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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Use and Siting of Electric Vehicle Charging Stations in Juneau, Alaska

This report details a study of electric vehicle (EV) Level 2 charging stations in Juneau, Alaska. Utilization analyses of six public over five years and 250 residential chargers over two years are included, and a composite score is introduced to identify optimal locations for future charging stations that target residents of manufactured and multifamily housing (MMFH) in Juneau. We find that public charging station usage is very location-dependent, with three chargers in use more than 60% of days during the peak hour of the day (which ranges from 10 a.m. to 7 p.m.), including a charger near residential housing, illuminating potential needs for additional public chargers in those areas. Residential charging utilization typically occurs overnight - opposite to most public charging stations analyzed - and spikes after 10 p.m. This suggests that Alaska Electric Light & Power Company's time-of-use charging program, which lowers electricity rates at 10 p.m. to incentivize overnight charging, is very effective. Residential charging data also show that households tend to charge 15 hours per week, or 9% of the time, meaning that multiple households could likely share one charger if one were provided near MMFH locations. This is supported by residential charging session analysis, which shows that the median household has around two night charging sessions per week. The EV siting analysis identifies areas of high housing density, low access to public chargers, and unconstrained feeders. A cluster of MMFH parcels in Douglas demonstrated the highest composite scores considering all factors, being the only area to have a perfect score of 2.25.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Benchmark datasets for SARS-CoV-2 surveillance bioinformatics

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has spread globally and is being surveilled with an international genome sequencing effort. Surveillance consists of sample acquisition, library preparation, and whole genome sequencing. This has necessitated a classification scheme detailing Variants of Concern (VOC) and Variants of Interest (VOI), and the rapid expansion of bioinformatics tools for sequence analysis. These bioinformatic tools are means for major actionable results: maintaining quality assurance and checks, defining population structure, performing genomic epidemiology, and inferring lineage to allow reliable and actionable identification and classification. Additionally, the pandemic has required public health laboratories to reach high throughput proficiency in sequencing library preparation and downstream data analysis rapidly. However, both processes can be limited by a lack of a standardized sequence dataset. We identified six SARS-CoV-2 sequence datasets from recent publications, public databases and internal resources. In addition, we created a method to mine public databases to identify representative genomes for these datasets. Using this novel method, we identified several genomes as either VOI/VOC representatives or non-VOI/VOC representatives. To describe each dataset, we utilized a previously published datasets format, which describes accession information and whole dataset information. Additionally, a script from the same publication has been enhanced to download and verify all data from this study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

National Emission Standards for Hazardous Air Pollutants – Radionuclide Emissions Calendar Year 2020

