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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-E-CAMPUS-I-03: Dosimetric Comparison of the Hypoxia Agent Iodoazomycin Arabinoside (IAZA) Labeled with the Radioisotopes I-123, I-131 and I-124

Purpose: To compare the radiation dose to normal organs from the radio-iodinated, hypoxia-binding radiosensitizer iodoazomycin arabinoside (IAZA) for three different isotopes of iodine. Methods: Dosimety studies with normal volunteers had been carried out with [{sup 123}I]IAZA, a drug binding selectively to hypoxic sites. Two other isotopes of iodine, {sup 131}I and {sup 124}I, offer the opportunity to use IAZA as an agent for radioisotope therapy and as an imaging tracer for Positron Emission Tomography. Radioisotope dosimetry for {sup 131}I and {sup 124}I was performed by first deriving from the [{sup 123}I]IAZA studies biological uptake and excretion data. The cumulated activities for {sup 131}I or {sup 124}I where obtained by including their half-lives when integrating the biological data and then extrapolating to infinite time points considering a) physical decay only or b) physical and biological excretion. Doses were calculated using the Medical Internal Radiation Dose (MIRD) schema (OLINDA1.1 code, Vanderbilt 2007). Results: Compared to {sup 123}I, organ doses were elevated on average by a factor 6 and 9 for {sup 131}I and {sup 124}I, respectively, if both physical decay and biological excretion were modeled. If only physical decay is considered, doses increase by a factor 18 ({sup 131}I) and 19 ({sup 124}I). Highest organ doses were observed in intestinal walls, urinary bladder and thyroid. Effective doses increased by a factor 11 and 14 for {sup 131}I and {sup 124}I, respectively, if biological and physical decay are present. Purely physical decay yields a 23-fold increase over {sup 123}I for both, {sup 131}I and {sup 124}I. Conclusion: Owing to the significant dose increase, caused by their longer half life and the approximately 10 times larger electronic dose deposited in tissue per nuclear decay, normal tissue doses of IAZA labeled with {sup 131}I and {sup 124}I need to be carefully considered when designing imaging and therapy protocols for clinical trials. Effective blocking of iodine uptake in the thyroid is essential. Alberta Innovates - Health Solutions (AIHS) and Canadian Institutes of Health Research (CIHR)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

MO-F-CAMPUS-I-05: Radiation Dosimetry of 99mTc-IDA-D-[c(RGDfK)]2, a SPECT Agent for Angiogenesis Imaging

Purpose: Tc-99m labeled IDA-D-[c(RGDfK){sub 2} ( {sup 99m}Tc-RGD) is a recently developed radiotracer for gamma camera or single photon emission computed tomography (SPECT) imaging and promising agent for the visualization of angiogenesis. In this study, we investigated the internal radiation dosimetry of {sup 99m}Tc-RGD in humans. Methods: Six normal controls (F:M=4:2; 68.3±3.2 years; 56.5±10.7 kg) were participated in this study. Simultaneous anterior and posterior scans of whole-body were performed using dual head gamma camera system. Before the emission scan, transmission scan was performed just before injection of {sup 99m}Tc-RGD using Co-57 flood source. After an intravenous injection of 388.7±29.3 MBq of {sup 99m}Tc-RGD, six serial emission scans were performed at 0, 1, 2, 4, 8 and 24 hours post-injection. The anterior and posterior images were geometrically averaged and attenuation correction was applied using transmission scan image. Regions of interest (ROIs) were drawn on liver, gallbladder, kidneys, urinary bladder, spleen, brain, and large intestine. Time activity curves were obtained from serial emission scan and ROIs. The number of disintegrations per unit activity administered (residence time) were calculated from the area under the curve of time activity curves and injected dose of each patient. Finally, the radiation dose for each organ and effective doses were obtained using OLINDA/EXM 1.1 software and residence time. Results: High radiation doses were reported on renal and biliary excretion tracks such as urinary bladder wall, upper large intestine, kidneys, liver and gallbladder wall and their doses were 19.15±6.84, 19.28±4.78, 15.67±0.90, 9.13±1.71 and 9.09±2.03 µGy/MBq, respectively. The effective dose and effective dose equivalent were 5.08±0.53 and 7.11±0.58 µSv/MBq, respectively. Conclusion: We evaluated the radiation dose of 99mTc-RGD, which has an acceptable effective radiation dose compare to the other Tc-99m labeled radio-tracers.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-D-210-04: Radiation-Induced Polymerization of Ultrasound Contrast Agents in View of Non-Invasive Dosimetry in External Beam Radiation Therapy

