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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Lipoprotein(a) is associated with the onset but not the progression of aortic valve calcification

Abstract Aim Lipoprotein(a) [Lp(a)] is a potential causal factor in the pathogenesis of aortic valve disease. However, the relationship of Lp(a) with new onset and progression of aortic valve calcium (AVC) has not been studied. The purpose of the study was to assess whether high serum levels of Lp(a) are associated with AVC incidence and progression. Methods and results A total of 922 individuals from the population-based Rotterdam Study (mean age 66.0±4.2 years, 47.7% men), whose Lp(a) measurements were available, underwent non-enhanced cardiac computed tomography imaging at baseline and after a median follow-up of 14.0 [interquartile range (IQR) 13.9–14.2] years. New-onset AVC was defined as an AVC score >0 on the follow-up scan in the absence of AVC on the first scan. Progression was defined as the absolute difference in AVC score between the baseline and follow-up scan. Logistic and linear regression analyses were performed to evaluate the relationship of Lp(a) with baseline, new onset, and progression of AVC. All analyses were corrected for age, sex, body mass index, smoking, hypertension, dyslipidaemia, and creatinine. AVC progression was analysed conditional on baseline AVC score expressed as restricted cubic splines. Of the 702 individuals without AVC at baseline, 415 (59.1%) developed new-onset AVC on the follow-up scan. In those with baseline AVC, median annual progression was 13.5 (IQR = 5.2–37.8) Agatston units (AU). Lipoprotein(a) concentration was independently associated with baseline AVC [odds ratio (OR) 1.43 for each 50 mg/dL higher Lp(a); 95% confidence interval (CI) 1.15–1.79] and new-onset AVC (OR 1.30 for each 50 mg/dL higher Lp(a); 95% CI 1.02–1.65), but not with AVC progression (β: −71 AU for each 50 mg/dL higher Lp(a); 95% CI −117; 35). Only baseline AVC score was significantly associated with AVC progression (P < 0.001). Conclusion In the population-based Rotterdam Study, Lp(a) is robustly associated with baseline and new-onset AVC but not with AVC progression, suggesting that Lp(a)-lowering interventions may be most effective in pre-calcific stages of aortic valve disease.

Kaiser, Yannick (ORCID:0000000168690042)↗
DOE OSTI2025

Artemether-Lumefantrine Treatment Selects Plasmodium falciparum Multidrug Resistance 1 ( pfmdr1 ) Increased Copy Number Among African Malaria Infections

Abstract Background Decreased efficacy of artemether-lumefantrine, the globally most used antimalarial, has recently emerged in Africa. Methods An efficacy trial was carried out based on directly observed artemether-lumefantrine therapy at Bengo, Northern Angola. One-hundred Plasmodium falciparum uncomplicated malaria patients (2–10 years old) were enrolled, hospitalized for the treatment period, and followed up for 42 days. Polymerase chain reaction (PCR) correction was performed with pfmsp1/2 plus glurp, with analysis considering 2 or 3 coincident markers. Infections were tested by quantitative PCR (qPCR) for pfmdr1 copy number (pfmdr1×N), a potential P. falciparum marker of lumefantrine resistance previously identified in the region. In vitro clone mixtures were built and used to determine the relation between qPCR copy number scores and actual intrainfection quantitative fractions of pfmdr1×N. Results We observed a significant posttreatment selection of gene amplification, suggesting a role in the parasite in vivo response to this drug. pfmdr1×2 qPCR scores of 1.3, 1.4, and 1.5 were determined to correspond to 15%, 25%, and 35% intrainfection rates. Patients carrying infections with a score ≥1.4 at baseline were linked to decreased artemether-lumefantrine day 42 efficacy (79% vs 97% single-copy pfmdr1). All infections were pfmdr1 N86 carriers and no pfk13 mutations were found. Conclusions Our study suggests pfmdr1×N as a marker of P. falciparum in vivo response to lumefantrine in Africa, while indicating patients carrying infections with a pretreatment pfmdr1×N score ≥1.4 before treatment are a group experiencing decreased artemether-lumefantrine performance.

