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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Computer processing through distance-based quality score method in geospatial-temporal semantic graphs

A computer-implemented method of improving processing of overhead image data by a processor using a distance-based quality score in a geospatial-temporal semantic graph. An allowable range for each attribute in the subgraph search template is defined. For each match in a comparison, attribute values of each match element are compared against the preferred range and the allowable range to compute a corresponding distance of each match attribute from the subgraph search template. A corresponding overall match quality score is determined for each match from the subgraph search template, wherein determining the corresponding overall match qualities is performed using a corresponding required quality score and a corresponding optional quality score. All corresponding overall match quality scores are sorted into an ordered list and then displayed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A score-based diffusion model approach for adaptive learning of stochastic partial differential equation solutions

In this paper, we propose a novel framework for adaptively learning the time-evolving solutions of stochastic partial differential equations (SPDEs) using score-based diffusion models within a recursive Bayesian inference setting. SPDEs play a central role in modeling complex physical systems under uncertainty, but their numerical solutions often suffer from model errors and reduced accuracy due to incomplete physical knowledge and environmental variability. To address these challenges, we encode the governing physics into the score function of a diffusion model using simulation data and incorporate observational information via a likelihood-based correction in a reverse-time stochastic differential equation. This enables adaptive learning through iterative refinement of the solution as new data becomes available. To improve computational efficiency in high-dimensional settings, we introduce the ensemble score filter, a training-free approximation of the score function designed for real-time inference. Numerical experiments on benchmark SPDEs demonstrate the accuracy and robustness of the proposed method under sparse and noisy observations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A new control score concept for building performance assessment

In buildings, performance assessment often focuses on energy use with metrics such as energy use intensity (EUI) used to benchmark performance. However, energy performance of a building is fundamentally determined by the control system that engages the energy-using systems. There are two aspects of control that are of particular importance: (1) the ability to regulate process variables to their setpoints; and (2) whether the setpoints are at the right levels and/or following desired profiles. Most buildings do not reach their energy efficiency potential due to deficiencies in control performance and operators do not have access to metrics that can illuminate these deficiencies. Here this paper addresses this problem by providing novel techniques that combine these two aspects of control performance into a single standardized score on the scale of 0-10. The concept of a standardized control scores enables all systems in a building to be compared on the same scale and also for scores to be rolled up to different levels in the building and system hierarchy for system-wide analysis. The paper presents the theory for the method, describes a prototype tool for displaying scores, and presents results from application to a large building in Minneapolis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Automated Scoring of Morphological Changes in Images of Pentaerythritol Tetranitrate

Recent advances in characterization techniques that generate large datasets of material microstructure images require robust, automated image-processing. We applied an unsupervised anomaly detection method called feature anomaly detection system (FADS) to automatically detect and quantify microstructure changes in images of the explosive pentaerythritol tetranitrate (PETN) aged at various temperatures. We demonstrated the FADS approach on two-dimensional images extracted from computed tomography scans, but the same technique can be readily applied to other imaging modalities. FADS calculates anomaly scores on the basis of differences in filter activations of nominal and test data in pretrained convolutional neural networks. The FADS scores successfully differentiated between pristine PETN and PETN aged at a temperature where material coarsening occurred. Morphological metric analysis of segmented images verified observed trends in FADS scores as a function of aging temperature and aging time, specifically by calculating volume fractions, specific boundary lengths, two-point correlation functions, and local thicknesses. Here, the FADS technique has two important advantages compared to traditional morphological analysis: First, it uses grayscale images as input, rather than images that are segmented to separate the appropriate phases; and second, FADS scores capture any type of changes among image sets, rather than requiring prior knowledge or selection of a relevant set of metrics.

Accelerated aging↗
DOE OSTI2023

BLINK enables ultrafast tandem mass spectrometry cosine similarity scoring

Metabolomics has a long history of using cosine similarity to match experimental tandem mass spectra to databases for compound identification. Here we introduce the Blur-and-Link (BLINK) approach for scoring cosine similarity. By bypassing fragment alignment and simultaneously scoring all pairs of spectra using sparse matrix operations, BLINK is over 3000 times faster than MatchMS, a widely used loop-based alignment and scoring implementation. Using a similarity cutoff of 0.7, BLINK and MatchMS had practically equivalent identification agreement, and greater than 99% of their scores and matching ion counts were identical. This performance improvement can enable calculations to be performed that would typically be limited by time and available computational resources.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Next-generation yeast-two-hybrid analysis with Y2H-SCORES identifies novel interactors of the MLA immune receptor