Purpose: Ultrasound contrast agents (UCA’s) based on gas-filled microbubbles encapsulated by an amphiphilic shell are well established as safe and effective echo-enhancers in diagnostic imaging. In view of an alternative application of UCA’s, we investigated the use of targeted microbubbles as radiation sensors for external beam radiation therapy. As radiation induces permanent changes in the microbubble’s physico-chemical properties, a robust measure of these changes can provide a direct or indirect estimate of the applied radiation dose. For instance, by analyzing the ultrasonic dispersion characteristics of microbubble distributions before and after radiation treatment, an estimate of the radiation dose at the location of the irradiated volume can be made. To increase the radiation sensitivity of microbubbles, polymerizable diacetylene molecules can be incorporated into the shell. This study focuses on characterizing the acoustic response and quantifying the chemical modifications as a function of radiation dose. Methods: Lipid/diacetylene microbubbles were irradiated with a 6 MV photon beam using dose levels in the range of 0–150 Gy. The acoustic response of the microbubbles was monitored by ultrasonic through-transmission measurements in the range of 500 kHz to 20 MHz, thereby providing the dispersion relations of the phase velocity, attenuation and nonlinear coefficient. In addition, the radiation-induced chemical modifications were quantified using UV-VIS spectroscopy. Results: UV-VIS spectroscopy measurements indicate that ionizing radiation induces the polymerization of diacetylenes incorporated in the microbubble shell. The polymer yield strongly depends on the shell composition and the radiation-dose. The acoustic response is inherently related to the visco-elastic properties of the shell and is strongly influenced by the shell composition and the physico-chemical changes in the environment. Conclusion: Diacetylene-containing microbubbles are polymerizable under influence of ionizing radiation and are a promising design concept within the development of a novel non-invasive in-vivo radiation dosimeter for external beam radiation therapy. This work was funded by the Research Foundation - Flanders (FWO)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Ice-nucleating agents in sea spray aerosol identified and quantified with a holistic multimodal freezing model

Sea spray aerosol (SSA) is a widely recognized important source of ice-nucleating particles (INPs) in the atmosphere. However, composition-specific identification, nucleation processes, and ice nucleation rates of SSA-INPs have not been well constrained. Microspectroscopic characterization of ambient and laboratory-generated SSA confirms that water-borne exudates from planktonic microorganisms composed of a mixture of proteinaceous and polysaccharidic compounds act as ice-nucleating agents (INAs). These data and data from previously published mesocosm and wave channel studies are subsequently used to further develop the stochastic freezing model (SFM) producing ice nucleation rate coefficients for SSA-INPs. The SFM simultaneously predicts immersion freezing and deposition and homogeneous ice nucleation by SSA particles under tropospheric conditions. Predicted INP concentrations agree with ambient and laboratory measurements. In addition, this holistic freezing model is independent of the source and exact composition of the SSA particles, making it well suited for implementation in cloud and climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The (R)evolution of Scientific Workflows in the Agentic AI Era: Towards Autonomous Science

Modern scientific discovery increasingly requires coordinating distributed facilities and heterogeneous resources, forcing researchers to act as manual workflow coordinators rather than scientists. Advances in AI leading to AI agents show exciting new opportunities that can accelerate scientific discovery by providing intelligence as a component in the ecosystem. However, it is unclear how this new capability would materialize and integrate in the real world. To address this, we propose a conceptual framework where workflows evolve along two dimensions which are intelligence (from static to intelligent) and composition (from single to swarm) to chart an evolutionary path from current workflow management systems to fully autonomous scientific laboratories. With these trajectories in mind, we present an architectural blueprint that can help the community take the next steps towards harnessing the opportunities in autonomous science with the potential for 100x discovery acceleration and transformational scientific workflows.

Shin, Woong [ORNL] (ORCID:0000000172077814)↗
DOE OSTI2022

An agent-based deployment decision-support system for electric vehicle services

METS-R ADDSEVS simulator is a high fidelity, parallel, agent-based evacuation simulator for multi-modal energy-optimal trip scheduling in real-time (METS-R) at transportation hubs. It consists of two modules. The first one is the traffic simulator module; the second one is the high-performance computing (HPC) module. More details can be found at https://umnilab.github.io/METS-R_doc/.