Fançony, Claudia (ORCID:0000000344211769)↗
DOE OSTI2024

Steroid responsiveness in alcohol-associated hepatitis is linked to glucocorticoid metabolism, mitochondrial repair, and heat shock proteins

Alcohol-associated hepatitis (AH) is one of the clinical presentations of alcohol-associated liver disease. AH has poor prognosis, and corticosteroids remain the mainstay of drug therapy. However, ~40% of patients do not respond to this treatment, and the mechanisms underlying the altered response to corticosteroids are not understood. The current study aimed to identify changes in hepatic protein expression associated with responsiveness to corticosteroids and prognosis in patients with AH. Patients with AH were enrolled based on the National Institute on Alcohol Abuse and Alcoholism inclusion criteria for acute AH and further confirmed by a diagnostic liver biopsy. Proteomic analysis was conducted on liver samples acquired from patients with AH grouped as nonresponders (AH-NR, n = 7) and responders (AH-R, n = 14) to corticosteroids, and nonalcohol-associated liver disease controls (n = 10). The definition of responders was based on the clinical prognostic model, the Lille Score, where a score < 0.45 classified patients as AH-R and a score > 0.45 as AH-NR. Primary outcomes used to assess steroid response were Lille Score (eg, improved liver function) and survival at 24 weeks. Reduced levels of the glucocorticoid receptor and its transcriptional co-activator, glucocorticoid modulatory element-binding protein 2, were observed in the hepatic proteome of AH-NR versus AH-R. The corticosteroid metabolizing enzyme, 11-beta-hydroxysteroid dehydrogenase 1, was increased in AH-NR versus AH-R along with elevated mitochondrial DNA repair enzymes, while several proteins of the heat shock pathway were reduced. Analysis of differentially expressed proteins in AH-NR who survived 24 weeks relative to AH-NR nonsurvivors revealed several protein expression changes, including increased levels of acute phase proteins, elevated coagulation factors, and reduced mast cell markers. This study identified hepatic proteomic changes that may predict responsiveness to corticosteroids and mortality in patients with AH.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Predicting variable gene content in Escherichia coli using conserved genes

Having the ability to predict the protein-encoding gene content of an incomplete genome or metagenome-assembled genome is important for a variety of bioinformatic tasks. In this study, as a proof of concept, we built machine learning classifiers for predicting variable gene content in Escherichia coli genomes using only the nucleotide k-mers from a set of 100 conserved genes as features. Protein families were used to define orthologs, and a single classifier was built for predicting the presence or absence of each protein family occurring in 10%–90% of all E. coli genomes. The resulting set of 3,259 extreme gradient boosting classifiers had a per-genome average macro F1 score of 0.944 [0.943–0.945, 95% CI]. We show that the F1 scores are stable across multi-locus sequence types and that the trend can be recapitulated by sampling a smaller number of core genes or diverse input genomes. Surprisingly, the presence or absence of poorly annotated proteins, including “hypothetical proteins” was accurately predicted (F1 = 0.902 [0.898–0.906, 95% CI]). Models for proteins with horizontal gene transfer-related functions had slightly lower F1 scores but were still accurate (F1s = 0.895, 0.872, 0.824, and 0.841 for transposon, phage, plasmid, and antimicrobial resistance-related functions, respectively). Finally, using a holdout set of 419 diverse E. coli genomes that were isolated from freshwater environmental sources, we observed an average per-genome F1 score of 0.880 [0.876–0.883, 95% CI], demonstrating the extensibility of the models. Overall, this study provides a framework for predicting variable gene content using a limited amount of input sequence data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The Efficacy and Safety of Mesalamine and Probiotics in Mild‐to‐Moderate Ulcerative Colitis: A Systematic Review and Meta‐Analysis

