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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Does the Presence of the Biological Control Agent, Hypena opulenta (Lepidoptera: Erebidae) on Swallow-Worts Deter Monarch Oviposition?

Abstract Invasive black and pale swallow-worts (Vincetoxicum nigrum (L.) Moench, and Vincetoxicum rossicum Kelopow), which are related to milkweeds, can act as ecological traps for monarch butterflies (Danaus plexippus L. (Lepidoptera: Nymphalidae)) as they lay eggs on them that fail to develop. A recently approved biological control agent against swallow-worts, Hypena opulenta Christoph, occupies the same feeding guild on swallow-worts as monarch larvae and could be perceived as a competitor to monarchs. We tested how the presence of this defoliating moth on swallow-worts may influence monarch host selection. In a two-year field experiment, we placed pale swallow-wort plants that were either infested with H. opulenta or noninfested as well as common milkweed (Asclepias syriaca L.), into monarch habitats to assess oviposition rates. In the laboratory, monarchs were either given a choice or not between milkweeds and black swallow-worts with or without H. opulenta. While monarchs strongly preferred common milkweed in the field, up to 25% of the eggs we observed were laid on pale swallow-wort, without preference for swallow-wort with (10.7%) or without (14.3%) H. opulenta. In laboratory choice and no-choice tests, monarchs did not lay any eggs on black swallow-wort, likely because of the long-term laboratory rearing on common milkweeds. Our results confirm that pale swallow-wort may act as an oviposition sink to monarchs in Michigan as well. Since the biological control program is still in its infancy, the nature of interactions between monarchs and H. opulenta may change as the biocontrol agent becomes more widespread.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Remarkably High Internal Transcribed Spacer Haplotype Diversity of the Fungal Select Agent Coniothyrium glycines Discovered Throughout Its Range in Sub-Saharan Africa

Red leaf blotch of soybean, caused by the fungus Coniothyrium glycines, is a foliar disease characterized by blotching, necrosis, and defoliation that has only been reported from Africa. The species is listed as a Select Agent by the Federal Select Agent Program due to its potentially devastating impacts to soybean production should it spread to the United States. Despite its potential import, very few isolates are available for study. Herein, we obtained 96 new C. glycines isolates from six soybean-producing countries throughout sub-Saharan Africa. Along with 12 previously collected ones, we sequenced each at the internal transcribed spacer (ITS) region. Between all isolates, we identified a total of 28 single-nucleotide polymorphisms and 23 haplotypes. One hypothesis to explain the tremendous diversity uncovered at the ITS—which is generally conserved within a species—is that our current species concept of C. glycines is too broad and that there may be multiple species that cause red leaf blotch. Zambia contained the highest haplotype diversity, a significant fraction of which remains unsampled. Most haplotypes were specific to a single country, except for two, which were found in Zambia and either neighboring Mozambique or Zimbabwe. This geographic specificity indicates that the ITS region may be useful for identifying source populations or routes of transmission should this pathogen spread beyond Africa. The observed geographic partitioning of this pathogen is likely the result of millions of years of replication on little-studied native hosts, given that soybean has only been cultivated in Africa since the early 1900s.

Plant Sciences↗
DOE OSTI2026

Agentic artificial intelligence for multistage physics experiments at a large-scale user facility particle accelerator

We present a language-model-driven agentic artificial intelligence (AI) system to autonomously execute multistage physics experiments on a production synchrotron light source. Implemented at the Advanced Light Source particle accelerator, the system translates natural language user prompts into structured execution plans that combine archive data retrieval, control-system channel resolution, automated script generation, controlled machine interaction, and analysis. In a representative machine physics task, we show that preparation time was reduced by 2 orders of magnitude relative to manual scripting even for a system expert, while operator-standard safety constraints were strictly upheld. Core architectural features, plan-first orchestration, bounded tool access, and dynamic capability selection, enable transparent, auditable execution with fully reproducible artifacts. These results establish a blueprint for the safe integration of agentic AI into accelerator experiments and demanding machine physics studies, as well as routine operations, with direct portability across accelerators worldwide and, more broadly, to other large-scale scientific infrastructures.

