission on America’s Nuclear Future (BRC) recommended conducting the PPS with a full-scale rail transportation cask for the purpose of building public trust and confidence in the safety of SNF transport. In 2021, the U.S. Department of Energy (DOE) restarted a consent-based siting process, focusing on how to site federal facilities for the interim consolidated storage of SNF using a consent-based approach. Large-scale SNF transportation would be necessary for any such interim storage facility. As the planning activities begin for future large-scale shipping campaigns, the DOE is considering options for conducting a DOE-led PPS to help build public trust and confidence in the transportation of SNF. Therefore, the DOE is gathering information related to the previous NRC-led PPS efforts, as well as applicable international experience with the testing of SNF packages. This paper discusses previous NRC efforts, as well as the current status of a DOE-led PPS, which is in the early planning stages.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Feasibility Studies and Downselection of New Materials and Manufacturing Technologies for Nuclear Applications

This report is intended to present the results of multi-laboratory collaborative studies on the feasibility and downselection of the structural materials that are newly considered for application to future nuclear energy technologies. The Advanced Materials and Manufacturing Techniques (AMMT) program has been implemented to develop cross-cutting technologies in support of a broad range of nuclear reactor technologies and to maintain U.S. leadership in materials and manufacturing technologies for nuclear energy applications. In line with these program objectives, this collaborative studies aim to explore new materials utilizing advanced manufacturing technologies. The FY23 research scope consists of the feasibility studies on new materials and relevant advanced manufacturing technologies, collection of materials properties data and knowledge through experiments and literature survey, and development and application of decision criteria matrix for downselecting candidate materials and manufacturing technologies. The three-laboratory efforts for FY23 have focused on the three new material groups including oxide dispersion strengthened (ODS) materials, refractory composites and alloys, and high entropy alloys (HEAs) investigated, respectively, by Oak Ridge National Laboratory (ORNL) (work package: CT-23OR130406), Los Alamos National Laboratory (LANL) (CT-23LA130403) and Pacific Northwest National Laboratory (PNNL) (CT-23PN130408). The execution of this multi-lab research aimed to provide the AMMT program a merit-based feasibility study identifying an accelerated development path for these materials. A collaborative approach for achieving this goal was to develop a common materials evaluation criteria matrix and apply to all new candidate materials for the evaluation and prioritization of new materials using advanced manufacturing processes. The decision criteria matrix created is a matrix of criteria which a prospective material is scored against. The evaluation criteria are divided into four categories: Application Space, Environmental Compatibility, Physical & Mechanical Properties, and Manufacturability. Materials are given a score from 1−5 for each criterion, with the highest score (5) essentially mean that a material has the most near-term potential for application. Application of the decision criteria matrix will provide guidance to the future research on new materials.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Front-end engineering design (FEED) studies: a quantitative analysis

NETL has devised a methodology for normalizing FEED study metrics of interest and allowing cautious quantitative comparison across FEED studies. This presentation introduces the novel quantitative comparison methodology and presents results from utilizing this methodology to examine data presented in recent FEED study reports. The quantitative methodology developed for the examination of FEED study performance and cost also allows comparison of real-world performance and costs against NETL TEA model predicted performance and cost. Learnings from examining NETL model predicted performance and cost versus real world reported values are highlighted. These learnings provide insight into NETL TEA model uncertainty and highlight opportunities for further model development.