Objective . To evaluate the efficacy and safety of mesalamine in conjunction with probiotics for ulcerative colitis. Methods . Random controlled trials (RCTs) were searched in PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure, Wanfang, and VIP (VIP Database for Chinese Technical Periodicals) from inception to October 2019. Methodological quality was assessed by the Cochrane Collaboration tool. The quality of evidence was rated by the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE). Data analysis was carried out in Review Manager 5.3. Results . A total of fifteen studies met the criteria for inclusion. Thirteen studies reported the clinical efficacy, three studies provided data on the clinical symptom scores, two trials reported disease activity index, four studies evaluated endoscopic score, and twelve studies reported adverse events. For ulcerative colitis (UC), mesalamine and probiotics had better clinical efficacy than mesalamine alone (≤8 weeks: RR = 1.12, 95% CI: 1.07–1.18, P < 0.0001; >8 weeks: RR = 1.25, 95% CI: 1.11–1.41, P = 0.0003). On the clinical symptom scores, disease activity index, and endoscopic score, UC patients receiving mesalamine and probiotics had significant difference than patients receiving mesalazine alone (MD = −2.02, 95% CI: −3.28 to −0.76, P = 0.002; MD = −1.20, 95% CI: −1.76 to −0.65, P < 0.001; and MD = −0.42, 95% CI: −0.61 to −0.23, P < 0.0001, respectively). There was no statistically significant difference in adverse events between the two groups (RR = 0.88, 95% CI: 0.54 to 1.43, P = 0.60). Conclusion . Our meta‐analysis results supported that mesalamine and probiotics were effective and safe in treating ulcerative colitis.

Tian, Chunying↗
DOE OSTI2022

ccp137/SUGAR

This package (SUrface-wave Grader with ARtificial intelligence or SUGAR) automatically assigns a quality score to surface-wave seismograms (SAC format) using a trained artificial neural network model (included). Specifically, the python script 01_apply_ann.py calculates probability scores for a list of SAC files. You may consider seismograms with probability scores larger than 0.5 as acceptable data. Note no scores will be given to seismograms that do not pass an initial check (e.g., insufficient number of data points). See https://doi.org/10.1002/essoar.10507941.3 for more details.

Chai, Chengping [Oak Ridge National Lab. (ORNL), O↗
DOE OSTI2023

Characteristics of Veterans With Depression Who Use the Veterans Choice Program of the Veterans Health Administration

Objective: The Veterans Choice Program (VCP) of the Veterans Health Administration (VHA) allowed eligible veterans to use their benefits with participating providers outside the VHA. The authors aimed to identify characteristics of veterans with depression who used or did not use mental health care through the VCP. Methods: In this cross-sectional study, the authors analyzed secondary data from the national VHA Corporate Data Warehouse. VHA administrative data were linked with VCP claims to examine characteristics of VCP-eligible veterans with depression. Further, the study sample included 595,943 unique veterans who were enrolled in the VHA before 2013, were eligible for the VCP in 2016, were alive in 2018, and had an assessed Patient Health Questionnaire–9 (PHQ-9) score or depressive disorder diagnosis documented in the VHA between 2016 and 2018. Results: Veterans who used the VCP had lower medical comorbidity scores and lived in less socioeconomically disadvantaged counties, compared with veterans who received only VHA care. VCP veterans were also more likely to have a PHQ-9 score assessment and to have higher mean depression scores. Mean counts of annual mental health visits per 1,000 veterans were markedly higher for direct VHA care than for care provided via the VCP. As a percentage of the total counts of visits per 1,000 veterans across the VCP and VHA, residential programs and outpatient procedures were the services that were most frequently delivered through the VCP. Conclusions: Between 2016 and 2018, the VCP was used primarily to augment mental health care provided by the VHA, rather than to fill a gap in care.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Mobility Energy Productivity Evaluation of On-Demand Transit: A Case Study in Arlington, Texas

