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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Predicting nutrition and environmental factors associated with female reproductive disorders using a knowledge graph and random forests

Female reproductive disorders (FRDs) are common health conditions that may present with significant symptoms. Diet and environment are potential areas for FRD interventions. We utilized a knowledge graph (KG) method to predict factors associated with common FRDs (for example, endometriosis, ovarian cyst, and uterine fibroids). We harmonized survey data from the Personalized Environment and Genes Study (PEGS) on internal and external environmental exposures and health conditions with biomedical ontology content. We merged the harmonized data and ontologies with supplemental nutrient and agricultural chemical data to create a KG. We analyzed the KG by embedding edges and applying a random forest for edge prediction to identify variables potentially associated with FRDs. We also conducted logistic regression analysis for comparison. Across 9765 PEGS respondents, the KG analysis resulted in 8535 significant or suggestive predicted links between FRDs and chemicals, phenotypes, and diseases. Amongst these links, 32 were exact matches when compared with the logistic regression results, including comorbidities, medications, foods, and occupational exposures. Mechanistic underpinnings of predicted links documented in the literature may support some of our findings. Our KG methods are useful for predicting possible associations in large, survey-based datasets with added information on directionality and magnitude of effect from logistic regression. These results should not be construed as causal but can support hypothesis generation. This investigation enabled the generation of hypotheses on a variety of potential links between FRDs and exposures. Future investigations should prospectively evaluate the variables hypothesized to impact FRDs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Use of Multi-Site Radiation Therapy for Systemic Disease Control

Metastatic cancer is a heterogeneous entity, some of which could benefit from local consolidative radiation therapy (RT). Although randomized evidence is growing in support of using RT for oligometastatic disease, a highly active area of investigation relates to whether RT could benefit patients with polymetastatic disease. This article highlights the preclinical and clinical rationale for using RT for polymetastatic disease, proposes an exploratory framework for selecting patients best suited for these types of treatments, and briefly reviews potential challenges. The goal of this hypothesis-generating review is to address personalized multimodality systemic treatment for patients with metastatic cancer. The rationale for using high-dose RT is primarily for local control and immune activation in either oligometastatic or polymetastatic disease. However, the primary application of low-dose RT is to activate distinct antitumor immune pathways and modulate the tumor stroma in efforts to better facilitate T cell infiltration. We explore clinical cases involving high- and low-dose RT to demonstrate the potential efficacy of such treatment. We then group patients by extent of disease burden to implement high- and/or low-dose RT. Patients with low-volume disease may receive high-dose RT to all sites as part of an oligometastatic paradigm. Subjects with high-volume disease (for whom standard of care remains palliative RT only) could be treated with a combination of high-dose RT to a few sites for immune activation, while receiving low-dose RT to several remaining lesions to enhance systemic responses from high-dose RT and immunotherapy. We further discuss how emerging but speculative concepts such as immune function may be integrated into this approach and examine therapies currently under investigation that may help address immune deficiencies. The review concludes by addressing challenges in using RT for polymetastatic disease, such as concerns about treatment planning workflows, treatment times, dose constraints for multiple-isocenter treatments, and economic considerations.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Research-Driven Radiation Oncology: A Narrative on the Ongoing Legacy of Henry S. Kaplan

In this rapidly evolving time of precision medicine and scientifically based cancer care, how radiation oncology became a strong research-based scientific discipline in the United States after its separation from diagnostic radiology might be lost. The importance of generational mentorship, “family trees,” and interpersonal relationships can be difficult or impossible to trace absent personal narrative recollections of those involved. Henry S. Kaplan is a central figure and the focal point for 3 generations of research-based academic department chairs. This report establishes a first draft of a living record of the radiation oncology history of the Kaplan legacy to serve as an example of how knowledge networks grow and flourish and as an impetus for others to trace the legacy of other radiation oncology academic “trees.”.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Utility of Circulating MicroRNA-150 for Rapid Evaluation of Bone Marrow Depletion After Radiation and Efficiency of Bone Marrow Reconstitution

Total body irradiation (TBI) is a common myeloablative preparative regimen used in acute myeloid and lymphoblastic leukemia patients before allogenic hematopoietic stem cell transplantation (HSCT). The inefficient clearance of tumor cells and radiation-induced toxicity to normal tissues is attributed to relapse and morbidity in a significant fraction of patients. Developing biomarkers that indicate an individual's physiological response to radiation will allow personalized treatment and follow-up. We investigated the utility of circulating microRNA150-5p (miR150) for evaluation of radiation dose response.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Subject-specific multi-scale modeling of the fate of inhaled aerosols