Protein-protein interaction networks are one of the most effective representations of cellular behavior. In order to build these models, high-throughput techniques are required. Next-generation interaction screening (NGIS) protocols that combine yeast two-hybrid (Y2H) with deep sequencing are promising approaches to generate interactome networks in any organism. However, challenges remain to mining reliable information from these screens and thus, limit its broader implementation. Here, we present a computational framework, designated Y2H-SCORES, for analyzing high-throughput Y2H screens. Y2H-SCORES considers key aspects of NGIS experimental design and important characteristics of the resulting data that distinguish it from RNA-seq expression datasets. Three quantitative ranking scores were implemented to identify interacting partners, comprising: 1) significant enrichment under selection for positive interactions, 2) degree of interaction specificity among multi-bait comparisons, and 3) selection of in-frame interactors. Using simulation and an empirical dataset, we provide a quantitative assessment to predict interacting partners under a wide range of experimental scenarios, facilitating independent confirmation by one-to-one bait-prey tests. Simulation of Y2H-NGIS enabled us to identify conditions that maximize detection of true interactors, which can be achieved with protocols such as prey library normalization, maintenance of larger culture volumes and replication of experimental treatments. Y2H-SCORES can be implemented in different yeast-based interaction screenings, with an equivalent or superior performance than existing methods. Proof-of-concept was demonstrated by discovery and validation of novel interactions between the barley nucleotide-binding leucine-rich repeat (NLR) immune receptor MLA6, and fourteen proteins, including those that function in signaling, transcriptional regulation, and intracellular trafficking.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Score-based deterministic density sampling

We propose a deterministic sampling framework using Score-Based Transport Modeling for sampling an unnormalized target density π given only its score ∇ log π. Our method approximates the Wasserstein gradient flow on KL($f_t$∥π) by learning the time-varying score ∇ log $f_t$ on the fly using score matching. While having the same marginal distribution as Langevin dynamics, our method produces smooth deterministic trajectories, resulting in monotone noise-free convergence. We prove that our method dissipates relative entropy at the same rate as the exact gradient flow, provided sufficient training. Numerical experiments validate our theoretical findings: our method converges at the optimal rate, has smooth trajectories, and is often more sample efficient than its stochastic counterpart. Experiments on high-dimensional image data show that our method produces high-quality generations in as few as 15 steps and exhibits natural exploratory behavior. The memory and runtime scale linearly in the sample size.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Assessment of lubricated contacts: Mechanisms of scuffing and scoring

Scoring and scuffing are defined as two distinct but related forms of failure of hardened ferrous components lubricated by liquids. Experimental observations of these phenomena are described, and criteria for scoring and scuffing are discussed. The mechanisms proposed by various authors to explain these observations are enumerated. The view presented here is that, under conditions yet to be defined, scoring is a gradual breakdown of the lubrication of interacting asperities, such lubrication being boundary or microelastohydrodynamic in nature, or a mixture of the two. The final scuffing stage represents a breakdown of the main elastohydrodynamic system, but this may be triggered by the deterioration in surface topography as a result of scoring. An extension of published theoretical treatment of elastohydrodynamic breakdown is proposed, and a critical experiment to assess the importance of edge effects in band contacts is suggested. The practical implications of the proposed mechanism are reviewed, and recommendations for further work are made. A possible thermal instability mechanism for the breakdown of boundary lubrication is outlined.

Dyson, A.↗
DOE OSTI2022

A novel methodology to integrate outcomes regarding perioperative pain experience into a composite score: Prediction model development and validation

Abstract Background An integrated score that globally assesses perioperative pain experience and rationally weights each component has not yet been developed. Methods A development dataset specific to adult Chinese patients undergoing orthopaedic surgery was obtained from PAIN OUT (1985 qualified patients of 2244). A more recent validation dataset obeying the same conditions was obtained from the Chinese Anaesthesia Shared‐database Platform (1004 qualified patients of 1032). Outcomes were assessed using the International Pain Outcomes Questionnaire (IPO‐Q), which comprises key patient‐level outcomes of perioperative pain management, including pain experience and perceptions of care. Using principal component analysis and regression models, a composite score (CS) was inferred to integrate pain experience. The discrimination of the CS for dissatisfaction and desire for more pain treatment was compared with that of the worst pain score. Results A CS was developed from the 12 items of the IPO‐Q regarding pain experience. The weight for calculating the CS was worst pain 11, least pain 17, time spent in severe pain 11, interference with activity in bed 9, interference with breathing deeply or coughing 10, interference with sleep 9, anxiety 12, helplessness 12, nausea 0, drowsiness 2, itch 5 and dizziness 2. In external validation, the CS indicated superior discrimination to the worst pain in predicting dissatisfaction ( p < 0.001) and desire for more pain treatment ( p < 0.001). Conclusions This study introduced a methodology to integrate outcomes regarding perioperative pain experience into a CS, which was based on the weight of each item. Significance This novel methodology sheds additional light on the riveting issue of carefully integrating several measures into a composite endpoint, which may be useful for quality improvement purposes when addressing the impact of a change in clinical practice.