On-demand transit (ODT) systems are increasing in number and size. To evaluate and quantify outcomes, the research team utilizes the mobility energy productivity (MEP) metric, which is a holistic accessibility measure, to analyze and compare the mobility of various transportation modes in Arlington, Texas. The MEP tool is applied to the ODT system in Arlington, Texas, as well as to five existing transportation modes (driving, transportation network company, transit, biking, and walking). Six ODT scenarios are also analyzed and compared. The analysis is focused on the opportunities that an ODT system presents for transportation disadvantaged communities (DACs) with low rates of car ownership. Although driving received the highest MEP score—a finding typical for a U.S.A. city— the results for the ODT system reveal that it serves those in DACs effectively, helping to achieve an equity design goal. ODT improved the average MEP score across the service area by 83% when considering only accessible, nonprivate vehicle modes (biking, transit, and ODT). For the ODT scenarios, decreasing the wait time by 50% compared with the baseline scenario led to a nearly 160% increase in the MEP score, whereas increasing the ODT travel speed by 21% led to an 80% improvement in the MEP score. As analyzed through the MEP tool, here this paper demonstrates how ODT can enhance mobility, particularly for DACs. The results of an MEP analysis can be used by researchers and transit agencies to compare transportation modes and improve the effectiveness of transportation systems across a service area.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Proteome-scale Structure Prediction Data - Pseudodesulfovibrio mercurii

The number of proteins predicted for Pseudodesulfovibrio mercurii is 3,446, each of which have five predicted structures from an AlphaFold run, as well as structural alignment results using the TMscore-based structural alignment method within the APoc program. Specifically, AlphaFold outputs the atoms and coordinates of the protein model in human-readable PDB files and quantitative prediction metrics in Python PICKLE files. The 5 models have been ranked based on the predicted TM-score (pTMS), a quantitative confidence metric output by AlphaFold that reports on protein model quality. The top ranked model has undergone an energy minimization calculation to relax and remove any potential clashes in the atomic coordinates. Structural alignment results are stored in two files for each protein; the top ranked model (as discussed above) is used for all alignment analyses. Both are compressed gzip files that, once unpacked, are human readable. The first file is the TMalign score results and contains the quantitative metrics for the top alignments between the predicted structure and experimental structures from the PDB70, a curated non-redundant database of about 80,000 experimental structures developed by the Soding lab. Each data point in this file is directly associated with one experimental structure; PDB ID and brief meta-data about the protein taken from the PDB70 file are reported alongside the quantitative metrics. The second results file contains the raw results associated with each alignment reported in the score results file. Specifically, the translation and rotation arrays for each alignment are provided so that the structural alignment can be recreated. Additionally, residue-level scores are reported to quantify the closeness of the aligned residues between the predicted and experimental models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Modeling protected species distributions and habitats to inform siting and management of pioneering ocean industries: A case study for Gulf of Mexico aquaculture

Marine Spatial Planning (MSP) provides a process that uses spatial data and models to evaluate environmental, social, economic, cultural, and management trade-offs when siting (i.e., strategically locating) ocean industries. Aquaculture is the fastest-growing food sector in the world. The United States (U.S.) has substantial opportunity for offshore aquaculture development given the size of its exclusive economic zone, habitat diversity, and variety of candidate species for cultivation. However, promising aquaculture areas overlap many protected species habitats. Aquaculture siting surveys, construction, operations, and decommissioning can alter protected species habitat and behavior. Additionally, aquaculture-associated vessel activity, underwater noise, and physical interactions between protected species and farms can increase the risk of injury and mortality. In 2020, the U.S. Gulf of Mexico was identified as one of the first regions to be evaluated for offshore aquaculture opportunities as directed by a Presidential Executive Order. We developed a transparent and repeatable method to identify aquaculture opportunity areas (AOAs) with the least conflict with protected species. First, we developed a generalized scoring approach for protected species that captures their vulnerability to adverse effects from anthropogenic activities using conservation status and demographic information. Next, we applied this approach to data layers for eight species listed under the Endangered Species Act, including five species of sea turtles, Rice’s whale, smalltooth sawfish, and giant manta ray. Next, we evaluated four methods for mathematically combining scores (i.e., Arithmetic mean, Geometric mean, Product, Lowest Scoring layer) to generate a combined protected species data layer. The Product approach provided the most logical ordering of, and the greatest contrast in, site suitability scores. Finally, we integrated the combined protected species data layer into a multi-criteria decision-making modeling framework for MSP. This process identified AOAs with reduced potential for protected species conflict. These modeling methods are transferable to other regions, to other sensitive or protected species, and for spatial planning for other ocean-uses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Performance of solar leasing for low- and middle-income customers in Connecticut