Lei, Zengxiang↗
DOE OSTI2024

Bayesian calibration of stochastic agent based model via random forest

SAND2024-11403O The Bayesian Calibration of Stochastic Agent-based Model via Random Forest is a code that was developed in concurrence with an article by the same name that was written for a journal. The code reproduces simulation results and plots from the article. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗
DOE OSTI2026

LeWRON: Learning ElectroWeak phase tRansitiON with agentic architecture

An agent to analyze electroweak phase transition. LeWRON turns a BSM model description or a reproduction target into a structured run: symbolic setup, effective-potential artifacts, finite-temperature machinery, generated model code, a scientific report, and an interactive exploration session. It keeps both machine-readable artifacts and human-readable notes, so a run can be resumed, audited, revised, and shared.

Wang, Isaac [Fermi National Accelerator Laboratory↗
DOE OSTI2026

Reverse Logistics Ev Battery Recycling Agent Base Model

This represents the initial regional tier of the electric vehicle (EV) battery recycling agent base model. Through this model, we can ascertain the number of EV purchases at both the state and regional levels. We employ census data to develop a diverse household profile to inform decisions regarding the acquisition of new or used EVs. The number of EV purchases at the state level will affect the future demand for recycling, reuse, and repurposing of end-of-life EV batteries. Additionally, tax credits, EV rebate programs, and the financial capacity of households will influence the number of EV purchases, thereby further impacting the demand for EV battery recycling.

Alam, Lamia [Idaho National Laboratory (INL), Idah↗
DOE OSTI2018

Determinants of the efficacy of HIV latency-reversing agents and implications for drug and treatment design

HIV eradication studies have focused on developing latency-reversing agents (LRAs). However, it is not understood how the rate of latent reservoir reduction is affected by different steps in the process of latency reversal. Furthermore, as current LRAs are host-directed, LRA treatment is likely to be intermittent to avoid host toxicities. Few careful studies of the serial effects of pulsatile LRA treatment have yet been done. This lack of clarity makes it difficult to evaluate the efficacy of candidate LRAs or predict long-term treatment outcomes. Here, we constructed a mathematical model that describes the dynamics of latently infected cells under LRA treatment. Model analysis showed that, in addition to increasing the immune recognition and clearance of infected cells, the duration of HIV antigen expression (i.e., the period of vulnerability) plays an important role in determining the efficacy of LRAs, especially if effective clearance is achieved. Patients may benefit from pulsatile LRA exposures compared with continuous LRA exposures if the period of vulnerability is long and the clearance rate is high, both in the presence and absence of an LRA. Overall, the model framework serves as a useful tool to evaluate the efficacy and the rational design of LRAs and combination strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Modeling and Calibration of Supplier Selection Problem in Freight Agent-Based Simulations

Freight transportation modeling often struggles with data limitations, especially in accurately representing complex supplier selection processes and their impact on network flows. This research addresses this critical gap by developing a large-scale, calibrated agent-based model for supplier selection, complemented by a probabilistic heuristic for international shipments. Our approach integrates trade relationships between industry sectors, transportation costs, and a supplier-rating model adapted from existing literature. The model’s core objective is to minimize the discrepancy between modeled and observed commodity flows while ensuring a close match to regional shipping distance distributions. Implemented and tested across four major U.S. metropolitan areas—Atlanta, Chicago, Dallas–Fort Worth, and Los Angeles—the model demonstrates high fidelity in replicating observed freight patterns. Key findings reveal consistent alignment with national shipping distance trends and highlight significant spatial variations in commodity trade assignments and demand across the study regions. This behaviorally informed and transport-sensitive framework is designed to approximate real-world decision making, providing a robust tool for policymakers and planners to evaluate targeted interventions, assess infrastructure investments, and enhance supply chain resilience in the face of disruptions.

