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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluating efficacy of indoor non-pharmaceutical interventions against COVID-19 outbreaks with a coupled spatial-SIR agent-based simulation framework

Contagious respiratory diseases, such as COVID-19, depend on sufficiently prolonged exposures for the successful transmission of the underlying pathogen. It is important that organizations evaluate the efficacy of non-pharmaceutical interventions aimed at mitigating viral transmission among their personnel. We have developed a operational risk assessment simulation framework that couples a spatial agent-based model of movement with an agent-based SIR model to assess the relative risks of different intervention strategies. By applying our model on MIT’s Stata center, we assess the impacts of three possible dimensions of intervention: one-way vs unrestricted movement, population size allowed onsite, and frequency of leaving designated work location for breaks. We find that there is no significant impact made by one-way movement restrictions over unrestricted movement. Instead, we find that reducing the frequency at which individuals leave their workstations combined with lowering the number of individuals admitted below the current recommendations lowers the likelihood of highly connected individuals within the contact networks that emerge, which in turn lowers the overall risk of infection. We discover three classes of possible interventions based on their epidemiological effects. By assuming a direct relationship between data on secondary attack rates and transmissibility in the agent-based SIR model, we compare relative infection risk of four respiratory illnesses, MERS, SARS, COVID-19, and Measles, within the simulated area, and recommend appropriate intervention guidelines.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Atomic resolution tracking of nerve-agent simulant decomposition and host metal–organic framework response in real space

Gas capture and sequestration are valuable properties of metal–organic frameworks (MOFs) driving tremendous interest in their use as filtration materials for chemical warfare agents. Recently, the Zr-based MOF UiO-67 was shown to effectively adsorb and decompose the nerve-agent simulant, dimethyl methylphosphonate (DMMP). Understanding mechanisms of MOF-agent interaction is challenging due to the need to distinguish between the roles of the MOF framework and its particular sites for the activation and sequestration process. Here, we demonstrate the quantitative tracking of both framework and binding component structures using in situ X-ray total scattering measurements of UiO-67 under DMMP exposure, pair distribution function analysis, and theoretical calculations. The sorption and desorption of DMMP within the pores, association with linker-deficient Zr6 cores, and decomposition to irreversibly bound methyl methylphosphonate were directly observed and analyzed with atomic resolution.

36 MATERIALS SCIENCE↗
DOE OSTI2026

ChemGraph as an agentic framework for computational chemistry workflows

Atomistic simulations are essential in chemistry and materials science but remain challenging to run due to the expert knowledge required for the setup, execution, and validation stages of these calculations. We present ChemGraph, an agentic framework powered by artificial intelligence and state-of-the-art simulation tools to streamline and automate computational chemistry and materials science workflows. ChemGraph leverages graph neural network-based foundation models for accurate yet computationally efficient calculations and large language models (LLMs) for natural language understanding, task planning, and scientific reasoning to provide an intuitive and interactive interface. We evaluate ChemGraph across 13 benchmark tasks and demonstrate that smaller LLMs (GPT-4o-mini, Claude-3.5-haiku, Qwen-2.5-14B) perform well on simple workflows, while more complex tasks benefit from using larger models. Importantly, we show that decomposing complex tasks into smaller subtasks through a multi-agent framework enables GPT-4o to reach perfect accuracy and smaller LLMs to match or exceed single-agent GPT-4o's performance in these benchmarks.