Determining the fate of inhaled aerosols in the respiratory system is essential in assessing the potential toxicity of inhaled airborne materials, responses to airborne pathogens, or in improving inhaled drug delivery. The availability of high-resolution clinical lung imaging and advances in the reconstruction of lung airways from CT images have led to the development of subject-specific in-silico 3D models of aerosol dosimetry, often referred to as computational fluid-particle-dynamics (CFPD) models. As CFPD models require extensive computing resources, they are typically confined to the upper and large airways. These models can be combined with lower-dimensional models to form multiscale models that predict the transport and deposition of inhaled aerosols in the entire respiratory tract. Understanding where aerosols deposit is only the first of potentially several key events necessary to predict an outcome, being a detrimental health effect or a therapeutic response. To that end, multiscale approaches that combine CFPD with physiologically-based pharmacokinetics (PBPK) models have been developed to evaluate the absorption, distribution, metabolism, and excretion (ADME) of toxic or medicinal chemicals in one or more compartments of the human body. CFPD models can also be combined with host cell dynamics (HCD) models to assess regional immune system responses. Here, this paper reviews the state of the art of these different multiscale approaches and discusses the potential role of personalized or subject-specific modeling in respiratory health.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Subject-specific modeling framework for particle deposition using computational fluid dynamics

Quantifying particle deposition and dose in the respiratory tract requires a physiologically realistic representation and reproducible computational workflows. However, existing modeling frameworks, such as the International Commission on Radiological Protection (ICRP) compartmental models and the Multiple Path Particle Dosimetry (MPPD) tool, lack detailed deposition profiles and subject-specific capabilities. The combination of advances in computer vision algorithms applied to the respiratory tract and Computational Fluid and Particle Dynamics (CFPD) allows high-fidelity simulations of particle behavior in anatomically accurate geometries derived from individual CT scans. The segmentation, preprocessing, and file preparation task for a CFPD simulation was often time-consuming, and no prior studies to-date have yet presented a fully automated framework. This work presents a fully automated workflow to obtain individualized particle deposition profiles in the human respiratory tract. The pipeline starts with segmenting upper and lower airway geometries using morphological and deep learning-based methods, generating three-dimensional (3D) models from CT imaging data. Next, a series of algorithms are presented to quality check and prepare the 3D geometry for a CFD or CFPD simulation. The preprocessing step includes correcting geometric artifacts, enforcing a physically consistent mesh, and automatically identifying and capping multiple outlets, which is required for CFD/CFPD simulations. These processed models are then input into open-source (OpenFOAM) or commercial (StarCCM+) CFD solvers, where flow and transient particle transport equations — including turbulence and particle–wall interactions are solved under realistic breathing conditions. Finally, the resulting particle deposition profiles can be integrated with Monte Carlo radiation transport codes and state-of-the-art computational phantoms to assess organ-specific absorbed doses in scenarios of radioactive aerosol inhalation. The presented work streamlines respiratory tract segmentation, preprocessing for CFD/CFPD simulations, and integration with dose assessment workflows, reducing manual intervention and improving access to high-fidelity, subject-specific modeling. The high precision in predicted particle deposition and dose distributions can improve personalized treatment strategies in respiratory medicine and refine dose estimates for radiation protection.

AI↗
DOE OSTI2022

UV/chlorine advanced oxidation processes for degradation of contaminants in water and wastewater: A comprehensive review

Advanced oxidation processes (AOPs) have recently gained increasing attention as promising alternatives to conventional water and wastewater treatment technologies. As an AOP, there has been a growing interest in UV/chlorine due to its multiple disinfection modes and ability to maintain chlorine residuals in drinking water distribution systems. Compared to the popular UV/H 2 O 2 AOP treatment process, UV/chlorine AOP possesses several advantages including a higher radical production efficiency and a lower power demand. The process has recently been applied for the degradation of a wide range of natural and synthetic organic as well as inorganic compounds including pharmaceutical and personal care products, natural organic matter, herbicides and insecticides, taste and odor, and different types of water and wastewaters. The focus of the present work is to review and evaluate the efficiency of the UV/chlorine process on the oxidation of these pollutants. Here a critical overview is provided of the fundamentals of UV/chlorine, controlling factors of the process performance, and a comparison with other UV-based AOPs. The formation of disinfection by-products (DBPs), one of the concerns associated with UV/chlorine treatment, is discussed and strategies to tackle this obstacle are provided for future studies and applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Dirty bomb source term characterization and downwind dispersion: Review of experimental evidence