Jiang, Bailin↗
DOE OSTI2024

A Corrected Score Function Framework for Modelling Circadian Gene Expression

Many biological processes display oscillatory behaviour based on an approximately 24 h internal timing system specific to each individual. One process of particular interest is gene expression, for which several circadian transcriptomic studies have identified associations between gene expression during a 24 h period and an individual's health. A challenge with analysing data from these studies is that each individual's internal timing system is offset relative to the 24 h day-night cycle, where day–night cycle time is recorded for each collected sample. Laboratory procedures can accurately determine each individual's offset and determine the internal time of sample collection. However, these laboratory procedures are labour-intensive and expensive. Here, in this paper, we propose a corrected score function framework to obtain a regression model of gene expression given internal time when the offset of each individual is too burdensome to determine. A feature of this framework is that it does not require the probability distribution generating offsets to be symmetric with a mean of zero. Simulation studies validate the use of this corrected score function framework for cosinor regression, which is prevalent in circadian transcriptomic studies. Illustrations with data from three circadian transcriptomic studies further demonstrate that the proposed framework consistently mitigates bias relative to using a score function that does not account for this offset.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The Clinical Cell-Cycle Risk (CCR) score Is Associated With Metastasis After Radiation Therapy and Provides Guidance on When to Forgo Combined Androgen Deprivation Therapy With Dose-Escalated Radiation

The clinical cell-cycle risk (CCR) score, which combines the University of California, San Francisco's Cancer of the Prostate Risk Assessment (CAPRA) and the cell cycle progression (CCP) molecular score, has been validated to be prognostic of disease progression for men with prostate cancer. This study evaluated the ability of the CCR score to prognosticate the risk of metastasis in men receiving dose-escalated radiation therapy (RT) with or without androgen deprivation therapy (ADT).

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Incorporating uncertainty for enhanced leaderboard scoring and ranking in data competitions

Data competitions have become a popular and cost-effective approach for crowdsourcing versatile solutions from diverse expertise. Current practice relies on the simple leaderboard scoring based on a given set of competition data for ranking competitors and distributing the prize. However, a disadvantage of this practice in many competitions is that a slight difference in the scores due to the natural variability of the observed data could result in a much larger difference in the prize amounts. In this article, we propose a new strategy to quantify the uncertainty in the rankings and scores from using different data sets that share common characteristics with the provided competition data. By using a bootstrap approach to generate many comparable data sets, the new method has four advantages over current practice. Furthermore, during the competition, it provides a mechanism for competitors to get feedback about the uncertainty in their relative ranking. After the competition, it allows the host to gain a deeper understanding of the algorithm performance and their robustness across representative data sets. It also offers a transparent mechanism for prize distribution to reward the competitors more fairly with superior and robust performance. Finally, it has the additional advantage of being able to explore what results might have looked like if competition goals evolved from their original choices. The implementation of the strategy is illustrated with a real data competition hosted by Topcoder on urban radiation search.

42 ENGINEERING↗
DOE OSTI2020

Exploit, Malware And Vulnerability Scoring Application

Exploit, Malware and Vulnerability (EMV) is a way for users to create and use their own scoring schema against various configurations they might be scoring cyber issues against. This application was created to take the EMV process and develop a GUI to accomplish this task. EMV application is customizable and configurable, interfaces with STIX objects and allows exporting scored objects.

Priest, ZacharyM↗
DOE OSTI2023

New machine learning techniques for simulation-based inference: InferoStatic nets, kernel score estimation, and kernel likelihood ratio estimation

We propose an intuitive, machine-learning approach to multiparameter inference, dubbed the InferoStatic Networks (ISN) method, to model the score and likelihood ratio estimators in cases when the probability density can be sampled but not computed directly. The ISN uses a backend neural network that models a scalar function called the inferostatic potential \varphi φ . In addition, we introduce new strategies, respectively called Kernel Score Estimation (KSE) and Kernel Likelihood Ratio Estimation (KLRE), to learn the score and the likelihood ratio functions from simulated data. We illustrate the new techniques with some toy examples and compare to existing approaches in the literature. We mention en passant some new loss functions that optimally incorporate latent information from simulations into the training procedure.