Computational chemistry↗
DOE OSTI2016

Tuning the metabolism of the anticancer drug cisplatin with chemoprotective agents to improve its safety and efficacy

Numerous in vivo studies have shown that the severe toxic side-effects of intravenously administered cisplatin can be significantly reduced by the co-administration of sulfur-containing ‘chemoprotective agents’. Using a metallomics approach, a likely biochemical basis for these potentially useful observations was only recently uncovered and appears to involve the reaction of chemoprotective agents with cisplatin-derived Pt-species in human plasma to form novel platinum–sulfur complexes (PSC's). We here reveal aspects of the structure of two PSC's and establish the identification of an optimal chemoprotective agent to ameliorate the toxic side-effects of cisplatin, while leaving its antineoplastic activity largely intact, as a feasible research strategy to transform cisplatin into a safer and more effective anticancer drug.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Dynamical systems approach to the study of a sociophysics agent-based model

The Sznajd model is a Potts-like model that has been studied in the context of sociophysics [1,2](where spins are interpreted as opinions). In a recent work [3], we generalized the Sznajd model to include assymetric interactions between the spins (interpreted as biases towards opinions) and used dynamical systems techniques to tackle its mean-field version, given by the flow: {eta}{sub {sigma}} = {Sigma}{sub {sigma}}'{sup M} = 1{eta}{sub {sigma}}{eta}{sigma}'({eta}{sub {sigma}}{rho}{sigma}'{yields}{sigma}-{sigma}'{rho}{sigma}{yields}{sigma}').Where hs is the proportion of agents with opinion (spin){sigma}', M is the number of opinions and {sigma}'{yields}{sigma}' is the probability weight for an agent with opinion {sigma} being convinced by another agent with opinion {sigma}'. We made Monte Carlo simulations of the model in a complex network (using Barabasi-Albert networks [4]) and they displayed the same attractors than the mean-field. Using linear stability analysis, we were able to determine the mean-field attractor structure analytically and to show that it has connections with well known graph theory problems (maximal independent sets and positive fluxes in directed graphs). Our dynamical systems approach is quite simple and can be used also in other models, like the voter model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Microbubbles as contrast agent for in-line x-ray phase-contrast imaging

In the present study, we investigated the potential of gas-filled microbubbles as contrast agents for in-line x-ray phase-contrast imaging (PCI) in biomedical applications. When imaging parameters are optimized, the microbubbles function as microlenses that focus the incoming x-rays to form bright spots, which can significantly enhance the image contrast. Since microbubbles have been shown to be safe contrast agents in clinical ultrasonography, this contrast-enhancement procedure for PCI may have promising utility in biomedical applications, especially when the dose of radiation is a serious concern. In this study, we performed both numerical simulations and ex vivo experiments to investigate the formation of the contrast and the effectiveness of microbubbles as contrast agents in PCI.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Multirate delivery of multiple therapeutic agents from metal-organic frameworks

The highly porous nature of metal-organic frameworks (MOFs) offers great potential for the delivery of therapeutic agents. Here, we show that highly porous metal-organic frameworks can be used to deliver multiple therapeutic agents—a biologically active gas, an antibiotic drug molecule, and an active metal ion—simultaneously but at different rates. The possibilities offered by delivery of multiple agents with different mechanisms of action and, in particular, variable timescales may allow new therapy approaches. Here, we show that the loaded MOFs are highly active against various strains of bacteria.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Influence of additional coupling agent on the mechanical properties of polyester–agave cantala roxb based composites

The mechanical and morphological properties of the unsaturated polyester resins (UPRs)-agave cantala roxb based composite are investigated in this paper. The cantala fiber woven in 3D angle interlock was utilized as the composite reinforcement. Surface grafting of the cantala fiber through chemical treatment was performed by introducing silane coupling agent to improving the compatibility with the polymer matrix. The fabrication of the composite specimens was conducted using vacuum bagging technique. The effect of additional coupling agent to the morphological appearance of surface fracture was observed using scanning electron microscopy. Meanwhile, the influence of additional silane to the mechanical properties was examined using tensile, bending and impact test. The photograph of surface fracture on the treated specimens showed the residual matrix left on the fibers in which the phenomenon was not found in the untreated specimens. Based on mechanical tests, the treated specimens were successfully increased their mechanical properties by 55%, 9.67%, and 92.4% for tensile strength, flexural strength, and impact strength, respectively, at 1.5% silane coupling agent.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Gadolinium vanadate nanocrystals as carriers of α-emitters ( 225 Ac, 227 Th) and contrast agents

