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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Light in Ecological Settings: Entrainment, Circadian Disruption, and Interventions

Light is the predominant signal for the human circadian clock to synchronize to the solar 24-h day through an active process called entrainment. Modern light profiles are characterized by exposure to both natural daylight and artificial lighting. A mismatch between these self-selected light profiles and the solar day-night alternation can disrupt the circadian system, resulting in acute and chronic effects for health and safety. In this chapter, we describe (i) how entrainment works in the real world, illustrating the major role of light for this process; (ii) ways in which the circadian system can be disrupted by (external) factors such as irregular sleep, shift work, daylight saving time, and longitudinal position in a time zone; and (iii) how field studies have used light interventions to reduce direct and indirect effects of circadian disruption in ecological settings.

light interventions↗
DOE OSTI2022

Optimizing equity in energy policy interventions: A quantitative decision-support framework for energy justice

This paper presents a quantitative framework to support policy decision-making around equitable energy interventions. By combining sociodemographic and techno-economic models in the energy space, we propose a linear programming model to calculate the optimal portfolio of energy investments that explicitly minimizes the energy burden of a given population of energy insecure households. The model is formulated as a multi-objective optimization suitable to support the decisions on weatherization and deployment of distributed energy resources. We illustrate our methodology with a case study involving a population of 14,043 energy insecure households in Wayne County, Detroit, United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

The impacts of COVID-19 on clean energy labor markets: Evidence from multifaceted analysis of public health interventions and COVID-health factors

COVID-19 pandemic has affected clean energy labor market. Using real-time job vacancy data, this study analyzes the impacts of the pandemic on the U.S. clean energy labor market in 2020, including biomass, energy efficiency (EE), electric vehicle (EV), power/microgrid, solar, and wind industries. This study identifies how COVID-health factors and public health interventions influence clean energy job availability during the early COVID pandemic. Overall, California had the most energy jobs and experienced a significant decrease in April 2020. EV and solar had the highest percentages of job vacancies during the pandemic in general. Still, lockdowns had the most severe influence on EE and wind jobs. Stay-at-home orders negatively affected clean energy job vacancies in biomass, EV, power/microgrid, and wind. Social-gathering restrictions, however, did not have much influence. Increased COVID tests at the state level had the strongest and most positive influence on clean energy job postings, indicating the importance of a state's ability to manage public health infrastructure or crisis issues. COVID hospitalizations negatively influenced the job vacancies in biomass and wind but did not affect the other four sectors; conversely, as COVID death numbers increased, the number of jobs in biomass, EV, power grid, solar, and wind decreased, but not in EE jobs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Lipid and lipoprotein metabolism in microglia: Alzheimer’s disease mechanisms and interventions

Alzheimer's disease (AD) presents a significant challenge owing to its widespread prevalence and complex neuropathogenesis, affecting millions worldwide. Current therapeutic strategies that predominantly target amyloid-beta accumulation are insufficient, particularly for ApoE4 carriers. Alterations in lipid composition are well documented in AD, characterized by reductions in phospholipids and sulfatides, along with increases in cholesterol, cholesteryl esters, and triglycerides (TGs). Microglia, the brain's resident immune cells, link dysfunctional lipid processing to AD neuropathogenesis. For example, genetic studies have pointed to microglial lipid and lipoprotein processing gene variants as some of the strongest risk factors for AD. In addition, microglial dysfunction, characterized by lipid droplet accumulation, increased cholesterol and TG levels, and altered lipid transport, may exacerbate the pathological hallmarks of AD, such as amyloid-beta and tau accumulation. Conversely, emerging studies have shown that strategies aimed at inhibiting lipid droplet accumulation in microglia, reducing TG synthesis, and promoting the activity of lipoprotein receptors expressed by microglia can improve cell functions and markers of AD pathology. This review dissects the interplay between microglial lipid metabolism and AD, highlighting the significance of lipid transport and trafficking within the CNS. Given the intrinsic link between microglial metabolism and AD progression, emerging and potential therapeutic strategies aimed at restoring lipid handling and improving microglial function are explored. This review provides a comprehensive examination of the emerging literature, detailing the current state of knowledge on microglial lipid metabolism, its genetic underpinnings, and the potential for novel interventions targeting these mechanisms to ameliorate AD pathology.