Kong, Kyoungchul↗
DOE OSTI2022

Method for Generating Expert Derived Confidence Scores

We executed a pilot demonstration of a methodology for developing a new confidence metric to help operators calibrate their trust in ML event classifiers. This confidence metric was derived from domain expert judgment and was accompanied with a qualitative description describing the reason for each confidence rating. After learning the boundaries of an ML’s performance by studying a subset of events an SME rated his confidence in the ML’s ability to classify similar events and provided an explanation for his ratings. To demonstrate this methodology, we developed our expert driven confidence scores for the ML event classifier within the ESAMS. Next, we assessed the accuracy of the human expert confidence scores relative to the ML’s uncertainty quantification scores. This report includes a description of our methodology, summary of our findings and future directions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

SCORE (Synthesis of COnsists as Rolling Energy microgrids) (Final Technical Report)

The SCORE toolset is an open source, web-based application to assess the impact of new powering technologies on railroad performance, specifically technologies capable of both putting power into the rail (motive force) and taking power from the rail (regeneration). SCORE’s primary goal is generate trade studies to analyze different powering and train make-up options to minimize energy usage and greenhouse gas generation. At the core of generating these trade spaces is calculating the optimal powering policy for the train given the makeup of the train, the route, and time constraints. This paper presents details on the algorithms used in SCORE to compute this powering policies that is fast and accurate, discusses its implementation in an Energy-Longitudinal Train Dynamics (E-LTD) model, compares it to naïve approaches, and demonstrates its use across a variety of train/route pairs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Characterizing Families of Spectral Similarity Scores and Their Use Cases for Gas Chromatography–Mass Spectrometry Small Molecule Identification

Metabolomics provides a unique snapshot into the world of small molecules and the complex biological processes that govern the human, animal, plant, and environmental ecosystems encapsulated by the One Health modeling framework. However, this “molecular snapshot” is only as informative as the number of metabolites confidently identified within it. The spectral similarity (SS) score is traditionally used to identify compound(s) in mass spectrometry approaches to metabolomics, where spectra are matched to reference libraries of candidate spectra. Unfortunately, there is little consensus on which of the dozens of available SS metrics should be used. This lack of standard SS score creates analytic uncertainty and potentially leads to issues in reproducibility, especially as these data are integrated across other domains. In this work, we use metabolomic spectral similarity as a case study to showcase the challenges in consistency within just one piece of the One Health framework that must be addressed to enable data science approaches for One Health problems. Here, using a large cohort of datasets comprising both standard and complex datasets with expert-verified truth annotations, we evaluated the effectiveness of 66 similarity metrics to delineate between correct matches (true positives) and incorrect matches (true negatives). We additionally characterize the families of these metrics to make informed recommendations for their use. Our results indicate that specific families of metrics (the Inner Product, Correlative, and Intersection families of scores) tend to perform better than others, with no single similarity metric performing optimally for all queried spectra. This work and its findings provide an empirically-based resource for researchers to use in their selection of similarity metrics for GC-MS identification, increasing scientific reproducibility through taking steps towards standardizing identification workflows.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Sensitivity of the ACCP Value Framework Science Benefit Score

NASA’s priorities for Earth Science are informed by the 2017-2027 Decadal Survey for Earth Science and Applications from Space of the National Academies of Sciences, Engineering and Medicine. In that document, five Designated Observables are identified as priorities for implementation: Aerosols, Cloud-Convection-Precipitation, Surface Biology, Mass Change, and Surface Deformation Change. In 2019, NASA initiated four multi-year studies to formulate, assess, and recommend potential Observing System concepts that are responsive to the recommendations of the Earth Science Decadal Survey. The Aerosols, Clouds, Convection, and Precipitation (ACCP) study investigates opportunities for synergistic science resulting from implementations that combine both Aerosols science objectives and Clouds, Convection, and Precipitation science objectives. For the ACCP study, a Value Framework was designed to introduce structure, transparency, and traceability in the mission down-select decision process. This paper presents a sensitivity analysis that was conducted to characterize the behavior of the science benefit score of the ACCP Value Framework. it includes derivations of the sensitivity analysis equations, numerical analyses of the behavior of the combined benefit score, and the conclusions drawn from the results of the work that was conducted. The results of this analysis were key to ensuring that the aggregated science benefit scores would enable the team to differentiate and contrast across concepts.

John McLaughlan↗