The U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office (NNSA/NFO) operates the Nevada National Security Site (NNSS) and the North Las Vegas Facility (NLVF). From 1951 through 1992, the NNSS was the continental testing location for U.S. nuclear weapons. Radionuclides in air from NNSS activities have been monitored since the initiation of atmospheric testing. After 1962, testing was limited to underground detonations, which greatly reduced radiation exposure to the public. Since the end of nuclear testing in 1992, radiation monitoring has focused on detecting airborne radionuclides from historically contaminated soils because this sources dominates the potential offsite dose. These radionuclides are derived from re-suspension of soil (primarily by wind) and emission of tritium-contaminated soil moisture through evapotranspiration. Low amounts of legacy-related tritium are also emitted to air at the NLVF, an NNSS support complex in North Las Vegas. To protect the public from harmful levels of manmade radiation, the Clean Air Act, National Emission Standards for Hazardous Air Pollutants (NESHAP), specifically the National Emission Standards for Emissions of Radionuclides Other Than Radon From Department of Energy Facilities (40 CFR 61, Subpart H, 2020) limits the release of radioactivity from a DOE facility to that which would cause 10 millirem per year (mrem/y) effective dose equivalent (EDE) to any member of the public. This limit does not include radiation unrelated to NNSS activities. Unrelated doses could come from naturally occurring radioactive elements, from sources such as medically or commercially used radionuclides, or from sources outside of the United States, such as Japan’s Fukushima nuclear power plant, which was damaged in 2011. NNSA/NFO demonstrates compliance with the NESHAP limit by reporting environmental measurements of radionuclide air concentrations at critical receptor locations on the NNSS. This alternative was proposed and formerly submitted to the U.S. Environmental Protection Agency (EPA) in 2001 (EPA 2001a) and has been the method used to demonstrate compliance with the 40 CFR 61.92 dose standard since 2005. Six locations on the NNSS have been established to act as critical receptor locations to demonstrate compliance with the NESHAP limit. These locations are closer to radionuclide releases than where the public resides so they act as protective substitutes for public receptor locations. Compliance is demonstrated if the measured annual average concentration is less than the NESHAP Concentration Level (CL) for Environmental Compliance listed in Table 2 of 40 CFR 61, Appendix E. For multiple radionuclides, compliance is demonstrated when the sum of the fractions (determined by dividing each radionuclide’s concentration by its CL and then adding the fractions together) is less than 1.0. The EPAapproved air transport model, called the Clean Air Package 1988 (CAP88-PC) is also used to calculate the effective dose equivalent to the maximally exposed individual from NNSS air emissions. CAP88-PC was also used to calculate the population dose, or the collective EDE (expressed as person-rem [roentgen equivalent man] per year [person-rem/y]) for all individuals combined who reside within 80 kilometers (km) of NNSS emission sources. In 2020, the potential dose from radiological emissions to air from both current and past NNSS activities was well below the 10 mrem/y dose limit. This is demonstrated by both the air sampling data collected at critical receptor air monitoring stations and CAP88-PC modeling. The average concentrations of radioactivity at air critical receptor stations ranged from 0.2% to a maximum of 4.2% of the allowed NESHAP limit. CAP88-PC modeling of all 2020 NNSS radionuclide emissions showed the maximally exposed individual to be in Amargosa Valley and this individual received a potential dose of 0.063 mrem/y. The collective dose was calculated to be 0.29 person-rem/year for the 521,300 people who lived within 80 km of NNSS emission sources.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

PR100 One-Year Progress Update: Preliminary Modeling Results and High-Resolution Solar and Wind Data Sets

The Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) is a 2-year study by the U.S. Department of Energy's (DOE's) Grid Deployment Office and six national laboratories to comprehensively analyze stakeholder-driven pathways to Puerto Rico's clean energy future. In Year 1 of the study, the PR100 team rigorously modeled and analyzed scenarios that meet Puerto Rico's renewable energy targets and achieve short-term recovery goals and long-term energy resilience. This presentation will be showcased in the form of a public webinar, which summarizes PR100 progress in Year 1, provides considerations that can inform potential funding and implementation decisions by key federal and local agencies and stakeholders. The presentation follows the publication in July 2022 of a PR100 Six-Month Progress Update (in English and Spanish), as well as public webinars in February 2022 to kick off the study and in July 2022 to present the 6-month update. A final written report and web-based visuals will be published in late 2023. All publications and public events associated with the study will be available in Spanish and English. This report is also available in Spanish: https://www.nrel.gov/docs/fy23osti/85201.pdf.

100%↗
DOE OSTI2022

A New Process for Small-Batch Purification of the Medical Isotope Molybdenum-99: Non-Technical Overview

The U.S. medical community depends on a reliable supply of the radioisotope molybdenum-99 (Mo-99) for nuclear medical diagnostic procedures. Mo-99's decay product, technetium-99m (Tc-99m), is used in over 40,000 medical procedures in the United States each day to diagnose heart disease and cancer, to study organ structure and function, and to perform other important medical applications. For example, patients undergoing a common procedure—the cardiac “stress test”—likely have benefited from Tc-99m. Historically, Mo-99 was primarily produced through the fission of uranium-235, in the form of highly enriched uranium (HEU) targets irradiated in research and test reactors. HEU is a proliferation-sensitive material that, if diverted or stolen, could be used as a component of a nuclear weapon. NNSA’s Office of Material Management and Minimization (M3) manages the Molybdenum-99 (Mo-99) Program as part of its mission to minimize the use of HEU in civilian applications. The Mo-99 Program assists global Mo-99 production facilities in converting to non-HEU processes and supports the establishment of domestic supplies of Mo-99 without the use of proliferation-sensitive HEU. As part of this program, M3 funds U.S. national laboratories to provide non-proprietary technical support to U.S. companies working to establish non-HEU-based Mo-99 production capabilities. The results of this research are published on OSTI.gov for the benefit of the Mo-99 community and the public. However, it can be difficult for readers without a scientific background to understand and interpret these publications. In order to increase public understanding of the work being done in M3’s Mo-99 Program, this paper aims to provide an overview of a key, recent national laboratory technical publication in terms that can be understood by readers without a technical background. To accomplish this, the paper first explains key scientific concepts—primarily related to chemistry—that provide a foundation for understanding research in this area. This includes chromatography, absorption vs. adsorption, dissolution and precipitation, and liquid-liquid extraction. Drawing on these concepts, the paper then provides an explanation for non-technical audiences of the Argonne National Laboratory publication entitled Recovery of High Specific Activity Molybdenum-99 from Accelerator-Induced Fission on Low-Enriched Uranium for Technetium-99m Generators (Brown, M.A. et al., 2021) and related article Separation and Purification of Mo-99 Produced from Natural U3O8 Targets via Photo-Fission (Brown, M.A. et al., 2021).