Gadolinium vanadate (GdVO 4 ) core and core +2 shell nanocrystals (NCs) were evaluated for in vitro retention of 225 Ac, 227 Th, and their first decay daughters, 221 Fr and 223 Ra, respectively. GdVO 4 NCs with a tetragonal crystal system (zircon-type) and spherical morphology were obtained by precipitation of GdCl 3 and Na 3 VO 4 using sodium citrate as a complexing agent. The growth of two nonradioactive GdVO 4 shells on both Gd( 225 Ac)VO 4 and Gd( 227 Th)VO 4 core NCs was demonstrated by an increase of 0.7 nm and 2 nm in the crystallite size, respectively. The maximum leakage of 225 Ac was 15% and 2.4% from core and core + 2 shells, whereas the leakage of 227 Th was 3% and 1.5%, respectively. The presence of two nonradioactive GdVO 4 shells increased the retention of 221 Fr and 223 Ra by 20% and 15% with respect to core NCs. Furthermore, a longitudinal proton relaxivity, r 1 = 0.9289 s –1 mM –1 , confirmed their potential application as contrast agents for magnetic resonance imaging. In summary, GdVO 4 NCs show promising capabilities as radionuclide carriers with partial retention of decay daughters and as contrast agents for theranostic applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Comparison of the Antiviral Activity of Remdesivir, Chloroquine, and Interferon-β as Single or Dual Agents Against the Human Beta-Coronavirus OC43

The human beta-coronavirus strain, OC43, provides a useful model for testing the antiviral activity of various agents. We compared the activity of several antiviral drugs against OC43, including remdesivir, chloroquine, interferon (IFN)-β, IFN-λ1, and IFN-λ4, in two distinct cell types: human colorectal carcinoma cell line (HCT-8 cells) and normal human bronchial epithelial (NHBE) cells. We also tested whether these agents mediate additive, synergistic, or antagonistic activity against OC43 infection when used in combination. When used as single agents, remdesivir exhibited stronger antiviral activity than chloroquine, and IFN-β exhibited stronger activity than IFN-λ1 or IFN-λ4 against OC43 in both HCT-8 and NHBE cells. Anakinra (IL-1 inhibitor) and tocilizumab (IL-6 inhibitor) did not mediate any antiviral activity. The combination of IFN-β plus chloroquine or remdesivir resulted in higher synergy scores and higher expression of IFN-stimulated genes than did IFN-β alone. In contrast, the combination of remdesivir plus chloroquine resulted in an antagonistic interaction in NHBE cells. Our findings indicate that the combined use of IFN-β plus remdesivir or chloroquine induces maximal antiviral activity against human coronavirus strain OC43 in primary human respiratory epithelial cells. Furthermore, our experimental OC43 virus infection model provides an excellent method for evaluating the biological activity of antiviral drugs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Data-driven Distributed Learning of Multi-agent Systems: A Koopman Operator Approach

Koopman operator theory provides a model-free technique for studying nonlinear dynamical systems purely from data. Since the Koopman operator is infinite-dimensional, researchers have developed several methods that provide a finite-dimensional approximation of the Koopman operator so that it can be applied for practical use cases. One common thing with most of the methods is that their solutions are obtained by solving a centralized minimization problem. In this work, we treat the dynamical system to be a multi-agent system and propose an algorithm to compute the finite-dimensional approximation of the Koopman operator in a distributed manner using the knowledge of the topology of the underlying multi-agent system. The proposed distributed approach is shown to be equivalent to the centralized learning problem and results in a sparse Koopman whose block structure mimics the Laplacian of the multi-agent system. Extensive simulation studies illustrate the proposed framework on the network of oscillators and the IEEE 68 bus system.