Alzheimer's disease↗
DOE OSTI2023

Explainability and human intervention in autonomous scanning probe microscopy

The broad adoption of machine learning (ML)-based autonomous experiments (AEs) in material characterization and synthesis requires strategies development for understanding and intervention in the experimental workflow. Here, we introduce and realize a post-experimental analysis strategy for deep kernel learning-based autonomous scanning probe microscopy. This approach yields real-time and post-experimental indicators for the progression of an active learning process interacting with an experimental system. We further illustrate how this approach can be applied to human-in-the-loop AEs, where human operators make high-level decisions at high latencies setting the policies for AEs, and the ML algorithm performs low-level, fast decisions. The proposed approach is universal and can be extended to other techniques and applications such as combinatorial library analysis.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Investigation of the Sensitivity of Tropical Cyclogenesis to Aerosol Intervention

Abstract As risks from tropical cyclones (TCs) are fueled by climate change escalation, there is an urgent need for transformational solutions to complement traditional approaches. Seeding TCs using aerosols can be a promising method to reduce cyclone intensity, supported by theoretical understanding of the microphysical effects of aerosols on TC clouds. The ideal time to intervene effectively in TCs is likely during their initial stage, before TC wind speeds reach their peak. However, studies exploring potential aerosol effects on TC formation remain scarce. This study investigates how a TC embryo responds to the addition of aerosols of varying sizes using the Weather Research & Forecasting (WRF) model coupled with a spectral‐bin microphysics model. We found that aerosols of different sizes and concentrations distinctively affect the pre‐TC vortex's microstructure and dynamics. Fine and ultrafine aerosols enhance the latent heat of condensation, freezing, deposition, and riming, initially intensifying the vortex. However, this results in enhancement of the cold pool, thereby reducing inflow and surface fluxes, subsequently weakening the vortex. Coarse aerosols produce the opposite effect to that of fine and ultrafine aerosols. Coarse aerosols lead to a slower initial acceleration owing to enhanced warm rain. However, the resulting weaker cold pool is insufficient to effectively reduce the strength of the vortex at the later stage. This study provides critical insights into how aerosols of varying sizes and concentrations modulate the energy cascade and impact the evolution of a TC embryo, laying the groundwork for further research on TC risk management through aerosol intervention.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Real time monitoring of COVID-19 intervention effectiveness through contact tracing data

Communities worldwide have used vaccines and facemasks to mitigate the COVID-19 pandemic. When an individual opts to vaccinate or wear a mask, they may lower their own risk of becoming infected as well as the risk that they pose to others while infected. The first benefit–reducing susceptibility–has been established across multiple studies, while the second–reducing infectivity–is less well understood. Using a new statistical method, we estimate the efficacy of vaccines and facemasks at reducing both types of risks from contact tracing data collected in an urban setting. We find that vaccination reduced the risk of onward transmission by 40.7% [95% CI 25.8–53.2%] during the Delta wave and 31.0% [95% CI 19.4–40.9%] during the Omicron wave and that mask wearing reduced the risk of infection by 64.2% [95% CI 5.8–77.3%] during the Omicron wave. By harnessing commonly-collected contact tracing data, the approach can broadly provide timely and actionable estimates of intervention efficacy against a rapidly evolving pathogen.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Laser speckle contrast imaging of blood microcirculation in pancreatic tissues during laparoscopic interventions