Stamler, Bradley↗
DOE OSTI2020

Analysis of Exposure during Transportation of Waste to the Nevada National Security Site (NNSS) - 20445

Safety is a priority for the U.S. Department of Energy (DOE) Environmental Management (EM) Nevada Program. This commitment to safety is integrated into requirements and work procedures at DOE sites across the U.S. that generate low-level radioactive waste, mixed low-level radioactive waste, and classified waste that is transported to the Nevada National Security Site (NNSS) for permanent disposal. Generators of this waste are responsible for ensuring it is packaged and transported in a safe and compliant manner. These generators and their contracted commercial carriers must comply with U.S. Department of Transportation (DOT) regulations; the Nevada National Security Site Waste Acceptance Criteria (NNSSWAC); and other applicable federal, state, and local regulations and requirements. This includes packaging and shipping the waste to meet DOT regulatory radiation dose limits to ensure public safety during transportation. NNSS waste generators have a solid safety record for complying with these stringent regulations as demonstrated by the fact that no shipments exceeding DOT dose rate limits were received at the NNSS Area 5 Radioactive Waste Management Complex (RWMC) during FY 2014 through FY 2018. A 2005 study conducted by the Desert Research Institute validated shipments to the NNSS comply with DOT radiation dose limits. In response to recent Nevada stakeholder requests for an updated study, an analysis was conducted to verify and provide evidence that the public continues to be safe from exposure to radioactive waste shipment to the NNSS. Radiation exposure from radioactive waste shipments in transit to the NNSS was evaluated. Three studies were performed: 1. Confirm compliance of waste shipments to the DOT radiation limits using dose rate surveys taken at the generator site and at the disposal site. 2. Estimate the dose to the public from waste shipments using the dosimetry results for disposal site personnel by comparing time of exposure for various individuals/scenarios. 3. Estimate the truck driver dose using the receipt dose rate surveys and time of exposure, and from dosimetry results. Study 1 confirmed compliance with the DOT dose rate limits for a sample of waste shipments (123 of 1,038) received during fiscal year (FY) 2017. Study 2 showed that the average annual radiation equivalent dose for disposal site personnel during FY 2017 was approximately 6.7% [0.415 mSv (41.5 millirem)] of the annual average dose that a person living in the U.S. receives from all sources [6.2 mSv (620 mrem)]. Maximum dose to a member of the public, a person resting/sleeping in an adjacent truck at a rest area to a waste shipment, was 0.0166 mSv (1.66 mrem), which is less than the dose received from a person taking a round trip from the east coast to the west coast of the continental U.S. on an airplane [0.07 mSv (7 mrem) per round trip]. Study 3 showed that the truck driver who made the most shipments of radioactive waste to the NNSS, who drove the most hours (estimated time of exposure 2,520 hours), during FY 2017 had a total dose of 0.15 mSv (15 mrem), which was obtained from their personal dosimeter. The annual dose recorded for disposal site personnel, the dose estimates for the public, and the truck driver dose were all a small percentage of the average radiation dose a person receives from all sources (e.g., background and medical radiation). At these levels, risk should only be described qualitatively. Radiation exposure from radioactive waste shipments to the NNSS were shown to be compliant with the DOT dose rate limits, safe, and very low (i.e., within background levels). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Fungal Spore Seasons Advanced Across the US Over Two Decades of Climate Change