FEED Studies↗
DOE OSTI2023

Risk Ratio and Risk Difference Estimation in Case-cohort Studies

Background: In case-cohort studies with binary outcomes, ordinary logistic regression analyses have been widely used because of their computational simplicity. However, the resultant odds ratio estimates cannot be interpreted as relative risk measures unless the event rate is low. The risk ratio and risk difference are more favorable outcome measures that are directly interpreted as effect measures without the rare disease assumption. Methods: We provide pseudo-Poisson and pseudo-normal linear regression methods for estimating risk ratios and risk differences in analyses of case-cohort studies. These multivariate regression models are fitted by weighting the inverses of sampling probabilities. Also, the precisions of the risk ratio and risk difference estimators can be improved using auxiliary variable information, specifically by adapting the calibrated or estimated weights, which are readily measured on all samples from the whole cohort. Finally, we provide computational code in R (R Foundation for Statistical Computing, Vienna, Austria) that can easily perform these methods. Results: Through numerical analyses of artificially simulated data and the National Wilms Tumor Study data, accurate risk ratio and risk difference estimates were obtained using the pseudo-Poisson and pseudo-normal linear regression methods. Also, using the auxiliary variable information from the whole cohort, precisions of these estimators were markedly improved. Conclusion: The ordinary logistic regression analyses may provide uninterpretable effect measure estimates, and the risk ratio and risk difference estimation methods are effective alternative approaches for case-cohort studies. These methods are especially recommended under situations in which the event rate is not low.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Electrification Futures Study Flexible Load Profiles

This data set includes hourly profiles for flexible load developed for the Electrification Futures Study (EFS). The load profiles represent projected end-use electricity demand that is assumed to be flexible (i.e., can be shifted throughout a day) for various scenarios of flexibility (Base, Enhanced), electrification (Reference, Medium, High), and technology advancement (Slow, Moderate, Rapid), and were developed as inputs into the ReEDS model. The quantity of flexible load is estimated using assumptions on the level of flexibility and customer participation within each subsector modeled in the EFS. Detailed assumptions and modeling implementation will be documented in ongoing EFS analyses. Flexible load profiles are provided for a subset of years (2018, 2020, 2024, 2030, 2040, 2050) and are aggregated to the state and sector level. Total electricity load profiles can be found in a related EFS data set (https://dx.doi.org/10.7799/1593122). NOTE: Due to the file size, Mac users may experience issues decompressing the zip files using the Mac Archive Utility. In those cases, decompressing using the command line is recommended. - Mai, Trieu, Paige Jadun, Jeffrey Logan, Colin McMillan, Matteo Muratori, Daniel Steinberg, Laura Vimmerstedt, Ryan Jones, Benjamin Haley, and Brent Nelson. 2018. Electrification Futures Study: Scenarios of Electric Technology Adoption and Power Consumption for the United States. National Renewable Energy Laboratory. NREL/TP-6A20-71500. https://doi.org/10.2172/1459351. - Murphy, Caitlin, Trieu Mai, Yinong Sun, Paige Jadun, Matteo Muratori, Brent Nelson, Ryan Jones. Forthcoming. Electrification Futures Study: Scenarios of Power System Evolution and Infrastructure Development for the United States. National Renewable Energy Laboratory. - Sun, Yinong, Paige Jadun, Brent Nelson, Matteo Muratori, Caitlin Murphy, Jeffrey Logan, and Trieu Mai. Forthcoming. Electrification Futures Study: Methodological Approaches for Assessing Long-Term Power System Impacts of End-Use Electrification. National Renewable Energy Laboratory.

buildings↗
DOE OSTI2024

SEC ‐ SAXS / MC Ensemble Structural Studies of the Microtubule Binding Protein Cdt1 Show Monomeric, Folded‐Over Conformations

ABSTRACT Cdt1 is a mixed folded protein critical for DNA replication licensing and it also has a “moonlighting” role at the kinetochore via direct binding to microtubules and the Ndc80 complex. However, it is unknown how the structure and conformations of Cdt1 could allow it to participate in these multiple, unique sets of protein complexes. While robust methods exist to study entirely folded or unfolded proteins, structure–function studies of combined, mixed folded/disordered proteins remain challenging. In this work, we employ orthogonal biophysical and computational techniques to provide structural characterization of mitosis‐competent human Cdt1. Thermal stability analyses shows that both folded winged helix domains1 are unstable. CD and NMR show that the N‐terminal and linker regions are intrinsically disordered. DLS shows that Cdt1 is monomeric and polydisperse, while SEC‐MALS confirms that it is monomeric at high concentrations, but without any apparent inter‐molecular self‐association. SEC‐SAXS enabled computational modeling of the protein structures. Using the program SASSIE, we performed rigid body Monte Carlo simulations to generate a conformational ensemble of structures. We observe that neither fully extended nor extremely compact Cdt1 conformations are consistent with SAXS. The best‐fit models have the N‐terminal and linker disordered regions extended into the solution and the two folded domains close to each other in apparent “folded over” conformations. We hypothesize the best‐fit Cdt1 conformations could be consistent with a function as a scaffold protein that may be sterically blocked without binding partners. Our study also provides a template for combining experimental and computational techniques to study mixed‐folded proteins.

