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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Neighborhood sociome factors and pediatric asthma exacerbations: Protective role of tree crown density and importance of pharmacy access in Chicago's south side

Abstract Background Pediatric asthma exacerbations remain a critical public health concern, particularly in historically underserved urban settings. Objective This study investigates sociome factors—the social context of disease—associated with asthma exacerbations among children living in Chicago's South Side, leveraging clinical and publicly available generalizable census tract‐level datasets from agencies including ChiVes, the City of Chicago Data Portal, EPA, Census Bureau, HUD, NOAA, and more. The aim is to uncover novel hypotheses for potential new interventions. Methods A generalized linear model assessed associations with the outcome of asthma exacerbations while accounting for clustering at the patient level. Predictors included all variables from the Sociome Data Commons, including social, environmental, behavioral, economic, housing, and school variables. Results Predictors of decreased risk included patient age (+4.8 years, −22%), tree crown density (+6% coverage, −17%), parks per acre (+0.41, −8%), and labor market engagement (+0.8 points, −9%). Conversely, predictors of increased risk included increased distance to the nearest pharmacy (+0.28 miles, +12%), limited English skills (+2.3%, +10%), higher inequality (+0.08 points, +8%), and visits in the Spring (+11%) and Fall (+20%). Conclusion The results suggest that tree crown density, a novel finding in the context of asthma exacerbations, may play a protective role. Limited access to health care facilities such as pharmacies continues to complicate care. Clinical Implications These findings provide hypotheses for future interventions for long‐standing asthma disparities.

Allergy↗
DOE OSTI2016

SU-F-T-118: Characterization of Change in Fractional Anisotropy After Radiation Therapy: Does Nearby Disruption Predict for White Matter Damage?

Purpose: We investigated predictors of fractional anisotropy (FA) change in the corticospinal white matter tract (CST) following radiation therapy (RT). Methods: Diffusion tensor imaging (DTI) is a non-invasive modality which models water diffusion properties. FA quantifies the extent of directional bias—a decrease indicates disrupted white matter integrity. Fifteen patients with high-grade glioma underwent DTI scans before, and ten months after RT to 59.4–60 Gy. The CST was segmented using an automated atlas-based algorithm on all DTI images. Treatment planning CT and DTI images were aligned using non-linear registration allowing for baseline FA, follow-up FA, and absorbed dose to be determined in each voxel. Relative FA change was dichotomized into a binary outcome using 25% decrease as cutoff. Three metrics were assessed as predictors: voxel dose, distance from the voxel to the center of the CST (Rc), and the number of neighboring voxels (Nadj from 0 to 26) with ≥25% decrease in FA. Logistic regression and the area under the receiver-operating characteristics curve (AUC) analysis were performed for each patient. Results: Median age of the cohort was 59 years (range: 40–85). The average number of voxels in the CST amongst all patients was 1181 (±172, SD). In logistic regression, the probability of FA change was highly associated with Nadj in all 15 patients with corresponding AUCs between 0.81 and 0.97. With all three metrics included in the logistic regression models, Nadj was highly significant (p<0.001) in all patients, voxel dose significant (p<0.05) in 3/15 patients, and Rc significant in 12/15 patients (p<0.05). Conclusion: The number of neighboring voxels with change in FA was the dominant predictor of FA change at any given voxel. This suggests that the microenvironment of surrounding white matter disruption after radiation therapy may drive local effects along a white matter tract. Pettersson and Cervino are funded by a Varian Medical Systems grant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-D-207B-05: Intra-Tumor Partitioning and Texture Analysis of DCE-MRI Identifies Relevant Tumor Subregions to Predict Early Pathological Response of Breast Cancer to Neoadjuvant Chemotherapy