Abstract Phenological shifts due to climate change have been extensively studied in plants and animals. Yet, the responses of fungal spores—organisms important to ecosystems and major airborne allergens—remain understudied. This knowledge gap limits our understanding of their ecological and public health implications. To address this, we analyzed a long‐term (2003–2022), large‐scale (the continental US) data set of airborne fungal spores collected by the US National Allergy Bureau. We first pre‐processed the spore data by gap‐filling and smoothing. Afterward, we extracted 10 metrics describing the phenology (e.g., start and end of season) and intensity (e.g., peak concentration and integral) of fungal spore seasons. These metrics were derived using two complementary but not mutually exclusive approaches—ecological and public health approaches, defined as percentiles of total spore concentration and allergenic thresholds of spore concentration, respectively. Using linear mixed‐effects models, we quantified annual shifts in these metrics across the continental US. We revealed a significant advancement in the onset of the spore seasons defined in both ecological (11 days, 95% confidence interval: 0.4–23 days) and public health (22 days, 6–38 days) approaches over two decades. Meanwhile, total spore concentrations in an annual cycle and in a spore allergy season tended to decrease over time. The earlier start of the spore season was significantly correlated with climatic variables, such as warmer temperatures and altered precipitations. Overall, our findings suggest possible climate‐driven advanced fungal spore seasons, highlighting the importance of climate change mitigation and adaptation in public health decision‐making.

Environmental Sciences & Ecology↗
DOE OSTI2020

Conscientious vaccination exemptions in kindergarten to eighth-grade children across Texas schools from 2012 to 2018: A regression analysis

Background: As conscientious vaccination exemption (CVE) percentages rise across the United States, so does the risk and occurrence of outbreaks of vaccine-preventable diseases such as measles. In the state of Texas, the median CVE percentage across school systems more than doubled between 2012 and 2018. During this period, the proportion of schools surpassing a CVE percentage of 3% rose from 2% to 6% for public schools, 20% to 26% for private schools, and 17% to 22% for charter schools. The aim of this study was to investigate this phenomenon at a fine scale. Methods and findings: Here, we use beta regression models to study the socioeconomic and geographic drivers of CVE trends in Texas. Using annual counts of CVEs at the school system level from the 2012–2013 to the 2017–2018 school year, we identified county-level predictors of median CVE percentage among public, private, and charter schools, the proportion of schools below a high-risk threshold for vaccination coverage, and five-year trends in CVEs. Since the 2012–2013 school year, CVE percentages have increased in 41 out of 46 counties in the top 10 metropolitan areas of Texas. We find that 77.6% of the variation in CVE percentages across metropolitan counties is explained by median income, the proportion of the population that holds a bachelor's degree, the proportion of the population that self-reports as ethnically white, the proportion of the population that is English speaking, and the proportion of the population that is under the age of five years old. Across the 10 top metropolitan areas in Texas, counties vary considerably in the proportion of school systems reporting CVE percentages above 3%. Sixty-six percent of that variation is explained by the proportion of the population that holds a bachelor’s degree and the proportion of the population affiliated with a religious congregation. Three of the largest metropolitan areas—Austin, Dallas–Fort Worth, and Houston—are potential vaccination exemption "hotspots," with over 13% of local school systems above this risk threshold. The major limitations of this study are inconsistent school-system-level CVE reporting during the study period and a lack of geographic and socioeconomic data for individual private schools. Conclusions: In this study, we have identified high-risk communities that are typically obscured in county-level risk assessments and found that public schools, like private schools, are exhibiting predictable increases in vaccination exemption percentages. As public health agencies confront the reemerging threat of measles and other vaccine-preventable diseases, findings such as ours can guide targeted interventions and surveillance within schools, cities, counties, and sociodemographic subgroups.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Quantifying air quality co-benefits to industrial decarbonization: the local Air Emissions Tracking Atlas