Cell Biology↗
DOE OSTI2024

Surface Segregation Studies in Ternary Noble Metal Alloys: Comparing DFT and Machine Learning with Experimental Data

Abstract Surface segregation, whereby the surface composition of an alloy differs systematically from the bulk, has historically been hard to study, because it requires experimental and modeling methods that span alloy composition space. In this work, we study surface segregation in catalytically relevant noble and platinum‐group metal alloys with a focus on three ternary systems: AgAuCu, AuCuPd, and CuPdPt. We develop a data set of 2478 fcc slabs with those compositions including all three low‐index crystallographic orientations relaxed with Density Functional Theory using the PBEsol functional with D3 dispersion corrections. We fine‐tune a machine learning model on this data and use the model in a series of 1800 Monte Carlo simulations spanning ternary composition space for each surface orientation and ternary chemical system. The results of these simulations are validated against prior experimental surface segregation data collected using composition spread alloy films for AgAuCu and AuCuPd. Our findings reveal that simulations conducted using the (110) orientation most closely match experimentally observed surface segregation trends, and while predicted trends qualitatively match observation, biases in the PBEsol functional limit numeric accuracy. This study advances understanding of surface segregation and the utility of computational studies and highlights the need for further improvements in simulation accuracy.

Chemistry↗
DOE OSTI2023

Time-lapse VSP integration and calibration of subsurface stress field utilizing machine learning approaches: A case study of the morrow B formation, FWU

This study aims to develop a methodology for calibrating subsurface stress changes through time-lapse vertical seismic profiling (VSP) integration. The selected study site is a region around the injector well located within Farnsworth field unit (FWU), where there is an ongoing CO 2 -enhanced oil recovery (EOR) operation. In our study, a site-specific rock physics model was created from extensive geological, geophysical, and geomechanical characterization through 3D seismic data, well logs, and core assessed as part of the 1D MEM conducted on the characterization well within the study area. Here, the Biot-Gassmann workflow was utilized to combine the rock physics and reservoir simulation outputs to determine the seismic velocity change due to fluid substitution. Modeled seismic velocities attributed to mean effective stress were determined from the geomechanical simulation outputs, and the stress-velocity relationship developed from ultrasonic seismic velocity measurements. A machine learning-assisted workflow comprised of an artificial neural network and a particle swarm optimizer (PSO) was utilized to minimize a penalty function created between the modeled seismic velocities and the observed time-lapse VSP dataset. The successful execution of this workflow has affirmed the suitability of acoustic time-lapse measurements for 4D-VSP geomechanical stress calibration pending measurable stress sensitivities within the anticipated effective stress changes and the availability of suitable and reliable datasets for petroelastic modeling. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

58 GEOSCIENCES↗
DOE OSTI2020

Misclassification of primary liver cancer in the Life Span Study of atomic bomb survivors

Primary liver cancer is difficult to diagnose accurately at death, due to metastases from nearby organs and to concomitant diseases, such as chronic hepatitis and cirrhosis. Trends in diagnostic accuracy could affect radiation risk estimates for incident liver cancer by altering background rates or by impacting risk modification by sex and age. We quantified the potential impact of death‐certificate inaccuracies on radiation risk estimates for liver cancer in the Life Span Study of atomic bomb survivors. True‐positive and false‐negative rates were obtained from a previous study that compared death‐certificate causes of death with those based on pathological review, from 1958 to 1987. We assumed various scenarios for misclassification rates after 1987. We obtained estimated true positives and estimated false negatives by stratified sampling from binomial distributions with probabilities given by the true‐positive and false‐negative rates, respectively. Poisson regression methods were applied to highly stratified person‐year tables of corrected case counts and accrued person years. During the study period (1958–2009), there were 1,885 cases of liver cancer, which included 383 death‐certificate‐only (DCO) cases; 1,283 cases with chronic liver disease as the underlying cause of death; and 150 DCO cases of pancreatic cancer among 105,444 study participants. Across the range of scenarios considered, radiation risk estimates based on corrected case counts were attenuated, on average, by 13–30%. Our results indicated that radiation risk estimates for liver cancer were potentially sensitive to death‐certificate inaccuracies. Additional data are needed to inform misclassification rates in recent years.