Accelerator/storage ring control systems↗
DOE OSTI2025

Virtual Agents-Based Attack-Resilient Distributed Control for Islanded AC Microgrid

Due to its dependence on a communication network, distributed secondary control of microgrids is susceptible to denial-of-service (DoS) attacks in channel shutdown mode, which may negatively impact the network connectivity and thus deteriorate the coordination and power sharing among distributed generators (DGs). Honeypot is a common method for cyber deception by introducing fake targets. However, in the context of microgrid, the misleading information spread by honeypots will also impact the system performance. This paper proposes an attack-resilient distributed control for AC microgrids utilizing virtual agents (VAs) to counteract both DoS edge and node attacks. The VAs are designed to not impact the system’s steady state during normal operation but to share information among neighboring real agents and serve as dummy targets for DoS attacks. The control with VAs is implemented by a primal-dual gradient based distributed algorithm to efficiently obtain a practical solution for voltage/frequency regulation and power sharing. The simulation results on a 4-DG test system and a modified IEEE 34-bus system show that 1) VAs do not impact the normal functionality of the test system, and 2) deploying VAs can enhance the resilience of the microgrid control against DoS edge and node attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Agent-Based Framework for Supporting Behind the Meter Transactive Power Electronic Systems

In this paper, the concept of a framework based on an agent-based interface for power stages in a power electronic system is presented. The presented concept or agent system is able to consider any number of different types of sources, types of converters, communication protocols, embedded decision making to support transactive, and hierarchy for large system integration. The concept is presented through several examples including the implementation on an actual physical system and demonstration of transactive type controls.

Starke, Michael↗
DOE OSTI2018

High performance Data Driven Agent-based Modeling Framework for Simulation of Commute Mode Choices in Metropolitan Area

Active transportation, human-powered transportation modes such as walking and bicycling, not only reduces the carbon footprint from the transportation sector but also promotes healthy living by offering opportunities for people to build physical activity into their daily routine. To encourage active transportation through urban planning and public campaigns, it is of significant importance to infer factors that substantially influence commuters in their transportation mode choice process. This necessitates a flexible and repeatable tool that can evaluate how a policy is perceived by individual commuters and convert their decisions into macro level understanding. This paper introduces one such effort that is specifically designed for studies of transportation mode choices in metropolitan areas. It provides results from a high-resolution data driven simulation based on high performance computing implementation of the agent-based model framework for home-to-work commute trips. The framework uses a graph-partition based technique that can leverage the interaction structure of agents within a geographic proximity and can boost the simulation execution time. Further, based on a flexible design, it can run ABM with different levels of computing resources-from multi core workstations to an HPC grid. The framework has been tested on the Titan Cray XK7 supercomputer of the Oak Ridge Leadership Computing Facility.

Park, Byung↗
DOE OSTI2021

Agent-Supervisor Coordination for Decentralized Event-Triggered Optimization

This letter proposes decentralized resource-aware coordination schemes for solving network optimization problems defined by objective functions that combine locally evaluable costs with network-wide coupling components. These methods are well suited for a group of supervised agents trying to solve an optimization problem under mild coordination requirements. Each agent has information on its local cost and coordinates with the network supervisor for information about the coupling term of the cost. The proposed approach is feedback-based and asynchronous by design, guarantees anytime feasibility, and ensures the asymptotic convergence of the network state to the desired optimizer. Numerical simulations on a power system example illustrate our results.

decentralized algorithms↗
DOE OSTI2019

Agent-Based System for Transactive Control of Smart Residential Neighborhoods

Buildings consume 74% of the total electricity produced in the United States. A significant portion of the building electric load includes heating ventilation and air-conditioning (HVAC) systems and water heating (WH) systems. Enabling flexibility in the operations can improve overall electric grid efficiency. This paper describes a multi-agent system for supporting integration, learning, optimization, and control of HVAC and WH in supporting a future smart grid. The architecture supports a transactive-based negotiation strategy between homeowners and a microgrid controller to adjust consumption behavior and reduce electricity costs. The framework is deployed in a neighborhood and preliminary testing is underway. The agent architecture design is discussed along with the preliminary optimization results from the demonstration site.