Dirty bombs are considered one of the easiest forms of radiological terrorism, a form of terrorism based on the deliberate use of radiological material to cause adverse effects in a target population. One U.S. Government official has even described a dirty bomb attack as “all but inevitable”. While people in the vicinity of the blast may experience acute radiation effects, people downwind may unknowingly be contaminated by the radioactive airborne particulate and face increased long-term cancer risk. The likelihood of increased cancer risk depends on the radionuclide used and its specific activity, its aerosolization potential, the particle sizes generated in the blast, and where a person is with respect to the detonation. Different studies have reported that plausible radionuclides for dirty bomb include 60 Co, 90 Sr, 137 Cs, 192 Ir, 241 Am based on their availability in commercial sources as well as safeguards, the amount needed for adverse health effects, previous mishandling of radionuclides and malicious uses. In order to have increased long-term cancer risk, the radionuclide would have to deposit inside the body by entering the respiratory tract and then possibly migrate to other organs or bones (ground shine is not considered in this paper because areas affected by the event will likely become inaccessible). This implies that the particles will have to be smaller than 10 μm to be inhaled. Experiments involving the detonation of dirty bombs have shown that particles or droplets smaller than 10 μm are generated, independently from the initial radionuclide or its state (e.g., powder, solution). Atmospheric tests have shown that in unobstructed terrain, the radionuclide laden cloud can travel kilometers downwind even for relatively small amounts of explosives. Furthermore, buildings in the path of the cloud can change the dose rate. For instance, in one experiment with a single building, the dose rate was 1–2 orders of magnitude lower behind the obstacle compared to its front face. For people walking around, the amount of particulate deposited on them and inhaled will depend on their path relative to the cloud, resulting in the counterintuitive result that the closer people may actually not be the ones more at risk because they could simply miss the bulk of the cloud in their wandering. In summary, the long-term cancer risk for people caught in a dirty bomb cloud away from the detonation requires considering where and when the people are, which radionuclide was used, and the layout of the obstacles (e.g., buildings, vegetation) in the path of the cloud.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2022

Intrinsically stretchable neuromorphic devices for on-body processing of health data with artificial intelligence

For leveraging wearable technologies to advance precision medicine, personalized and learning-based analysis of continuously acquired health data is indispensable, for which neuromorphic computing could provide the most efficient implementation of artificial intelligence (AI) data processing. For realizing on-body neuromorphic computing, skin-like stretchability is required, but yet to be combined with the suite of desired neuromorphic metrics, including linear, symmetric weight update, and sufficient state retention, for achieving high computing efficiency. Here, we report an intrinsically stretchable neuromorphic device based on an electrochemical transistor, which provides a large number (>800) of states, linear/symmetric weight update, excellent switching endurance (>100 million), good state retention (>10 4 s), together with high stretchability of 100% strain. Further integration into a prototype array successfully realized the implementation of vector-matrix multiplication even at 100% strain. Finally, we demonstrate the feasibility of implementing AI-based classification of health signals (as exemplified by electrocardiograms) with a high accuracy that is minimally influenced by the stretched state of the neuromorphic hardware. Finally, this work breaks the ground for combining AI data analysis into skin-like wearable electronics for achieving human-integrated/mimetic intelligent systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Porous Janus materials with unique asymmetries and functionality

Porous Janus materials have attracted widespread attention due to their asymmetry in wettability, charge, pore size or structure, thermal/electrical conductivity, and chemical activity, among other properties. Multifunction integration and unique directional manipulation of liquid, ions, or gas within porous Janus materials enable rapid progress in diverse applications such as water-oil separation, fog collection, personal moisture and healthcare management, energy conversion, desalination, sensor devices, and biomedical applications. Additionally, compared with conventional homogeneous materials, porous Janus materials not only showcase superior performance and energetic potential but also open up new applications by virtue of the synergistic or independent effects of asymmetry. This in-depth review systematically analyzes the research progress of porous Janus materials, highlighting fabrication strategies, synergistic/independent work mechanisms, and emerging advanced applications. Finally, ongoing challenges and outlook for the future research of porous Janus materials are presented.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Inactivation of multiple human pathogens by Fathhome's dry sanitizer device: Rapid and eco-friendly ozone-based disinfection

SARS-CoV-2 spread rapidly, causing millions of deaths across the globe. As a result, demand for medical supplies and personal protective equipment (PPE) surged and supplies dwindled. Separate entirely, hospital-acquired infections have become commonplace and challenging to treat. To explore the potential of novel sterilization techniques, this study evaluated the disinfection efficacy of Fathhome's ozone-based, dry-sanitizing device by dose and time response. Inactivation of human pathogens was tested on non-porous (plastic) surfaces. 95.42-100% inactivation was observed across all types of vegetative microorganisms and 27.36% inactivation of bacterial endospores tested, with no residual ozone detectable after completion. These results strongly support the hypothesis that Fathhome's commercial implementation of gas-based disinfection is suitable for rapid decontamination of a wide variety of pathogens on PPE and other industrially relevant materials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A comparison of machine learning surrogate models of street-scale flooding in Norfolk, Virginia