French, Benjamin↗
DOE OSTI2021

Alcohol consumption and breast cancer risk in Japan: A pooled analysis of eight population‐based cohort studies

Abstract Although alcohol consumption is reported to increase the incidence of breast cancer in European studies, evidence for an association between alcohol and breast cancer in Asian populations is insufficient. We conducted a pooled analysis of eight large‐scale population‐based prospective cohort studies in Japan to evaluate the association between alcohol (both frequency and amount) and breast cancer risk with categorization by menopausal status at baseline and at diagnosis. Estimated hazard ratios (HR) and 95% confidence intervals were calculated in the individual cohorts and combined using random‐effects models. Among 158 164 subjects with 2 369 252 person‐years of follow‐up, 2208 breast cancer cases were newly diagnosed. Alcohol consumption had a significant association with a higher risk of breast cancer in both women who were premenopausal at baseline (regular drinker compared to nondrinker: HR 1.37, 1.04‐1.81, ≥23 g/d compared to 0 g/d: HR 1.74, 1.25‐2.43, P for trend per frequency category: P = .017) and those who were premenopausal at diagnosis (≥23 g/d compared to 0 g/d: HR 1.89, 1.04‐3.43, P for trend per frequency category: P = .032). In contrast, no significant association was seen in women who were postmenopausal at baseline or at diagnosis, despite a substantial number of subjects and long follow‐up period. Our results revealed that frequent and high alcohol consumption are both risk factors for Asian premenopausal breast cancer, similarly to previous studies in Western countries. The lack of a clear association in postmenopausal women in our study warrants larger investigation in Asia.

Iwase, Madoka↗
DOE OSTI2023

Obesity is associated with biliary tract cancer mortality and incidence: A pooled analysis of 21 cohort studies in the Asia Cohort Consortium

Abstract Body fatness is considered a probable risk factor for biliary tract cancer (BTC), whereas cholelithiasis is an established factor. Nevertheless, although obesity is an established risk factor for cholelithiasis, previous studies of the association of body mass index (BMI) and BTC did not take the effect of cholelithiasis fully into account. To better understand the effect of BMI on BTC, we conducted a pooled analysis using population‐based cohort studies in Asians. In total, 905 530 subjects from 21 cohort studies participating in the Asia Cohort Consortium were included. BMI was categorized into four groups: underweight (<18.5 kg/m 2 ); normal (18.5‐22.9 kg/m 2 ); overweight (23‐24.9 kg/m 2 ); and obese (25+ kg/m 2 ). The association between BMI and BTC incidence and mortality was assessed using hazard ratios (HR) and 95% confidence intervals (CIs) by Cox regression models with shared frailty. Mediation analysis was used to decompose the association into a direct and an indirect (mediated) effect. Compared to normal BMI, high BMI was associated with BTC mortality (HR 1.19 [CI 1.02‐1.38] for males, HR 1.30 [1.14‐1.49] for females). Cholelithiasis had significant interaction with BMI on BTC risk. BMI was associated with BTC risk directly and through cholelithiasis in females, whereas the association was unclear in males. When cholelithiasis was present, BMI was not associated with BTC death in either males or females. BMI was associated with BTC death among females without cholelithiasis. This study suggests BMI is associated with BTC mortality in Asians. Cholelithiasis appears to contribute to the association; and moreover, obesity appears to increase BTC risk without cholelithiasis.