Starke, Michael↗
DOE OSTI2021

Transactive Electric Vehicle Agent: Design and Performance Evaluation

Transactive electric vehicle (TEV) agent enables the utilization of EVs’ flexible resources for the benefits of both utility and customer by active market participation. In this work, we propose a novel TEV agent optimization with a novel slider feature that models an individual customer’s willingness to participate in the transactive market. We characterize the customer comfort in EV’s context using a slider that provides flexibility to the customer to choose a trade-off between comfort and profit. Finally, the proposed optimization framework is used to investigate the comparative benefits of V2G technology compared to V1G.

day-ahead electricity market, electric vehicle, fl↗
DOE OSTI2023

Load Shedding for Voltage Regulation With Probabilistic Agent Compliance

With the increased observability and controllability of distribution systems, the share of behind-the-meter systems is trending upwards rapidly. As a consequence, the impact of human behaviors on system performance can no longer be ignored and should be reflected in the energy management system models. In this paper, we discuss the problem of distribution system voltage control by active power curtailment where the agent compliance of the load curtailment signal is probabilistic. We discuss the modeling of the optimal voltage control problem with probabilistic agent compliance as a chance-constrained optimization problem, its tractable safe approximation using convex restriction, and a scenario-based mixed-integer reformulation as well as the associated solution method based on augmented Lagrangian method. The numerical simulation on IEEE test system validates the effectiveness of the proposed approach in obtaining high-quality feasible load curtailment signal with low computational cost, which makes it a viable tool for real time decision making.

augmented Lagrangian method↗
DOE OSTI2023

Developing a Disaster-Ready Power Grid Agent Through Geophysically-Informed Fault Event Scenarios

Management of the nation’s power grid over the coming decades will need to factor multiple climate-driven threats to the power system that can be stressful or even detrimental to its operations. During disasters, grid operators suffer from cognitive overload where the electric grid is severely impacted by the weather, yet grid operators have limited awareness of these factors. Meanwhile, the electric grid is facing an explosion of data coming from a variety of sources which can enable the operator to evaluate the risks and develop mitigation strategies against hazardous events. In this work, we processed heterogeneous environmental and power grid data to learn and model grid behavior caused by extreme weather events. In this study, we focused on two weather-driven hazards, hurricanes and wildfires, which were analysed for the electric grid of Texas. We the used this data to train a Reinforcement Learning (RL) agent by analysing and predicting future behaviour of the grid during those hazard events. All these parts are incorporated in one framework to have a geophysically informed power simulators that can be used to train RL agents.

electic grid, reinforcement learning, climate adap↗
DOE OSTI2017

Agent-Centric Approach for Cybersecurity Decision-Support with Partial Observability

Generating automated cyber resilience policies for real-world settings is a challenging research problem that must account for uncertainties in system state over time and dynamics between attackers and defenders. In addition to understanding attacker and defender motives and tools, and identifying “relevant” system and attack data, it is also critical to develop rigorous mathematical formulations representing the defender’s decision-support problem under uncertainty. Game-theoretic approaches involving cyber resource allocation optimization with Markov decision processes (MDP) have been previously proposed in the literature. Moreover, advancements in reinforcement learning approaches have motivated the development of partially observable stochastic games (POSGs) in various multi-agent problem domains with partial information. Recent advances in cyber-system state space modeling have also generated interest in potential applicability of POSGs for cybersecurity. However, as is the case in strategic card games such as poker, research challenges using game-theoretic approaches for practical cyber defense applications include: 1) solving for equilibrium and designing efficient algorithms for large-scale, general problems; 2) establishing mathematical guarantees that equilibrium exists; 3) handling possible existence of multiple equilibria; and 4) exploitation of opponent weaknesses. Inspired by advances in solving strategic card games while acknowledging practical challenges associated with the use of game-theoretic approaches in cyber settings, this paper proposes an agent-centric approach for cybersecurity decision-support with partial system state observability.

Tipireddy, Ramakrishna↗
DOE OSTI2020

Analogous wheat root rhizosphere microbial successions in field and greenhouse trials in the presence of biocontrol agents Paenibacillus peoriae SP9 and Streptomyces fulvissimus FU14