Nandanoori, Sai Pushpak↗
DOE OSTI2019

PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design

The ever increasing computational cost of Deep Neural Networks (DNN) and the demand for energy efficient hardware for DNN acceleration has made accuracy and hardware cost co-optimization for DNNs tremendously important, especially for edge devices. Owing to the large parameter space and cost of evaluating each parameter in the search space, manually tuning of DNN hyperparameters is impractical. Automatic joint DNN and hardware hyperparameter optimization is indispensable for such problems. Bayesian optimization-based approaches have shown promising results for hyperparameter optimization of DNNs. However, most of these techniques have been developed without considering the underlying hardware, thereby leading to inefficient designs. Further, the few works that perform joint optimization are not generalizable and mainly focus on CMOS-based architectures. In this work, we present a novel pseudo agent-based multiobjective hyperparameter optimization (PABO) for maximizing the DNN performance while obtaining low hardware cost. Compared to the existing methods, our work poses a theoretically different approach for joint optimization of accuracy and hardware cost and focuses on memristive crossbar based accelerators. PABO uses a supervisor agent to establish connections between the posterior Gaussian distribution models of network accuracy and hardware cost requirements. The agent reduces the mathematical complexity of the co-optimization problem by removing unnecessary computations and updates of acquisition functions, thereby achieving significant speed-ups for the optimization procedure. PABO outputs a Pareto frontier that underscores the trade-offs between designing high-accuracy and hardware efficiency. Our results demonstrate a superior performance compared to the state-of-the-art methods both in terms of accuracy and computational speed (~100x speed up).

Parsa, Maryam↗
DOE OSTI2024

Deep Multi-Agent Reinforcement Learning for Real-World Signalized Traffic Corridor Control

Signalized traffic control problem has been addressed recently with deep Reinforcement Learning (RL) approaches involving diverse state, action, and reward structures. While significant progress has been noted in the literature, open challenges still remain in the areas of adaptive signal phase timing, coordination in a multi-intersection corridor setting, and consideration of real-world traffic conditions. In the context of deep RL-based problem framing, extensions are needed that enable adaptive signal phase timings in an intersection agent's action space, computationally efficient information sharing among neighboring signalized intersection agents along a corridor, and experimentation in realistic simulation environments. In this paper, we develop a deep Advantage Actor Critic (A2C) multi-agent RL (MARL) approach capturing the research extensions above and apply it within a real-world calibrated Aimsun Next traffic corridor simulation model based on traffic data from the City of Coral Gables, Florida. For a multi-intersection corridor control setting, our numerical simulation experiments with a decentralized A2C MARL algorithm applied at different time periods led to a total average corridor travel delay reduction (expressed in seconds/mile averaged over vehicles) from 4.9% to 19.9% compared to state-of-the-art actuated control.

Shuvo, Salman S. [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2018

A Hierarchical Multi-Agent Based Anomaly Detection for Wide-Area Protection in Smart Grid

Future smart grid capabilities provide assurance to expand the advanced information and communication technologies to evolve into densely interconnected cyber physical system. Remedial Action Scheme (RAS), widely used for wide-area protection, relies on the interconnected networks and data sharing devices, which are exposed to the multitude of vulnerabilities. This paper presents our proposed approach to developing multi-agent based RAS scheme against the system-aware stealthy cyber-attacks. Specifically, we propose the two-level hierarchical architecture which consists of distributed local RAS controllers (RAScs) as local agents, operating at different zones/ areas, which are constantly monitored by an overseer, the central agent. The local controllers receive local and randomly changing outside zonal measurements and cyclically forwards to the overseer. The overseer identifies the corrupted controller using the anomaly detection algorithm which processes the measurements coming from the local controllers, compute measurement errors using local and outside zonal measurements, perform validation checks, and finally detect anomalies based on the two-step verification. Next, as a proof of concept, we have implemented and validated the proposed methodology in cyber physical environment at Iowa State’s PowerCyber testbed. We have also implemented the coordinated attack vectors which involve corrupting the local controller and later performing stealthy attacks on the system’s generator. We have evaluated its performance during the online testing in terms of detection rate and Iatency. The experimental results show that it is efficient in detecting different classes of attacks, including ramp and pulse attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Use of carbonyldiimidazole as a derivatization agent for the detection of pinacolyl alcohol, a forensic marker for Soman, by EI-GC–MS and LC-HRMS in official OPCW proficiency test matrices