Many decarbonization technologies have the added co-benefit of reducing short-lived climate pollutants, such as particulate matter (PM), nitrogen oxides (NO x ), and sulfur dioxide (SO 2 ), creating a unique opportunity for identifying strategies that promote both climate change solutions and opportunities for air quality improvement. However, stakeholders and decision-makers may struggle to quantify how these co-benefits will impact public health for the communities most affected by industrial air pollution. To address this problem, the LOCal Air Emissions Tracking Atlas (LOCAETA) fills a data availability and analysis gap by providing estimated air quality benefits from industrial decarbonization options, such as carbon capture and storage (CCS). These co-benefits are calculated using an algorithm that connects disparate datasets that separately report greenhouse gas emissions and other pollutants at U.S. industrial facilities. Version 1.0 of LOCAETA displays the estimated primary PM 2.5 emission reduction co-benefits from additional pretreatment equipment for CCS on industrial and power facilities across the state of Louisiana, as well as the potential for VOC and NH 3 generation. The emission reductions are presented in the tool alongside facility pollutant emissions information and relevant air quality, environmental, demographic, and public health datasets, such as air toxics cancer risk, satellite and in situ pollutant measurements, and population vulnerability metrics. LOCAETA enables regulators, policymakers, environmental justice communities, and industrial and commercial users to compare and contrast quantifiable public health benefits due to air quality impacts from various climate change mitigation strategies using a free and publicly-available tool. Additional pollutant reductions can be calculated using the same methodology and will be available in future versions of the tool.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Predicting river turbidity in Pine Island Bayou using machine learning techniques coupled with variational mode decomposition

Elevated turbidity levels pose significant public health risks by facilitating the transport of harmful pollutants, including metals, organic compounds, and pathogenic microorganisms into the surface water. These conditions create serious challenges for public recreational water use and drinking water treatment, leading to economic losses and health risks. This study utilizes water monitoring data in Pine Island Bayou, Texas, and develops a Sequence-to-Sequence (S2S) model to predict turbidity using Attention-based Gated Recurrent Units with Encoder-Decoder (AT-GRU-ED) and Long Short-Term Memory (LSTM), coupled with Variational Mode Decomposition (VMD). Compared to the model without VMD, the model demonstrates satisfactory 72-hour turbidity prediction performance, achieving MAEs of 2.60 and 3.29 NTU (reductions of 53% and 58%), RMSEs of 21.08 and 31.49 NTU (reductions of 82% and 80%), and R² values of 0.96 and 0.84 on the validation and test sets, respectively. Feature importance analysis reveals that water temperature is the dominant factor influencing seasonal turbidity patterns, while real-time hourly rainfall significantly contributes to short-term variability. Turbidity typically peaks within 48 hours after rainfall events due to lagged effects from surface runoff and upstream flow. Findings suggest suspending recreational water use and water supply pumping for three days after heavy rainfall can benefit public health and improve water treatment processes. Discharges above 100 m3/s are found to accelerate sediment dilution and transport, reducing turbidity levels more quickly after the peak. In conclusion, the proposed model demonstrates reliable 72-hour turbidity prediction, supporting decision-making for water treatment plant operations and providing early warning for public recreational water use.

Deep learning↗
DOE OSTI2026

Examination of Replicate Syntheses of Metal Organic Frameworks as a Window into Reproducibility in Materials Chemistry

Replicate experiments are a useful tool in understanding the repeatability of scientific measurements. In 2019, a systematic search for replicate syntheses of a collection of 130 metal–organic frameworks (MOFs) found that 89% of these materials had no reported replicate syntheses apart from the original publications identifying the material (Agrawal, M. Proc. Natl. Acad. Sci. U.S.A. 2020, 117, 877−88210.1073/pnas.1918484117). A potential weakness of that search was that only 5–11 years had elapsed since the original publication of each material. Here, this analysis is extended to all publications 11–17 years after the original publication. Although this extended time period identifies more repeat syntheses, 83% of the materials still have no reported replicate syntheses. We also consider how appropriately selected Density Functional Theory (DFT) calculations can provide corroboration for the experimentally reported crystal structures. By using data from previous high-throughput DFT studies, corroborating evidence from DFT was available for 17% of the 130 structures for which no replicate syntheses are available. In total, approximately 1/3 of the 130 MOFs have data associated with replicate synthesis experiments and/or directly corroborating DFT calculations.