Policymakers are increasingly interested in expanding access to rooftop photovoltaic systems. This study analyzes the financial performance of a Connecticut Green Bank (CGB) solar leasing program, run in partnership with PosiGen, that targets low- and moderate-income customers. We show that this program has successfully reached underserved customers and has reasonable repayment rates given the credit characteristics of the participants. The CGB/PosiGen program reaches many more underserved customers than other PV financing programs in Connecticut.For example, the majority of CGB/PosiGen participants (58%) live in census tracts that have a median income of less than 80% of the area median income (AMI). In contrast, only 9% of participants in the other CGB solar financing programs live in these census tracts. Furthermore, the majority of CGB/PosiGen participants (56%) have FICO scores that would generally be considered non-prime (<670), whereas only 2% of participants in the other programs have similarly low scores. Credit, not income, is the primary factor that explains participants’ financial performance. Overall, we find that delinquency and annualized losses are higher for PosiGen (2.3% and 0.9%) than for other CGB programs (1.4% and 0.1%). Across the CGB programs, lower credit scores are associated with higher rates of delinquency and loss. Therefore, participants’ lower credit scores explain much of the program’s higher rates of delinquency and annualized losses. PosiGen leases perform competitively with market-rate solar and non-solar leases and loans. When compared to securities backed by market-rate PV loans and leases with similar amounts of seasoning, we find that the PosiGen leases have higher delinquency rates but comparable gross loss rates. The similarity in losses is notable given that loss rates for PosiGen leases were higher than those of the other CGB leases and loans. Rather than the PosiGen leases having high loss rates, other CGB leases and loans have unusually low loss rates. We also compare PosiGen to non-solar benchmarks, including indices of auto and consumer loans. We find that the PosiGen leases have significantly less delinquency than non-prime auto loans and have performance comparable to many consumer loans. The U.S. Department of Energy’s Solar Energy Technologies Office supported this research.

14 SOLAR ENERGY↗
DOE OSTI2021

Proof that Combining the Forced-collision and DXTRAN Monte Carlo Variance-reduction Techniques is Fair

This report provides mathematical proof that the MCNP DXTRAN (also known in other codes as forced-flight) and forced-collision variance-reduction techniques do not bias the expected value of Monte Carlo simulation estimates when combined. Proof is also provided that the techniques are unbiased when used independently. To prove that the techniques are unbiased, this report derives the first History Score Moment Equation (HSME) for non-multiplying media employing only forced collisions, only DXTRAN, and then both the variance-reduction techniques combined, as defined next. The HSMEs are found by forming the History Score Probability Density Functions (HSPDFs) and then taking the first score moment. Following its derivation, each HSME with a variance-reduction technique employed is reduced to the HSME for an analog simulation. Because the HSME represents the expected contribution to estimators in the simulation, reducing the HSME with variance reduction to the analog HSME shows that the simulation is unbiased despite the variance-reduction technique considered in the HSME. Analysis regarding higher-score moments of each technique is the subject of prior work and is not addressed herein. Throughout this work, the phase space p is defined to be the particle position x, direction-of-flight unit vector $\hat{Ω}$, energy E, and statistical weight w, $$p ≡ (x; \hat{Ω}; E; w).$$ A reduced phase-space excluding the statistical weight of the particle, $$r ≡ (x; \hat{Ω}; E),$$ is also used.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Power Supply Options for the Marpi Landfill, Saipan: Feasibility Study