Abstract Two Pythium ‐infested soils were used to compare the wheat root and rhizosphere soil microbial communities from plants grown in the field or in greenhouse trials and their stability in the presence of biocontrol agents. Bacteria showed the highest diversity at early stages of wheat growth in both field and greenhouse trials, while fungal diversity increased later on, at 12 weeks of the crop cycle. The microbial communities were stable in roots and rhizosphere samples across both soil types used in this study. Such stability was also observed irrespective of the cultivation system (field or greenhouse) or addition of biocontrol coatings to wheat seeds to control Pythium disease (in this study soil infected with Pythium sp. clade F was tested). In greenhouse plant roots, Archaeorhizomyces , Debaryomyces , Delftia , and unclassified Pseudeurotiaceae were significantly reduced when compared to plant roots obtained from the field trials. Some operational taxonomic units (OTUs) represented genetic determinants clearly transmitted vertically by seed endophytes (specific OTUs were found in plant roots) and the plant microbiota was enriched over time by OTUs from the rhizosphere soil. This study provided key information regarding the microbial communities associated with wheat roots and rhizosphere soils at different stages of plant growth and the role that Paenibacillus and Streptomyces strains play as biocontrol agents in supporting plant growth in infested soils.

Araujo, Ricardo↗
DOE OSTI2014

SU-E-QI-13: Predictable Models for Radio-Sensitizing Agent Kinetics: Application to Stereotactic Synchrotron Radiation Therapy

Purpose: Iodine-enhanced radiotherapy is an innovative treatment combining the selective accumulation of an iodinated contrast agent in brain tumors with irradiations using monochromatic medium energy x-rays. The radiation dose enhancement depends on the time course of iodine in the tumors. A prolonged CT scanning (∼30 min) is required to follow-up iodine kinetics for recruited patients. This protocol could lead to substantial radiation dose to the patient. A novel method is proposed to reduce the acquisition time. Methods: 12 patients received an intravenous bolus of iodinated contrast agent, followed by a steady-state infusion to ensure stable intra-tumoral amounts of iodine during the treatment. Absolute iodine concentrations (IC) were derived from 40 multi-slice dynamic conventional CT images of the brain. The impulse response function (IRF) to the bolus was estimated using the adiabatic approximation of the Johnson and Wilson's model. The arterial input function (AIF) of the steady-state infusion was fitted with several models: Gamma, Gamma with recirculation and hybrid. Estimated IC were calculated by convolving the IRF with the modeled AIF and were compared to the measured data. Results: The gamma variate function was not relevant to model the AIF due to high differences with the measured AIF. The hybrid and the gamma with recirculation models provided differences below 8% during the whole acquisition time. The absolute difference between the measured and the estimated IC was lower than 0.5 mg/ml, which corresponds to 5% of dose enhancement error. Conclusion: The proposed method allows a good estimation of the iodine time course with reduced scanning delays (3 instead of 30 min) and dose to the patient. The results suggest that the dose errors may stay within the radiotherapy standards.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-QI-21: Iodinated Contrast Agent Time Course In Human Brain Metastasis: A Study For Stereotactic Synchrotron Radiotherapy Clinical Trials

Purpose: Synchrotron stereotactic radiotherapy (SSRT) is an innovative treatment combining the selective accumulation of heavy elements in tumors with stereotactic irradiations using monochromatic medium energy x-rays from a synchrotron source. Phase I/II clinical trials on brain metastasis are underway using venous infusion of iodinated contrast agents. The radiation dose enhancement depends on the amount of iodine in the tumor and its time course. In the present study, the reproducibility of iodine concentrations between the CT planning scan day (Day 0) and the treatment day (Day 10) was assessed in order to predict dose errors. Methods: For each of days 0 and 10, three patients received a biphasic intravenous injection of iodinated contrast agent (40 ml, 4 ml/s, followed by 160 ml, 0.5 ml/s) in order to ensure stable intra-tumoral amounts of iodine during the treatment. Two volumetric CT scans (before and after iodine injection) and a multi-slice dynamic CT of the brain were performed using conventional radiotherapy CT (Day 0) or quantitative synchrotron radiation CT (Day 10). A 3D rigid registration was processed between images. The absolute and relative differences of absolute iodine concentrations and their corresponding dose errors were evaluated in the GTV and PTV used for treatment planning. Results: The differences in iodine concentrations remained within the standard deviation limits. The 3D absolute differences followed a normal distribution centered at zero mg/ml with a variance (∼1 mg/ml) which is related to the image noise. Conclusion: The results suggest that dose errors depend only on the image noise. This study shows that stable amounts of iodine are achievable in brain metastasis for SSRT treatment in a 10 days interval.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-F-207-07: Dual-Energy Computed Tomography Detection Limit of Various Radiopaque Contrast Agents That Can Be Infused Within Absorbable Inferior Vena Cava Filters