Sholl, David S. [Oak Ridge National Laboratory (OR↗
DOE OSTI2022

Achievements and Lessons Learned From Successful Small Satellite Missions for Space Weather‐Oriented Research

Abstract When the first CubeSats were launched nearly two decades ago, few people believed that the miniature satellites would likely prove to be a useful scientific tool. Skeptics abounded. However, the last decade has seen the highly successful implementation of space missions that make creative and innovative use of fast‐advancing CubeSat and small satellite technology to carry out important science experiments and missions. Several projects now have used CubeSats to obtain first‐of‐their‐kind observations and findings that have formed the basis for high‐profile engineering and science publications, thereby establishing without doubt the scientific value and broad utility of CubeSats. In this paper, we describe recent achievements and lessons learned from a representative selection of successful CubeSat missions with a space weather focus. We conclude that these missions were successful in part because their limited resources promoted not only mission focus but also appropriate risk‐taking for comparatively high science return. Quantitative analysis of refereed publications from these CubeSat missions and several larger missions reveals that mission outcome metrics compare favorably when publication number is normalized by mission cost or if expressed as a weighted net scientific impact of all mission publications.

Spence, Harlan E.↗
DOE OSTI2023

Financial Case Study on the Use of Cloud Resources in HEP Computing

An all-inclusive analysis of costs for on-premises and public cloudbased solutions to handle the bulk of HEP computing requirements shows that dedicated on-premises deployments of compute and storage resources are still the most cost-effective. Since the advent of public cloud services, the HEP community has engaged in multiple proofs of concept to study the technical viability of using cloud resources; however, the financial viability of using cloud resources for HEP computing and storage is of greater importance. We present the results of a study comparing the cost of providing computing resources in a public cloud and a comprehensive estimate for the cost of an on-premises solution for HEP computing. Like previous studies, the fundamental conclusion is that for the bulk of HEP computing needs, on premises is significantly more cost effective than public clouds.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Decision support for United States—Canada energy integration is impaired by fragmentary environmental and electricity system modeling capacity

The renewable energy transition is leading to increased electricity trade between the United States and Canada, with Canadian hydropower providing firm lower-carbon power and buffering variability of wind and solar generation in the U.S. However, long-term power purchase agreements and transborder transmission projects are controversial, with two of four proposed transmission lines between Quebec, Canada and the northeast U.S. cancelled since 2018. Here, we argue that controversies are exacerbated by a lack of open-source data and tools to understand tradeoffs of new hydropower generation and transmission infrastructure in comparison to alternatives. This gap includes impacts that incremental transmission and generation projects have on the economics of the entire system, for example, how new transmission projects affect exports to existing markets or incentivize new generation. We identify priority areas for data synthesis and model development, such as integrating linked hydropower and hydrologic interactions in energy system models and openly releasing (by utilities) or back-calculating (by researchers) hydropower generation and operational parameters. Publicly available environmental (e.g. streamflow, precipitation) and techno-economic (e.g. costs, reservoir size,) data can be used to parameterize freely usable and extensible models. Existing models have been calibrated with operational data from Canadian utilities that are not publicly available, limiting the range of scientific and commercial questions these tools have been used to answer and the range of parties that have been involved. Studies conducted using highly resolved, national-scale public data exist in other countries, notably, the United States, and demonstrate how greater transparency and extensibility can drive industry action. Improved data availability in Canada could facilitate approaches that (1) increase participation in decarbonization planning by a broader range of actors; (2) allow independent characterizations of environmental, health, and economic outcomes of interest to the public; and (3) identify decarbonization pathways consistent with community values.

13 HYDRO ENERGY↗
DOE OSTI2022

Private Tabular Survey Data Products through Synthetic Microdata Generation

We propose two synthetic microdata approaches to generate private tabular survey data products for public release. We adapt a pseudo posterior mechanism that downweights by-record likelihood contributions with weights ∈[0,1] based on their identification disclosure risks to producing tabular products for survey data. Our method applied to an observed survey database achieves an asymptotic global probabilistic differential privacy guarantee. Our two approaches synthesize the observed sample distribution of the outcome and survey weights, jointly, such that both quantities together possess a privacy guarantee. The privacy-protected outcome and survey weights are used to construct tabular cell estimates (where the cell inclusion indicators are treated as known and public) and associated standard errors to correct for survey sampling bias. Through a real data application to the Survey of Doctorate Recipients public use file and simulation studies motivated by the application, we demonstrate that our two microdata synthesis approaches to construct tabular products provide superior utility preservation as compared to the additive noise approach of the Laplace Mechanism. Moreover, our approaches allow the release of microdata to the public, enabling additional analyses at no extra privacy cost.