Laser speckle contrast imaging of the microcirculatory bed of the pancreas is performed, which allows its condition to be assessed and thereby is an additional valuable tool for making a diagnostic decision and dynamically monitoring the effectiveness of the treatment for pathology of the abdominal organs. Laparoscopic operations on the pancreas are low-traumatic and in most cases avoid open surgical interventions. For the first time an experimental system for recording speckle images, combined with a commercially available five-millimetre rigid laparoscope, is presented. The sensitivity of the system to the fluid motion in a capillary at different velocities is determined, and the possibility of finding areas of blood microcirculation disturbance in modelling pancreatic ischemia in an experiment on laboratory animals is revealed. The laparoscope illumination channel is verified by comparison with speckle dynamics under external illumination of the studied object. (paper)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Cryo-EM analyses of KIT and oncogenic mutants reveal structural oncogenic plasticity and a target for therapeutic intervention

The receptor tyrosine kinase KIT and its ligand stem cell factor (SCF) are required for the development of hematopoietic stem cells, germ cells, and other cells. A variety of human cancers, such as acute myeloid leukemia, gastrointestinal stromal tumor, and mast cell leukemia, are driven by somatic gain-of-function KIT mutations. Here, we report cryo electron microscopy (cryo-EM) structural analyses of full-length wild-type and two oncogenic KIT mutants, which show that the overall symmetric arrangement of the extracellular domain of ligand-occupied KIT dimers contains asymmetric D5 homotypic contacts juxtaposing the plasma membrane. Mutational analysis of KIT reveals in D5 region an “Achilles heel” for therapeutic intervention. A ligand-sensitized oncogenic KIT mutant exhibits a more comprehensive and stable D5 asymmetric conformation. A constitutively active ligand-independent oncogenic KIT mutant adopts a V-shaped conformation solely held by D5-mediated contacts. Binding of SCF to this mutant fully restores the conformation of wild-type KIT dimers, including the formation of salt bridges responsible for D4 homotypic contacts and other hallmarks of SCF-induced KIT dimerization. These experiments reveal an unexpected structural plasticity of oncogenic KIT mutants and a therapeutic target in D5.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Myosin in autoinhibited off state(s), stabilized by mavacamten, can be recruited in response to inotropic interventions

Mavacamten is a FDA-approved small-molecule therapeutic designed to regulate cardiac function at the sarcomere level by selectively but reversibly inhibiting the enzymatic activity of myosin. It shifts myosin toward ordered off states close to the thick filament backbone. It remains elusive whether these myosin heads in the off state(s) can be recruited in response to physiological stimuli when required to boost cardiac output. We show that cardiac myosins stabilized in these off state(s) by mavacamten are recruitable by 1) Ca 2+ , 2) increased chronotropy [heart rate (HR)], 3) stretch, and 4) β-adrenergic (β-AR) stimulation, all known physiological inotropic interventions. At the molecular level, we show that Ca 2+ increases myosin ATPase activity by shifting mavacamten-stabilized myosin heads from the inactive super-relaxed state to the active disordered relaxed state. At the myofilament level, both Ca 2+ and passive lengthening can shift mavacamten-ordered off myosin heads from positions close to the thick filament backbone to disordered on states closer to the thin filaments. In isolated rat cardiomyocytes, increased stimulation rates enhanced shortening fraction in mavacamten-treated cells. This observation was confirmed in vivo in telemetered rats, where left-ventricular dP/dt max , an index of inotropy, increased with HR in mavacamten-treated animals. Finally, we show that β-AR stimulation in vivo increases left-ventricular function and stroke volume in the setting of mavacamten. Our data demonstrate that the mavacamten-promoted off states of myosin in the thick filament are at least partially activable, thus preserving cardiac reserve mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The spread of technological innovations: effects of psychology, culture and policy interventions