Purpose: To predict early pathological response of breast cancer to neoadjuvant chemotherapy (NAC) based on quantitative, multi-region analysis of dynamic contrast enhancement magnetic resonance imaging (DCE-MRI). Methods: In this institution review board-approved study, 35 patients diagnosed with stage II/III breast cancer were retrospectively investigated using DCE-MR images acquired before and after the first cycle of NAC. First, principal component analysis (PCA) was used to reduce the dimensionality of the DCE-MRI data with a high-temporal resolution. We then partitioned the whole tumor into multiple subregions using k-means clustering based on the PCA-defined eigenmaps. Within each tumor subregion, we extracted four quantitative Haralick texture features based on the gray-level co-occurrence matrix (GLCM). The change in texture features in each tumor subregion between pre- and during-NAC was used to predict pathological complete response after NAC. Results: Three tumor subregions were identified through clustering, each with distinct enhancement characteristics. In univariate analysis, all imaging predictors except one extracted from the tumor subregion associated with fast wash-out were statistically significant (p< 0.05) after correcting for multiple testing, with area under the ROC curve or AUCs between 0.75 and 0.80. In multivariate analysis, the proposed imaging predictors achieved an AUC of 0.79 (p = 0.002) in leave-one-out cross validation. This improved upon conventional imaging predictors such as tumor volume (AUC=0.53) and texture features based on whole-tumor analysis (AUC=0.65). Conclusion: The heterogeneity of the tumor subregion associated with fast wash-out on DCE-MRI predicted early pathological response to neoadjuvant chemotherapy in breast cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Differential credibility assessment for statistical downscaling

Climate science is increasingly using (i) ensembles of climate projections from multiple models derived using different assumptions and/or scenarios and (ii) process-oriented diagnostics of model fidelity. Efforts to assign differential credibility to projections and/or models are also rapidly advancing. A framework to quantify and depict the credibility of statistically downscaled model output is presented and demonstrated. Here, the approach employs transfer functions in the form of robust and resilient generalized linear models applied to downscale daily minimum and maximum temperature anomalies at 10 locations using predictors drawn from ERA-Interim reanalysis and two global climate models (GCM; GFDL-ESM2M and MPI-ESM-LR). The downscaled time series are used to derive several impact relevant CLIMDEX temperature indices that are assigned credibility based on (1) the reproduction of relevant large-scale predictors by the GCMs (i.e. fraction of regression beta-weights derived from predictors that are well-reproduced) and (2) the degree of variance in the observations reproduced in the downscaled series following application of a new variance inflation technique. Credibility of the downscaled predictands varies across locations, between the two GCM and is generally higher for minimum temperature than maximum temperature. The differential credibility assessment framework demonstrated here is easy to use and flexible. It can be applied as is to inform decision makers regarding projection confidence, and/or extended to include other components of the transfer functions, and/or used to weight members of a statistically downscaled ensemble.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Predicting Postoperative Injury and Military Discharge Status After Knee Surgery in the US Army

Background: Researchers have assessed postoperative injury or disability predictors in the military setting but typically focused on 1 type of surgical procedure at a time, used relatively small sample sizes, or investigated mixed cohorts with civilian populations. Purpose: To identify the relationship between baseline variables and injury incidence or military discharge status in US Army soldiers after knee surgery. Study Design: Case-control study; Level of evidence, 3. Methods: Data were obtained from a repository containing personnel, performance, and medical records for all active-duty US Army soldiers. Multivariate logistic regressions were used to estimate the effects of numerous variables on postoperative injury or on medical discharge. Variable selection and model validation were conducted using the k-fold method. Results: A total of 7567 soldiers underwent knee surgery between 2017 and 2019. Meniscal procedures were the most common type of surgery (39%), and approximately 71% of the cohort had a postoperative injury. Significant predictors for sustaining a postoperative injury included having a previous nonknee injury (odds ratio [OR], 1.5), female sex (OR, 1.3), and Black race (OR, 1.2). Within 4 years after surgery, 17% of soldiers were discharged from the military because of knee-related disability. Significant predictors for discharge from duty included enlisted rank (OR, 2.3), recent fitness test failure (OR, 1.9), number of previous knee surgeries (OR, 1.7), and having a previous nonknee injury (OR, 1.6). Conclusion: After knee surgery, nearly three-fourths of the soldiers in this cohort sustained a postoperative injury and almost one-fifth of soldiers were medically discharged from the military within 4 years. This study identified variables that indicate statistically increased risk for these postoperative outcomes and highlighted potentially modifiable factors.