The Marpi Landfill, located on the northern end of the island of Saipan in the Commonwealth of the Northern Mariana Islands (CNMI), is powered by an on-site diesel generator that only operates when the landfill is open and staffed. The CNMI Office of Planning and Development (OPD) aspires to provide the Marpi Landfill with 24-hour power availability despite its remote location and to increase the use of sustainable energy within the CNMI. CNMI has a 20% target for renewable energy consumption, as documented in Sustainable Development Goal #7 in the Comprehensive Sustainable Development Plan (OPD 2021) and the renewable portfolio standard (GPO 2014). To accomplish these goals, the U.S. Department of Energy, through its Interagency Reimbursable Work Agreement with the Federal Emergency Management Agency, funded this feasibility study to assess and prioritize power supply options for the landfill. The availability of solar and wind resources varies seasonally, as does the load. A BESS can help to balance mismatches between generation and load on short (hourly or daily) timescales, but not across seasons. The microgrid scenarios evaluated for Marpi consider options for technology combinations that will both meet the load and utilize available resources, despite the challenge presented by higher loads and lower solar and wind availability during the rainy season, depicted in Figure ES-2. The seven scenarios evaluated are summarized in Table ES-1. Each scenario’s configuration was optimized to include component capacities that reduce capital and operating costs, meet the load, and minimize carbon emissions, as feasible. The costs and levelized cost of energy (LCOE) shown do not assume the use of any grant funding or incentives, although these options were also evaluated. To assist with decision-making, a prioritization matrix (Table ES-3) was created to compare the microgrid scenarios evaluated in this feasibility study according to various stakeholder priorities. The prioritization metrics were chosen based on discussions with OPD and will be finalized through stakeholder feedback. The scenarios were given a score between 1 and 7 for each prioritization metric (the lower the score, the higher the priority), and total scores were calculated using assigned weights based on the relative priority of each metric. The total scores were then ranked to produce a prioritized list of microgrid scenarios based on the metrics most important to the project stakeholders. As shown, scenario 4 (100 kW of solar PV, a 75 kW/300 kWh BESS, and 160 kW of diesel generation) ranks highest.

14 SOLAR ENERGY↗
DOE OSTI2024

Criticality Analysis of Wind Turbine Components - Intern Poster [Poster]

Wind turbines are an important part of critical energy infrastructure, with wind farms generating more than 10% of US energy in 2023. The goal of this project is to identify and analyze major, common components of wind turbines to reach a preliminary understanding of which should be considered most critical in terms of turbine operation and attack surface. At the time of this project, minimal data was available regarding component costs and lead times, so a qualitative risk assessment approach was used. Components were given a score of 1-5 in four categories– cost to repair, operational downtime, ease of physical attack, and ease of cyber attack. An overall component criticality score was assigned based on the sum of those scores, with a higher score indicating higher criticality. The turbine control system was identified as the most critical component, closely followed by the blades, structural components, and gearbox. This is ongoing project, and further research on the supply chain for wind turbine components will allow for a deeper and more concrete understanding of component criticality.

17 WIND ENERGY↗
DOE OSTI2025

PROACTIVE Focus Area 4: Structured Decision Metrics Analysis (Final Report)

A structured decision metrics analysis was developed as one of the tasks under PROACTIVE’s Focus Area 4 (FA4) and used structured decision metrics for processes, items, and facilities (PIF) to determine the efficacy of an M&V system in meeting treaty goals and technical objectives. The method starts with the functional decomposition of a “treaty” with the M&V system overlaid on it. A Functional Decomposition Rubric (FDR) for each PIF is used to determine a score ranging from 0 (weak) to 4 (strong) for assurance, security, and burden. The individual scores are combined to provide an overall Verification System Score (VSS) which assesses the overall verification system’s suitability given goals; scores for each step of the process are also given. The outcome of the evaluation is to identify needs or modifications to the enterprise model, verification system, or proposed testbed capabilities. VeriScore was used to evaluate FA4’s Spiral 0 exercise; those results are included in this report. The VeriScore and FDR framework can also be used in a non-treaty environment, as any goal/objective/method structure will work, thus expanding its applicability beyond traditional arms control structures.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Blueprint: Stakeholder-Specific Vulnerability Categorization Guidance