Technological innovations drive the evolution of human societies. The success of innovations depends not only on their actual benefits but also on how potential adopters perceive them and how their beliefs are affected by their social and cultural environment. To deepen our understanding of socio-psychological processes affecting the new technology spread, we model the joint dynamics of three interlinked processes: individual learning and mastering the new technology, changes in individual attitudes towards it, and changes in individual adoption decisions. We assume that the new technology can potentially lead to a higher benefit but achieving it requires learning. We posit that individual decision-making process as well as their attitudes are affected by cognitive dissonance and conformity with peers and an external authority. Individuals vary in different psychological characteristics and in their attitudes. We investigate both transient dynamics and long-term equilibria observed in our model. We show that early adopters are usually individuals who are characterized by low cognitive dissonance and low conformity with peers but are sensitive to the effort of an external authority promoting the innovation. We examine the effectiveness of five different intervention strategies aiming to promote the diffusion of a new technology: training individuals, providing subsidies for early adopters, increasing the visibility of peer actions, simplifying the exchange of opinions between people, and increasing the effort of an external authority. We also discuss the effects of culture on the spread of innovations. Finally, we demonstrate that neglecting the cognitive forces and the dynamic nature of individual attitudes can lead to wrong conclusions about adoption of innovations. Our results can be useful in developing more efficient policies aiming to promote the spread of new technologies in different societies, cultures and countries.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Compensatory reserve detects subclinical shock with more expeditious prediction for need of life‐saving interventions compared to systolic blood pressure and blood lactate

Abstract Introduction We conducted a prospective observational study on 205 trauma patients at a level I trauma facility to test the hypothesis that a compensatory reserve measurement (CRM) would identify higher risk for progression to shock and/or need a life‐saving interventions (LSIs) earlier than systolic blood pressure (SBP) and blood lactate (LAC). Methods A composite outcome metric included blood transfusion, procedural LSI, and mortality. Discrete measures assessed as abnormal (ab) were SBP <90 mmHg, CRM <60%, and LAC >2.0. A graded categorization of shock was defined as: no shock (normal [n] SBP [n‐SBP], n‐CRM, n‐LAC); sub‐clinical shock (ab‐CRM, n‐SBP, n‐LAC); occult shock (n‐SBP, ab‐CRM, ab‐LAC); or overt shock (ab‐SBP, ab‐CRM, ab‐LAC). Results Three patients displayed overt shock, 53 displayed sub‐clinical shock, and 149 displayed no shock. After incorporating lactate into the analysis, 86 patients demonstrated no shock, 25 were classified as sub‐clinical shock, 91 were classified as occult shock, and 3 were characterized as overt shock. Each shock subcategory revealed a graded increase requiring LSI and transfusion. Initial CRM was associated with progression to shock (odds ratio = 0.97; p < .001) at an earlier time than SBP or LAC. Conclusions Initial CRM uncovers a clinically relevant subset of patients who are not detected by SBP and LAC. Our results suggest CRM could be used to more expeditiously identify injured patients likely to deteriorate to shock, with requirements for blood transfusion or procedural LSI.

Convertino, Victor A.↗
DOE OSTI2023

Quantification of early nonpharmaceutical interventions aimed at slowing transmission of Coronavirus Disease 2019 in the Navajo Nation and surrounding states (Arizona, Colorado, New Mexico, and Utah)

During an early period of the Coronavirus Disease 2019 (COVID-19) pandemic, the Navajo Nation, much like New York City, experienced a relatively high rate of disease transmission. Yet, between January and October 2020, it experienced only a single period of growth in new COVID-19 cases, which ended when cases peaked in May 2020. The daily number of new cases slowly decayed in the summer of 2020 until late September 2020. In contrast, the surrounding states of Arizona, Colorado, New Mexico, and Utah all experienced at least two periods of growth in the same time frame, with second surges beginning in late May to early June. Here, we investigated these differences in disease transmission dynamics with the objective of quantifying the contributions of non-pharmaceutical interventions (NPIs) (e.g., behaviors that limit disease transmission). We considered a compartmental model accounting for distinct periods of NPIs to analyze the epidemic in each of the five regions. We used Bayesian inference to estimate region-specific model parameters from regional surveillance data (daily reports of new COVID-19 cases) and to quantify uncertainty in parameter estimates and model predictions. Our results suggest that NPIs in the Navajo Nation were sustained over the period of interest, whereas in the surrounding states, NPIs were relaxed, which allowed for subsequent surges in cases. Our region-specific model parameterizations allow us to quantify the impacts of NPIs on disease incidence in the regions of interest.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