Mathematical Methods In Social Sciences↗
DOE OSTI2022

IDAC-Bio, A Software for Internal Dosimetry Based on the New ICRP Biokinetic Models and Specific Absorbed Fractions

Radiation dosimetry is central to virtually all radiation safety applications, optimization, and research. It relates to various individuals and population groups and to miscellaneous exposure situations—including planned, existing, and emergency situations. The International Commission on Radiological Protection (ICRP) has developed a new computational framework for internal dose estimations. Important components are more detailed and improved anatomical models and more realistic biokinetic models than before. The ICRP is currently producing new organ dose and effective dose coefficients for occupational intakes of radionuclides (OIR) and environmental intakes of radionuclides (EIR), which supersede the earlier dose coefficients in Publication 68 and the Publication 72 series, respectively. However, the ICRP only publishes dose coefficients for a single acute intake of a radionuclide and for an integration period of 50 years for intake by adults and to age 70 years for intakes by pre-adults. The new software, IDAC-Bio, performs committed absorbed dose and effective dose calculations for a selectable intake scenario, e.g., for a continuous intake or an intake during x hours per day and y days per week, and for any selected integration time. The software uses the primary data and models of the ICRP biokinetic models and numerically solves the biokinetic model and calculates the absorbed doses to organs and tissues in the ICRP reference human phantoms. The software calculates absorbed dose using the nuclear decay data in ICRP publication 107. IDAC-Bio is a further development and an important addition to the internal dosimetry program IDAC-Dose2.1. Here, the results generated by the software were validated against published ICRP dose coefficients. The potential of the software is illustrated by dose calculations for a nuclear power plant worker who had been exposed to varying levels of 60 Co and who had undergone repeated whole-body measurements, and for a hypothetical member of the public subject to future releases of 148 Gd from neutron spallation in tungsten at the European Spallation Source.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Tensorized Feature Spaces for Feature Explosion

In this paper 1 1 This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-000R22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan) This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-000R22725., we present a novel framework that uses tensor factorization to generate richer feature spaces for pixel classification in hyperspectral images. In particular, we assess the performance of different tensor rank decomposition methods as compared to the traditional kernel-based approaches for the hyperspectral image classification problem. We propose Orion, which takes as input a hyperspectral image tensor and a rank and outputs an enhanced feature space from the factor matrices of the decomposed tensor. Our method is a feature explosion technique that inherently maps low dimensional input space in $\mathbb{R}^{K}$ to high dimensional space in $\mathbb{R}^{R}$ , where $R\gg K$ , say in the order of 1000x, like a kernel. We show how the proposed method exploits the multi-linear structure of hyperspectral three dimensional tensor. We demonstrate the effectiveness of our method with experiments on three publicly available hyperspectral datasets with labeled pixels and compare their classification performance against traditional linear and non-linear supervised learning methods such as SVM with Linear, Polynomial, RBF kernels, and the Multi-Layer Perceptron model. Finally, we explore the relationship between the rank of the tensor decomposition and the classification accuracy using several hyperspectral datasets with ground truth.

Pasricha, Ravdeep Singh↗
DOE OSTI2024

Biological Parts Search Portal (BioParts) v1.0.0

BioParts is a web based search portal for biological parts available in the public domain. It combines the ease and convenience of modern web search engines with the capabilities of bioinformatics search tools such as BLAST. This portal, available at bioparts.org, allows anyone to search for publicly accessible biological part information (e.g., NCBI, iGEM, SynBioHub, Addgene), including parts publicly accessible through ICE Registries. Additionally, the portal offers a REST API that enables third-party applications and tools to access the portal's functionality programmatically. While there are several standalone biological part repositories, there doesn't exist an application that indexes these publicly available parts and enables features such as keyword and BLAST searches along with automatic sequence annotation.

Plahar, Hector↗