Vulnerability management is a process of discovering, analyzing, and handling new or reported security vulnerabilities in systems to prevent the systems from being exploited, to reduce risk, and to protect assets. For vulnerability analysis, handling, and response, the prioritization of organizational and analyst resources must precede. The Common Vulnerability Scoring System (CVSS) is a standard prioritization method that is used to rate the severity of security vulnerabilities in systems by assigning numerical severity scores, but it does not provide clear guidelines of how the numerical severity scores might inform decisions. The Stakeholder-Specific Vulnerability Categorization (SSVC) provides a method for prioritizing vulnerabilities based on the needs of the stakeholders involved in the vulnerability management process. Instead of the numerical scoring used in the CVSS, the SSVC focuses on contextual decision-making to determine how quickly and effectively an organization should respond to vulnerabilities. The main functionality of the SSVC accommodates the diversity of the stakeholders in the vulnerability management process, including finders, vendors, coordinators, deployers, and others. So, the SSVC should be designed to be used by any of these stakeholders, and it should be customizable to enable specific stakeholder decision models and risk appetites.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making

The Centers for Disease Control and Prevention (CDC) Select Agent Program establishes a list of biological agents and toxins that potentially threaten public health and safety, the procedures governing the possession, utilization, and transfer of those agents, and training requirements for entities working with them. Every 2 years the Program reviews the select agent list, utilizing subject matter expert (SME) assessments to rank the agents. In this study, we explore the applicability of multi-criteria decision analysis (MCDA) techniques and logic tree analysis to support the CDC Select Agent Program biennial review process, applying the approach broadly to include non-select agents to evaluate its generality. We conducted a literature search for over 70 pathogens against 15 criteria for assessing public health and bioterrorism risk and documented the findings for archiving. The most prominent data gaps were found for aerosol stability and human infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. Analysis of results obtained from a two-dimensional plot of weighted scores for difficulty of attack (i.e., exposure and production criteria) vs. consequences of an attack (i.e., consequence and mitigation criteria) provided greater fidelity for understanding agent placement compared to a 1-to-n ranking and was used to define a region in the upper right-hand quadrant for identifying pathogens for consideration as select agents. A sensitivity analysis varied the numerical weights attributed to various properties of the pathogens to identify potential quantitative (x and y) thresholds for classifying select agents. The results indicate while there is some clustering of agent scores to suggest thresholds, there are still pathogens that score close to any threshold, suggesting that thresholding “by eye” may not be sufficient. The sensitivity analysis indicates quantitative thresholds are plausible, and there is good agreement of the analytical results with select agent designations. A second analytical approach that applied the data using a logic tree format to rule out pathogens for consideration as select agents arrived at similar conclusions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Identification of Galaxy–Galaxy Strong Lens Candidates in the DECam Local Volume Exploration Survey Using Machine Learning

We perform a search for galaxy–galaxy strong lens systems using a convolutional neural network (CNN) applied to imaging data from the first public data release of the DECam Local Volume Exploration Survey, which contains ~520 million astronomical sources covering ~4000 deg 2 of the southern sky to a 5σ point–source depth of g = 24.3, r= 23.9, i = 23.3, and z = 22.8 mag. Following the methodology of similar searches using Dark Energy Camera data, we apply color and magnitude cuts to select a catalog of ~11 million extended astronomical sources. After scoring with our CNN, the highest-scoring 50,000 images were visually inspected and assigned a score on a scale from 0 (not a lens) to 3 (very probable lens). We present a list of 581 strong lens candidates, 562 of which are previously unreported. We categorize our candidates using their human-assigned scores, resulting in 55 Grade A candidates, 149 Grade B candidates, and 377 Grade C candidates. We additionally highlight eight potential quadruply lensed quasars from this sample. Due to the location of our search footprint in the northern Galactic cap (b > 10 deg) and southern celestial hemisphere (decl. < 0 deg), our candidate list has little overlap with other existing ground-based searches. Where our search footprint does overlap with other searches, we find a significant number of high-quality candidates that were previously unidentified, indicating a degree of orthogonality in our methodology. We report properties of our candidates including apparent magnitude and Einstein radius estimated from the image separation.

79 ASTRONOMY AND ASTROPHYSICS↗