Ismael, Abdelrahman (ORCID:0000000303712110)↗
DOE OSTI2015

Targeted amplification for enhanced detection of biothreat agents by next-generation sequencing

Background: Historically, identification of causal agents of disease has relied heavily on the ability to culture the organism in the laboratory and/or the use of pathogen-specific antibodies or sequence-based probes. However, these methods can be limiting: Even highly sensitive PCR-based assays must be continually updated due to signature degradation as new target strains and near neighbors are sequenced. Thus, there has been a need for assays that do not suffer as greatly from these limitations and/or biases. Recent advances in library preparation technologies for Next-Generation Sequencing (NGS) are focusing on the use of targeted amplification and targeted enrichment/ capture to ensure that the most highly discriminating regions of the genomes of known targets (organism-unique regions and/or regions containing functionally important genes or phylogenetically-discriminating SNPs) will be sequenced, regardless of the complex sample background. Results: In the present study, we have assessed the feasibility of targeted sequence enhancement via amplification to facilitate detection of a bacterial pathogen present in low copy numbers in a background of human genomic material. Our results indicate that the targeted amplification of signature regions can effectively identify pathogen genomic material present in as little as 10 copies per ml in a complex sample. Importantly, the correct species and strain calls could be made in amplified samples, while this was not possible in unamplified samples. Conclusions: The results presented here demonstrate the efficacy of a targeted amplification approach to biothreat detection, using multiple highly-discriminative amplicons per biothreat organism that provide redundancy in case of variation in some primer regions. Importantly, strain level discrimination was possible at levels of 10 genome equivalents. Similar results could be obtained through use of panels focused on the identification of amplicons targeted for specific genes or SNPs instead of, or in addition to, those targeted for specific organisms (ongoing gene-targeting work to be reported later). Note that without some form of targeted enhancement, the enormous background present in complex clinical and environmental samples makes it highly unlikely that sufficient coverage of key pathogen(s) present in the sample will be achieved with current NGS technology to guarantee that the most highly discriminating regions will be sequenced.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Surrogate modeling of Cellular-Potts agent-based models as a segmentation task using the U-Net neural network architecture

The Cellular-Potts model is a powerful and ubiquitous framework for developing computational models for simulating complex multicellular biological systems. Cellular-Potts models (CPMs) are often computationally expensive due to the explicit modeling of interactions among large numbers of individual model agents and diffusive fields described by partial differential equations (PDEs). In this work, we develop a convolutional neural network (CNN) surrogate model using a U-Net architecture that accounts for periodic boundary conditions. We use this model to accelerate the evaluation of a mechanistic CPM previously used to investigate in vitro vasculogenesis. The surrogate model was trained to predict 100 computational steps ahead (Monte-Carlo steps, MCS), accelerating simulation evaluations by a factor of 562 times compared to single-core CPM code execution on CPU. Over short timescales of up to 3 recursive evaluations, or 300 MCS, our model captures the emergent behaviors demonstrated by the original Cellular-Potts model such as vessel sprouting, extension and anastomosis, and contraction of vascular lacunae. This approach demonstrates the potential for deep learning to serve as a step toward efficient surrogate models for CPM simulations, enabling faster evaluation of computationally expensive CPM simulations of biological processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Agent-based model forecasts aging of the population of people who inject drugs in metropolitan Chicago and changing prevalence of hepatitis C infections

People who inject drugs (PWID) are at high risk for blood-borne pathogens transmitted during the sharing of contaminated injection equipment, particularly hepatitis C virus (HCV). HCV prevalence is influenced by a complex interplay of drug-use behaviors, social networks, and geography, as well as the availability of interventions, such as needle exchange programs. To adequately address this complexity in HCV epidemic forecasting, we have developed a computational model, the Agent-based Pathogen Kinetics model (APK). APK simulates the PWID population in metropolitan Chicago, including the social interactions that result in HCV infection. We used multiple empirical data sources on Chicago PWID to build a spatial distribution of an in silico PWID population and modeled networks among the PWID by considering the geography of the city and its suburbs. APK was validated against 2012 empirical data (the latest available) and shown to agree with network and epidemiological surveys to within 1%. For the period 2010–2020, APK forecasts a decline in HCV prevalence of 0.8% per year from 44(±2)% to 36(±5)%, although some sub-populations would continue to have relatively high prevalence, including Non-Hispanic Blacks, 48(±5)%. The rate of decline will be lowest in Non-Hispanic Whites and we find, in a reversal of historical trends, that incidence among non-Hispanic Whites would exceed incidence among Non-Hispanic Blacks (0.66 per 100 per years vs 0.17 per 100 person years). APK also forecasts an increase in PWID mean age from 35(±1) to 40(±2) with a corresponding increase from 59(±2)% to 80(±6)% in the proportion of the population >30 years old. Our research highlight the importance of analyzing sub-populations in disease predictions, the utility of computer simulation for analyzing demographic and health trends among PWID and serve as a tool for guiding intervention and prevention strategies in Chicago, and other major cities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