Orthopedics↗
DOE OSTI2023

Black-box statistical prediction of lossy compression ratios for scientific data

Lossy compressors are increasingly adopted in scientific research, tackling volumes of data from experiments or parallel numerical simulations and facilitating data storage and movement. In contrast with the notion of entropy in lossless compression, no theoretical or data-based quantification of lossy compressibility exists for scientific data. Users rely on trial and error to assess lossy compression performance. As a strong data-driven effort toward quantifying lossy compressibility of scientific datasets, we provide a statistical framework to predict compression ratios of lossy compressors. Our method is a two-step framework where (i) compressor-agnostic predictors are computed and (ii) statistical prediction models relying on these predictors are trained on observed compression ratios. Proposed predictors exploit spatial correlations and notions of entropy and lossyness via the quantized entropy. We study 8+ compressors on 6 scientific datasets and achieve a median percentage prediction error less than 12%, which is substantially smaller than that of other methods while achieving at least a 8.8× speedup for searching for a specific compression ratio and 7.8× speedup for determining the best compressor out of a collection.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Modeling precision treatment of breast cancer

Background: First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets. Results: We used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples. Conclusions: These results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Clinical Importance of Sputum in the Respiratory Tract as a Predictive Marker of Postoperative Morbidity After Esophagectomy for Esophageal Cancer

Background: Respiratory morbidity is common after esophagectomy and can be a major cause of surgery-related mortality. Thus, it is important to identify novel predictors that can preoperatively estimate the incidence of postoperative respiratory morbidity. Asymptomatic sputum in the respiratory tract is sometimes observed on preoperative computed tomography (CT). This study aimed to determine the clinical importance of sputum in the respiratory tract as a predictor of postoperative morbidity after esophagectomy for esophageal cancer. Patients and Methods: The study included 609 consecutive patients who underwent three-incisional esophagectomy for esophageal cancer between April 2005 and November 2018. Results: Among the patients, 76 (12.5%) had sputum in the respiratory tract on preoperative CT. This finding was significantly associated with older age, more extreme smoking habit, worse performance status, lower forced expiratory volume 1%, and more frequent pulmonary comorbidities. Additionally, the incidence of postoperative pneumonia was higher in these patients than in those without sputum (16 vs 8%, p = 0.028). Sputum in the main bronchus was associated with higher frequencies of morbidity of Clavien–Dindo classification (CDc) ≥ II (p = 0.019), severe morbidity of CDc ≥ IIIb (p = 0.058), pneumonia (p = 0.10), and pulmonary morbidity (p = 0.19) compared with the finding of sputum in the trachea alone. On multivariate analysis, sputum in the respiratory tract was an independent risk factor (hazard ratio, 2.07; 95% confidence interval, 1.019–4.207; p = 0.044) for postoperative pneumonia. Conclusions: Sputum in the respiratory tract is a novel predictor of postesophagectomy pneumonia. Patients with sputum in the more distal respiratory tract might have high risk of postoperative morbidities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Inpatient Opioid Use After Pancreatectomy: Opportunities for Reducing Initial Opioid Exposure in Cancer Surgery Patients

Background: Despite advances in enhanced surgical recovery programs, strategies limiting postoperative inpatient opioid exposure have not been optimized for pancreatic surgery. The primary aims of this study were to analyze the magnitude and variations in post-pancreatectomy opioid administration and to characterize predictors of low and high inpatient use. Methods: Clinical characteristics and inpatient oral morphine equivalents (OMEs) were downloaded from electronic records for consecutive pancreatectomy patients at a high-volume institution between March 2016 and August 2017. Regression analyses identified predictors of total OMEs as well as highest and lowest quartiles. Results: Pancreatectomy was performed for 158 patients (73% pancreaticoduodenectomy). Transversus abdominus plane (TAP) block was performed for 80% (n = 127) of these patients, almost always paired with intravenous patient-controlled analgesia (IV-PCA), whereas 15% received epidural alone. All the patients received scheduled non-opioid analgesics (median, 2). The median total OME administered was 423 mg (range 0–4362 mg). Higher total OME was associated with preoperative opioid prescriptions (p < 0.001), longer hospital length of stay (LOS; p < 0.001), and no epidural (p = 0.006). The lowest and best quartile cutoff was 180 mg of OME or less, whereas the highest and worst quartile cutoff began at 892.5 mg. After adjustment for inpatient team, only epidural use [odds ratio (OR) 0.3; p = 0.04] predicted lowest-quartile OME. Preoperative opioid prescriptions (OR 8.1; p < 0.001), longer operative time (OR 3.4; p = 0.05), and longer LOS (OR 1.1; p = 0.007) predicted highest-quartile OME. Conclusions: Preoperative opioid prescriptions and longer LOS were associated with increased inpatient OME, whereas epidural use reduced inpatient OME. Understanding the predictors of inpatient opioid use and the variables predicting the lowest and highest quartiles can inform decision-making regarding preoperative counseling, regional anesthetic block choice, and novel inpatient opioid weaning strategies to reduce initial postoperative opioid exposure.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Squamous Cell Carcinoma with Regional Metastasis to Axilla or Groin Lymph Nodes: a Multicenter Outcome Analysis