Pinacolyl alcohol (PA), a key forensic marker for the nerve agent Soman (GD), is a particularly difficult analyte to detect by various analytical methods. In this work, we have explored the reaction between PA and 1,1'-carbonyldiimidazole (CDI) to yield pinacolyl 1H-imidazole-1-carboxylate (PIC), a product that can be conveniently detected by gas chromatography–mass spectrometry (GC–MS) and liquid chromatography-high-resolution mass spectrometry (LC-HRMS). Regarding its GC–MS profile, this new carbamate derivative of PA possesses favorable chromatographic features such as a sharp peak and a longer retention time (RT = 16.62 min) relative to PA (broad peak and short retention time, RT = 4.1 min). Additionally, the derivative can also be detected by LC-HRMS, providing an avenue for the analysis of this chemical using this technique where PA is virtually undetectable unless present in large concentrations. From a forensic science standpoint, detection of this low molecular weight alcohol signals the past or latent presence of the nerve agent Soman (GD) in a given matrix (i.e., environmental or biological). The efficiency of the protocol was tested separately in the analysis and detection of PA by EI-GC–MS and LC-HRMS when present at a 10 μg/mL in a soil matrix featured in the 44th PT and in a glycerol-rich liquid matrix featured in the 48th Official Organization for the Prohibition of Chemical Weapons (OPCW) Proficiency Test when present at a 5 μg/mL concentration. In both scenarios, PA was successfully transformed into PIC, establishing the protocol as an additional tool for the analysis of this unnatural and unique nerve agent marker by GC–MS and LC-HRMS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Comparative efficacy of valnoctamide and sec ‐butylpropylacetamide ( SPD ) in terminating nerve agent–induced seizures in pediatric rats

Summary Objectives Children and adults are likely to be among the casualties in a civilian nerve agent exposure. This study evaluated the efficacy of valnoctamide (racemic‐VCD), sec ‐butylpropylacetamide (racemic‐SPD), and phenobarbital for stopping nerve agent seizures in both immature and adult rats. Methods Female and male postnatal day ( PND ) 21, 28, and 70 (adult) rats, previously implanted with electroencephalography (EEG) electrodes were exposed to seizure‐inducing doses of the nerve agents sarin or VX and EEG was recorded continuously. Five minutes after seizure onset, animals were treated with SPD , VCD, or phenobarbital. The up‐down method was used over successive animals to determine the anticonvulsant median effective dose (ED 50 ) of the drugs. Results SPD‐ED 50 values in the VX model were the following: PND 21, 53 mg/kg (male) and 48 mg/kg (female); PND 28, 108 mg/kg (male) and 43 mg/kg (female); and PND 70, 101 mg/kg (male) and 40 mg/kg (female). SPD ‐ ED 50 values in the sarin model were the following: PND 21, 44 mg/kg (male) and 28 mg/kg (female); PND 28, 79 mg/kg (male) and 34 mg/kg (female); and PND 70, 53 mg/kg (male) and 53 mg/kg (female). VCD ‐ ED 50 values in the VX model were the following: PND 21, 34 mg/kg (male) and 43 mg/kg (female); PND 28, 165 mg/kg (male) and 59 mg/kg (female); and PND 70, 87 mg/kg (male) and 91 mg/kg (female). VCD ‐ ED 50 values in the sarin model were the following: PND 21, 45 mg/kg (male), 48 mg/kg (female); PND 28, 152 mg/kg (male) 79 mg/kg (female); and PND 70, 97 mg/kg (male) 79 mg/kg (female). Phenobarbital‐ ED 50 values in the VX model were the following: PND 21, 43 mg/kg (male) and 18 mg/kg (female); PND 28, 48 mg/kg (male) and 97 mg/kg (female). Phenobarbital‐ ED 50 values in the sarin model were the following: PND 21, 32 mg/kg (male) and 32 mg/kg (female); PND 28, 58 mg/kg (male) and 97 mg/kg (female); and PND 70, 65 mg/kg (female). Significance SPD and VCD demonstrated anticonvulsant activity in both immature and adult rats in the sarin‐ and VX ‐induced status epilepticus models. Phenobarbital was effective in immature rats, whereas in adult rats, higher doses were required that were accompanied by toxicity. Overall, significantly less drug was required to stop seizures in PND 21 animals than in the older animals, and overall, males required higher amounts of drug than females.