People who inject drugs in metropolitan Chicago: A meta-analysis of data from 1997-2017 to inform interventions and computational modeling toward hepatitis C microelimination

Progress toward hepatitis C virus (HCV) elimination in the United States is not on track to meet targets set by the World Health Organization, as the opioid crisis continues to drive both injection drug use and increasing HCV incidence. A pragmatic approach to achieving this is using a microelimination approach of focusing on high-risk populations such as people who inject drugs (PWID). Computational models are useful in understanding the complex interplay of individual, social, and structural level factors that might alter HCV incidence, prevalence, transmission, and treatment uptake to achieve HCV microelimination. However, these models need to be informed with realistic sociodemographic, risk behavior and network estimates on PWID. We conducted a meta-analysis of research studies spanning 20 years of research and interventions with PWID in metropolitan Chicago to produce parameters for a synthetic population for realistic computational models (e.g., agent-based models). We then fit an exponential random graph model (ERGM) using the network estimates from the meta-analysis in order to develop the network component of the synthetic population.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Model Exploration of an Information-Based Healthcare Intervention Using Parallelization and Active Learning

This paper describes the application of a large-scale active learning method to characterize the parameter space of a computational agent-based model developed to investigate the impact of CommunityRx, a clinical information-based health intervention that provides patients with personalized information about local community resources to meet basic and self-care needs. Additionally, the diffusion of information about community resources and their use is modeled via networked interactions and their subsequent effect on agents' use of community resources across an urban population. A random forest model is iteratively fitted to model evaluations to characterize the model parameter space with respect to observed empirical data. We demonstrate the feasibility of using high-performance computing and active learning model exploration techniques to characterize large parameter spaces; by partitioning the parameter space into potentially viable and non-viable regions, we rule out regions of space where simulation output is implausible to observed empirical data. We argue that such methods are necessary to enable model exploration in complex computational models that incorporate increasingly available micro-level behavior data. We provide public access to the model and high-performance computing experimentation code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Epigenetic drift underlies epigenetic clock signals, but displays distinct responses to lifespan interventions, development, and cellular dedifferentiation

Changes in DNA methylation with age are observed across the tree of life. The stereotypical nature of these changes can be modeled to produce epigenetic clocks capable of predicting chronological age with unprecedented accuracy. Despite the predictive ability of epigenetic clocks and their utility as biomarkers in clinical applications, the underlying processes that produce clock signals are not fully resolved, which limits their interpretability. Here, we develop a computational approach to spatially resolve the within read variability or “disorder” in DNA methylation patterns and test if age-associated changes in DNA methylation disorder underlie signals comprising epigenetic clocks. We find that epigenetic clock loci are enriched in regions that both accumulate and lose disorder with age, suggesting a link between DNA methylation disorder and epigenetic clocks. We then develop epigenetic clocks that are based on regional disorder of DNA methylation patterns and compare their performance to other epigenetic clocks by investigating the influences of development, lifespan interventions, and cellular dedifferentiation. We identify common responses as well as critical differences between canonical epigenetic clocks and those based on regional disorder, demonstrating a fundamental decoupling of epigenetic aging processes. Collectively, we identify key linkages between epigenetic disorder and epigenetic clocks and demonstrate the multifaceted nature of epigenetic aging in which stochastic processes occurring at non-random loci produce predictable outcomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Early Intervention Program Los Alamos National Laboratory [Slides]

Objectives of the Program: Identify employees with symptoms/discomfort and provide early intervention/rapid response before discomfort becomes an injury; Demonstrate to employees that the Laboratory cares about them using a personalized approach; Improve worker productivity and workplace satisfaction; Spread the word so that employees report discomfort early and rapid intervention can be executed to prevent injuries; facilitate procurement of necessary equipment as quickly as possible given risk of progression to injury.

99 GENERAL AND MISCELLANEOUS↗