Background: Cutaneous squamous cell carcinoma (cSCC) of the trunk/extremities with nodal metastasis represents a rare but significant clinical challenge. Treatment patterns and outcomes are poorly described. Patients and Methods: Patients with cSCC who developed axilla/groin lymph node metastasis and underwent curative-intent surgery between 2005 and 2015 were identified at four Canadian academic centers. Demographics, tumor characteristics, treatment patterns, recurrence rates, and mortality were described. Overall survival (OS) and disease-free survival (DFS) were calculated using Kaplan–Meier analysis. Predictors of survival and any recurrence were explored using Cox regression and logistic regression models, respectively. Results: Of 43 patients, 70% were male (median age 74 years). Median follow-up was 38 months. Median time to nodal metastasis was 11.3 months. Thirty-one and 12 patients had nodal metastasis to the axilla and groin, respectively. A total of 72% and 7% received adjuvant and neoadjuvant radiation, respectively, while 5% received adjuvant chemotherapy. Following surgery, 26% patients developed nodal and/or distant disease recurrence. Crude mortality rate was 39.5%. Mean OS was 5.3 years [95% confidence interval (CI) 3.9–6.8 years], and 5-year OS was 55.1%. Mean DFS was 4.8 years (95% CI 3.3–6.2 years), and five-year DFS was 49.3%. Any recurrence was the only independent predictor of death [p = 0.036, odds ratio (OR) = 29.5], and extracapsular extension (p = 0.028, OR = 189) and age (p = 0.017, OR = 0.823) were independent predictors of recurrence. Conclusions: This represents the largest contemporary series to date of outcomes for patients with axilla/groin nodal metastases from cSCC. Despite aggressive treatment, outcomes remain modest, indicating the need for a continued multidisciplinary approach and integration of new systemic agents.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Machine learning of factors for improving oyster hatchery production

Oyster aquaculture and restoration in the Chesapeake Bay are vital, yet hatcheries frequently struggle with inconsistent larval growth and sudden mass mortality events. Unpredictable disruptions in larval production cause large economic losses, represent a perceived risk to growers, and impede industry expansion. To better understand associations between production yield and its potential predictors, we applied machine learning (random forest, and neural network) and statistical (generalized additive model) models to a comprehensive dataset of environmental, water quality, and operational parameters from a Maryland oyster hatchery, aiming to identify key yield predictors and develop a robust forecasting tool. We used recursive Boruta algorithm for variable selection, pinpointing critical predictors, and employed cross-validation to fine-tune model settings. Shapley value analysis offered crucial insights into model interpretations, highlighting week number, Normalized Difference Vegetation Index, salinity, turbidity, and fecundity as primary drivers of yield variability. For low-yield cases, salinity-related variables were particularly important. Our findings provide an early warning system for potential production downturns, empowering hatchery operators to make data-driven decisions for optimizing water conditions, feeding schedules, and broodstock management. By boosting predictability and efficiency, this research directly supports economic stability of the oyster industry and ecological health of the Chesapeake Bay.

Vishwakarma, Srishti [Oak Ridge National Laborator↗
DOE OSTI2020

Within and Among Fish Species Differences in Simulated Turbine Blade Strike Mortality: Limits on the Use of Surrogacy for Untested Species

Use of surrogacy remains a useful method for prioritizing research on representatives of at-risk groups of fishes, yet quantifiable evidence in support of its use is generally not available. Blade strike impact represents one of the most traumatic stressors experienced by fish during non-volitional movements through hydropower turbines. Here, we use data generated from laboratory trials on blade strike impact experiments to directly test use of surrogacy for salmonid and clupeid fishes. Results of logistic regression indicated that a -taxonomic (genus) variable was not a significant predictor of mortality among large rainbow trout and brook trout. Similar results were found for young-of-the-year shad species, but genus-level taxonomy was a significant predictor of mortality while species was not. Multivariate analysis of morphometric data showed that shad clustered together based on similarities in fish shape which was also closely associated with genus. Logistic regression including size as a major covariate suggested total fish length was not a significant predictor of mortality, yet dose–response data suggest differential susceptibility to lower strike velocities. We suggest that use of surrogacy among species is justifiable but should be avoided within a species since the effects of size remain unclear.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1980

The effect of viewing time, time to encounter, and practice on perception of aircraft separation on a cockpit display of traffic information