Haines, Kari M.↗
DOE OSTI2025

Three‐trophic level food webs support the safety of a biocontrol agent 3 years after release

Biological control (biocontrol) is a powerful tool for managing invasive alien species and assisting the restoration of native ecosystems. Rigorous post‐release monitoring of biocontrol agents is critical to evaluate the success of biocontrol programs; however, this is still rarely implemented. Here, we combined the use of species interaction networks with a Before‐After Control‐Impact design to evaluate the target and non‐target, direct and indirect effects of the Australian gall wasp Trichilogaster acaciaelongifoliae , released to control the invasive plant Acacia longifolia in Portugal. We compared the structure of plant‐galling insect‐parasitoid food webs before and 3 years after the release of the biocontrol agent. Exhaustive sampling did not detect any non‐target effects, either direct (on non‐target plants) or indirect (on other galling insects via shared plants). Additionally, no significant changes were detected in network structure that could be related to the establishment of the biocontrol agent. This study shows that monitoring biocontrol at the community level is possible and that, when carefully planned, biocontrol poses minimal risk of non‐target effects.

López‐Núñez, Francisco A. [Centre for Functional E↗
DOE OSTI2014

SU-E-T-256: Optimizing the Combination of Targeted Radionuclide Therapy Agents Using a Multi-Scale Patient-Specific Monte Carlo Dosimetry Platform

Purpose: Combination targeted radionuclide therapy (TRT) is appealing because it can potentially exploit different mechanisms of action from multiple radionuclides as well as the variable dose rates due to the different radionuclide half-lives. The work describes the development of a multiobjective optimization algorithm to calculate the optimal ratio of radionuclide injection activities for delivery of combination TRT. Methods: The ‘diapeutic’ (diagnostic and therapeutic) agent, CLR1404, was used as a proof-of-principle compound in this work. Isosteric iodine substitution in CLR1404 creates a molecular imaging agent when labeled with I-124 or a targeted radiotherapeutic agent when labeled with I-125 or I-131. PET/CT images of high grade glioma patients were acquired at 4.5, 24, and 48 hours post injection of 124I-CLR1404. The therapeutic 131I-CLR1404 and 125ICLR1404 absorbed dose (AD) and biological effective dose (BED) were calculated for each patient using a patient-specific Monte Carlo dosimetry platform. The optimal ratio of injection activities for each radionuclide was calculated with a multi-objective optimization algorithm using the weighted sum method. Objective functions such as the tumor dose heterogeneity and the ratio of the normal tissue to tumor doses were minimized and the relative importance weights of each optimization function were varied. Results: For each optimization function, the program outputs a Pareto surface map representing all possible combinations of radionuclide injection activities so that values that minimize the objective function can be visualized. A Pareto surface map of the weighted sum given a set of user-specified importance weights is also displayed. Additionally, the ratio of optimal injection activities as a function of the all possible importance weights is generated so that the user can select the optimal ratio based on the desired weights. Conclusion: Multi-objective optimization of radionuclide injection activities can provide an invaluable tool for maximizing the dosimetric benefits in multi-radionuclide combination TRT. BT, JG, and JW are affiliated with Cellectar Biosciences which owns the licensing rights to CLR1404 and related compounds.

60 APPLIED LIFE SCIENCES↗