Oze, Isao↗
DOE OSTI2022

Hydration of divalent lanthanides, Sm 2+ and Eu 2+ : A molecular dynamics study with polarizable AMOEBA force field

The chemistry of divalent lanthanides, Ln 2+ , is a growing sub-field of heavy element chemistry owing to new synthetic approaches. However, some theoretical aspects of these unusual cations are currently underdeveloped, especially as they relate to their dynamic properties in solution. In this study, we address the hydration of two of the classical Ln 2+ cations, Sm 2+ and Eu 2+ , using atomic multipole optimized energetic for biomolecular applications (AMOEBA) force fields. These cations have not been parameterized to date with AMOEBA, and few studies are available because of their instability with respect to oxidation in aqueous media. Coordination numbers (CN's) of 8.2 and 8.1 respectively for Sm 2+ and Eu 2+ , and 8.8 for both Sm 3+ and Eu 3+ have been obtained and are in good agreement with the few available AIMD and X-ray absorption fine structures studies. The decreased CN of Ln 2+ compared with Ln 3+ arises from progressive water exchange events that indicates the gradual stabilization of 8-coordinate structures with respect to 9-coordinate geometries. Moreover, the effects of the chloride counter anions on the coordination of Ln 2+ cations have been studied at different chloride concentrations in this work. Lastly, water exchange times of Ln 2+ cations have been calculated to provide a comprehensive understanding of the behavior of Eu 2+ and Sm 2+ in aqueous chloride media.

AMOEBA force field parameterization↗
DOE OSTI2022

Case studies in bias reduction and inference for electronic health record data with selection bias and phenotype misclassification

Electronic health records (EHR) are not designed for population‐based research, but they provide easy and quick access to longitudinal health information for a large number of individuals. Many statistical methods have been proposed to account for selection bias, missing data, phenotyping errors, or other problems that arise in EHR data analysis. However, addressing multiple sources of bias simultaneously is challenging. We developed a methodological framework (R package, SAMBA ) for jointly handling both selection bias and phenotype misclassification in the EHR setting that leverages external data sources. These methods assume factors related to selection and misclassification are fully observed, but these factors may be poorly understood and partially observed in practice. As a follow‐up to the methodological work, we demonstrate how to apply these methods for two real‐world case studies, and we evaluate their performance. In both examples, we use individual patient‐level data collected through the University of Michigan Health System and various external population‐based data sources. In case study (a), we explore the impact of these methods on estimated associations between gender and cancer diagnosis. In case study (b), we compare corrected associations between previously identified genetic loci and age‐related macular degeneration with gold standard external summary estimates. These case studies illustrate how to utilize diverse auxiliary information to achieve less biased inference in EHR‐based research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A Rapid Population Assessment Method for Wild Pigs Using Baited Cameras at 3 Study Sites

ABSTRACT Reliable and efficient population estimates are a critical need for effective management of invasive wild pigs ( Sus scrofa ). We evaluated the use of 10‐day camera grids for rapid population assessment (RPA) of wild pigs at 3 study sites that varied in vegetation communities and wild pig densities. Study areas included Buck Island Ranch, Florida; Tejon Ranch, California; and the Savannah River Site, South Carolina, USA, during 2016–2018. Rapid population assessments grids were composed of baited camera traps spaced approximately 500 or 750 m apart. Two RPA grids were deployed per study site and each grid was deployed twice (4–6 months apart) to assess changes in response to season or population control efforts. We assessed the ability of RPA grids to track population trends, how camera number influenced estimate precision, and how relative abundance indices related to density estimates. We detected changes in occupancy probability, detection probability, and N‐mixture estimates following removal operations and between seasons, but the ability of RPA grids to track population trends was dependent on the statistical method used and number of cameras traps. Increasing the number of cameras traps used in RPA grids increased precision, and these results can be used in determining survey design and estimate choice. We found that estimates of occupancy probability, detection probability, and N‐mixture estimates were positively correlated with spatially explicit capture–recapture density estimates. Thus, these less labor‐intensive estimates from RPA grids showed potential to index the relative abundance of wild pigs in some systems. Our evaluation of RPAs indicates that using study‐specific combinations of statistical method and number of cameras can provide a useful tool for monitoring wild pig presence, tracking population trends, and evaluating the effectiveness of management actions. © 2020 The Wildlife Society.

Schlichting, Peter E.↗