The concept of a cockpit display of traffic information (CDTI) includes the integration of air traffic, navigation, and other pertinent information in a single electronic display in the cockpit. Two studies were conducted to develop a clear and concise display format for use in later full-mission simulator evaluations of the CDTI concept. Subjects were required to monitor a CDTI for specified periods of time and to make perceptual judgments concerning the future position of a single intruder aircraft in relationship to their own aircraft. Experimental variables included: type of predictor information displayed on the two aircraft symbols; time to encounter point; length of time subjects viewed the display; amount of practice; and type of encounter (straight or turning). Results show that length of viewing time had little or no effect on performance; time to encounter influenced performance with the straight predictor but did not with the curved predictor; and that learning occurred under all conditions.

Oconnor, S.↗
NASA NTRS1980

Composite model of a 3-D image

This paper presents a composite model of a moving (3-D) image especially useful for the sequential image processing and encoding. A non-linear predictor based on the composite model is described. The performance of this predictor is used as a measure of the validity of the model for a real image source. The minimization of a total mean square prediction error provides an inequality which determines a condition for the profitable use of the composite model and can serve as a decision device for the selection of the number of subsources within the model. The paper also describes statistical properties of the prediction error and contains results of computer simulation of two non-linear predictors in the case of perfect classification between subsources.

Dukhovich, I. J.↗
NASA NTRS1981

Experimental evaluation of a perspective tunnel display for three-dimensional helicopter approaches

A computer-generated perspective tunnel display for a steep and strongly curved three-dimensional helicopter approach is studied. The necessary control variables for following a curved trajectory are analyzed, the effectiveness of superimposed predictor symbology is investigated, and a suitable predictor law is formulated. The theoretical considerations are validated by an extensive fixed-base simulator program. The tunnel display with a superimposed predictor symbol is shown to outperform conventional-type displays in its abilities to follow a curved trajectory in the presence of gust disturbances, to enter the trajectory from an unknown position outside this trajectory, as well as to monitor automatic approaches. The feasibility of the tunnel display for operation in actual flight has been demonstrated in an exploratory flight test.

Grunwald, A. J.↗
NASA NTRS1984

Predictability of the Earth's polar motion

A comprehensive, experimental study of the predictability of the polar motion using a homogeneous BIH (Bureau International de l'Heure) data set is presented. Based on knowledge of the physics of the annual and the Chandler wobbles, the numerical model for the polar motion is constructed by allowing the wobble periods to vary. Using an optimum base length of 6 years for prediction, this floating-period model, equipped with a non-linear least-squares estimator, is found to yield polar motion predictions accurate from 0.012 to 0.024 inches depending on the prediction length up to one year, corresponding to a predictability of 91-83%. This represents a considerable improvement over the conventional fixed-period predictor, which does not respond to variations in the apparent wobble periods. The superiority of the floating-period predictor to other predictors based on critically different numerical models is also demonstrated.

Chao, B. F.↗
NASA NTRS1984

Tunnel display for four-dimensional fixed-wing aircraft approaches

The present evaluation of a computer-generated perspective tunnel display for four-dimensional fixed wing aircraft landing approaches gives attention to the development and performance assessment of superimposed predictor symbology. Simulator tests indicate that a complex perspective vehicle symbol yields a decrease in bank angle activity, by comparison to a flat predictor cross, while yielding larger lateral and vertical deviations in most cases. The perspective vehicle symbol motions are successful in forward velocity control without affecting path-following performance. The perspective vehicle symbol's advantage over the flat predictor cross is nevertheless marginal. While the tunnel display used yields satisfactory response in the lateral control axis, the vertical axis lacks sensitivity to vertical path angle variations.

Grunwald, A. J.↗
NASA NTRS1985

Predictability of the earth's polar motion

The results of a numerical experiment on the predictability of terrestrial polar motion using a Bureau International de l'Heure data set from 1967-83 are presented. A floating point predictor was defined by decomposing polar motion into secular motion and annual and Chandler wobbles. The secular term was linear and the others periodic, the former due to atmospheric mass transport and the latter to Eulerian nutation. A least squares estimator was employed with the data base to obtain constants for the model, which is given the name 'floating-point'. A fixed-period predictor was also devised and, in comparison with the floating point predictor in 6 yr estimates of the annual wobble period, failed after a given length of time. It is suggested that the failure is due to atmospheric motions.

Fong, B.↗