Purpose: Absorbable IVC filters are shown to be safe and efficacious in preventing pulmonary embolism. These absorbable filters disappear from the body after their required duration, alleviating costly removal procedures and downstream complications. Monitoring the positioning and integrity of absorbable devices using dual-energy computed tomography (DECT) would improve treatment efficacy. The purpose of this study is to determine the limit of detection and the energy dependence of DECT for various contrast agents that may be infused within the IVC filters including gold nanoparticles (AuNP) having diameters of 2 and 4 nm. Methods: All imaging studies were performed on a GE Discovery CT750 system in Gemstone Spectral Imaging (GSI) mode. Plastic vials containing the contrast agent solutions of water and blood were placed in a water bath, and images were acquired with the GSI-5 preset. The images were reformatted into the coronal plane and 5mm diameter ROIs were placed within each solution on a GE Advantage Workstation. Monoenergetic reconstructions were generated from 40 – 140 keV. Results: Mass attenuation (contrast per unit density) for AuNPs was greater than iron, but less than barium and iodine. Contrast was 10.2 (± 3.6) HU for 4 nm AuNP at 0.72 mg/ml and 12.1 (± 4.2) for 2 nm AuNP at 0.31 mg/ml at 70 keV suggesting reasonable chance of visualization at these concentrations for 70 keV reconstruction. The contrast as a function of CT energy is similar in both water and blood. Iodine is most dependent, followed closely by barium and iron, and trailed by a large margin by the AuNP. This was unexpected given Au’s large atomic number and the predominance of photoelectric effect at low energy. Conclusion: Infusion of IVC filters with AuNP is feasible. Discrimination of AuNP-infused IVC filters from surrounding anatomy warrants further investigation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Non-isothermal crystallization kinetics of Fe{sub 2}O{sub 3}–CaO–SiO{sub 2} glass containing nucleation agent P{sub 2}O{sub 5}/TiO{sub 2}

Fe{sub 2}O{sub 3}–CaO–SiO{sub 2} glass ceramics containing nucleation agent P{sub 2}O{sub 5}/TiO{sub 2} were prepared by sol-gel method. The samples were characterized by X-ray diffraction (XRD) and differential scanning calorimetry (DSC). The activation energy and kinetic parameters for crystallization of the samples were calculated by the Johnson-Mehi-Avrami (JMA) model and Augis-Bennett method according to the results of DSC. The results showed that the crystallization mechanism of Fe{sub 2}O{sub 3}–CaO–SiO{sub 2} glass, whose non-isothermal kinetic parameter n = 2.3, was consistent with surface crystallization of the JMA model. The kinetics model function of Fe{sub 2}O{sub 3}–CaO–SiO{sub 2} glass, f(α) = 2.3(1–α)[–ln(1–α)]{sup 0.57}, was also obtained. The addition of nucleation agent P{sub 2}O{sub 5}/TiO{sub 2} could reduce the activation energy, which made the crystal growth modes change from onedimensional to three-dimensional.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Towards Immobilized Proton-Coupled Electron Transfer Agents for Electrochemical Carbon Capture from Air and Seawater

Electrochemical CO 2 separation has drawn attention as a promising strategy for using renewable energy to mitigate climate change. Redox-active compounds that undergo proton-coupled electron transfer (PCET) are an impetus for pH-swing-driven CO 2 capture at low energetic costs. However, multiple barriers hinder this technology from maturing, including sensitivity to oxygen and the slow kinetics of CO 2 capture. Here, we use vapor phase chemistry to construct a textile electrode comprising an immobilized PCET agent, poly(1-aminoanthraquinone) (PAAQ), and incorporate it into redox flow cells. This design contrasts with others that use dissolved PCET agents by confining proton-storage to the surface of an electrode kept separate from an aqueous, CO 2 -capturing phase. This system facilitates carbon capture from gaseous sources (a 1% CO 2 feed and air), as well as seawater, with the latter at an energetic cost of 202 kJ/mol CO2 , and we find that quinone moieties embedded within the electrode are more stable to oxygen than dissolved counterparts. Simulations using a 1D reaction-transport model show that moderate energetic costs should be possible for air capture of CO 2 with higher loadings of polymer-bound PCET moieties. The remarkable stability of this system sets the stage for producing textile-based electrodes that facilitate pH-swing-driven carbon capture in practical situations.

Ali, Fawaz↗