A TaqMan-based multiplex qPCR assay and DNA extraction method for phylotype IIB sequevars 1&2 (select agent) strains of Ralstonia solanacearum

Ralstonia solanacearum race 3 biovar 2 strains belonging to phylotype IIB, sequevars 1 and 2 (IIB-1&2) cause brown rot of potato in temperate climates, and are quarantined pathogens in Canada and Europe. Since these strains are not established in the U.S. and because of their potential risk to the potato industry, the U.S. government has listed them as select agents. Cultivated geraniums are also a host and have the potential to spread the pathogen through trade, and its extracts strongly inhibits DNA-based detection methods. We designed four primer and probe sets for an improved qPCR method that targets stable regions of DNA. RsSA1 and RsSA2 recognize IIB-1&2 strains, RsII recognizes the current phylotype II (the newly proposed R. solanacearum species) strains (and a non-plant associated R. mannitolilytica ), and Cox1 recognizes eight plant species including major hosts of R. solanacearum such as potato, tomato and cultivated geranium as an internal plant control. We multiplexed the RsSA2 with the RsII and Cox1 sets to provide two layers of detection of a positive IIB-1&2 sample, and to validate plant extracts and qPCR reactions. The TaqMan-based uniplex and multiplex qPCR assays correctly identified 34 IIB-1&2 and 52 phylotype II strains out of 90 R. solanacearum species complex strains. Additionally, the multiplex qPCR assay was validated successfully using 169 artificially inoculated symptomatic and asymptomatic plant samples from multiple plant hosts including geranium. Moreover, we developed an extraction buffer that allowed for a quick and easy DNA extraction from infected plants including geranium for detection of R. solanacearum by qPCR. Our multiplex qPCR assay, especially when coupled with the quick extraction buffer method, allows for quick, easy and reliable detection and differentiation of the IIB-1&2 strains of R. solanacearum .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

‘Candidatus Liberibacter asiaticus’, causal agent of citrus Huanglongbing, is reduced by treatment with Brassinosteroids

Huanglongbing (HLB) constitutes the most destructive disease of citrus worldwide, yet no established efficient management measures exist for it. Brassinosteroids, a family of plant steroidal compounds, are essential for plant growth, development and stress tolerance. As a possible control strategy for HLB, epibrassinolide was applied to as a foliar spray to citrus plants infected with the causal agent of HLB, ‘Candidatus Liberibacter asiaticus’. The bacterial titers were reduced after treatment with epibrassinolide under both greenhouse and field conditions but were stronger in the greenhouse. Known defense genes were induced in leaves by epibrassinolide. With the SuperSAGE technology combined with next generation sequencing, induction of genes known to be associated with defense response to bacteria and hormone transduction pathways were identified. Lastly, the results demonstrate that epibrassinolide may provide a useful tool for the management of HLB.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

An Observation-Driven Agent-Based Modeling and Analysis Framework for C. elegans Embryogenesis

With cutting-edge live microscopy and image analysis, biologists can now systematically track individual cells in complex tissues and quantify cellular behavior over extended time windows. Computational approaches that utilize the systematic and quantitative data are needed to understand how cells interact in vivo to give rise to the different cell types and 3D morphology of tissues. An agent-based, minimum descriptive modeling and analysis framework is presented in this paper to study C. elegans embryogenesis. The framework is designed to incorporate the large amounts of experimental observations on cellular behavior and reserve data structures/interfaces that allow regulatory mechanisms to be added as more insights are gained. Observed cellular behaviors are organized into lineage identity, timing and direction of cell division, and path of cell movement. The framework also includes global parameters such as the eggshell and a clock. Division and movement behaviors are driven by statistical models of the observations. Data structures/interfaces are reserved for gene list, cell-cell interaction, cell fate and landscape, and other global parameters until the descriptive model is replaced by a regulatory mechanism. This approach provides a framework to handle the ongoing experiments of single-cell analysis of complex tissues where mechanistic insights lag data collection and need to be validated on complex observations.

Science & Technology - Other Topics↗