Low-lying coastal cities, exemplified by Norfolk, Virginia, face the challenge of street flooding caused by rainfall and tides, which strain transportation and sewer systems and can lead to personal and property damage. While high-fidelity, physics-based simulations provide accurate predictions of urban pluvial flooding, their computational complexity renders them unsuitable for real-time applications. Using data from Norfolk rainfall events between 2016 and 2018, this study compares the performance of a previous surrogate model based on a random forest algorithm with two deep learning models: Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). The comparison of deep learning to the random forest algorithm is motivated by the desire to utilize a machine learning architecture that allows for the future inclusion of common uncertainty quantification techniques and the effective integration of relevant, multi-modal features.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Density scaling approximation for Monte-Carlo simulations of radioactive plumes

The release of radioactive gas into the atmosphere can diffuse into large volumes of air downwind from the point of release. The extent of radioactivity can cover thousands of cubic meters of air. For such large volumes, the weather models used to predict the down-wind distribution of the plume and the radiation transport models used to predict the radiation reaching ground-level from the plume can take tens of hours of computer time on multi-node institutional High-Performance Computing facilities. In this paper we focus on the radiation transport aspect of plume modeling. Here, we describe a phenomenological method for approximating the amounts of radiation that reach ground level from large volumes of a static radioactive plume that can be calculated on a stand-alone personal computer in much shorter computation times than those usually needed for such large volume evaluations. We refer to this method as the Density Scaling Approximation (DSA). Its ability to approximate ground-level count rates of large plumes comes from using a small-plume volume with a scaled-up value of air density to simulate the same number of scatterings that occur during transport in larger plume volumes at normal air density. We demonstrate the DSA by using a 100 m-diameter air-filled hemispherical dome geometry with a uniform volumetric activity of 135 Xe gas throughout the air-filled volume. The DSA for a larger dome diameter is obtained by evaluating the 100 m dome with an air density scaled up by the linear ratio of the larger diameter to the 100 m diameter. We find that this approximation works well for dome diameters up to 1200 m – the largest diameter studied and a size more than sufficient for accounting for all the radiation from 135 Xe. Moreover, most of our DSA results can be calculated over 500 times faster than corresponding full-sized geometry with normal air density. To help evaluate the accuracy of the DSA and gain insight into how well it can reproduce different regions of the spectra, we use three, easily understood regions of interest to compare the DSA results to the full-sized geometry at normal air density results. These regions are the full-energy peak, the region of single-Compton scattering, and the region of multiple-Compton scattering. We show how the dominance of the Compton scattering mechanism determines this division and thus provides insight into how Compton scattering is manifested in spectra from photon scattering through air in general, and how well the DSA approximation works.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Studying QGP with flow: A theory overview

I review recent developments in the phenomenological study of the quark-gluon plasma (QGP) transport properties based on a personal selection of results that were presented at Quark Matter 2019. Additionally, the constraints on the temperature dependence of QGP shear and bulk viscosity are summarized. I discuss new theory advancements towards more realistic 3D dynamical simulations of heavy-ion collisions at finite baryon density. The challenges and opportunities of applying hydrodynamics to small collision systems are highlighted.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

What is the Hierarchy Problem?

Is there a Hierarchy Problem? If so, what, exactly, is the problem? Almost every theorist has a personal answer to these questions. In this article, I give my answer. I will explain that the Hierarchy Problem is not a formal problem but rather our ignorance of a crucial physics explanation – the explanation of the nature of the Higgs boson. Without the solution to this problem, we cannot make progress on the major questions of our field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Radioarsenic: A promising theragnostic candidate for nuclear medicine

Molecular imaging is a non-invasive process that enable the visualization, characterization, and quantitation of biological processes at the molecular and cellular level. With the emergence of theragnostic agents to diagnose and treat disease for personalized medicine there is a growing need for matched pairs of isotopes. Matched pairs offer the unique opportunity to obtain patient specific information from SPECT or PET diagnostic studies to quantitate in vivo function or receptor density to inform and tailor therapeutic treatment. There are several isotopes of arsenic that have emissions suitable for either or both diagnostic imaging and radiotherapy. Their half-lives are long enough to pair them with peptides and antibodies which take longer to reach maximum uptake to facilitate improved patient pharmacokinetics and dosimetry then can be obtained with shorter lived radionuclides. Arsenic-72 even offers availability from a generator that can be shipped to remote sites and thus enhances availability. Arsenic has a long history as a diagnostic agent, but until recently has suffered from limited availability, lack of suitable chelators, and concerns about toxicity have inhibited its use in nuclear medicine. However, new production methods and novel chelators are coming online and the use of radioarsenic in the pico and nanomolar scale is well below the limits associated with toxicity. This manuscript will review the production routes, separation chemistry, radiolabeling techniques and in vitro/in vivo studies of three medically relevant isotopes of arsenic (arsenic-74, arsenic-72, and arsenic-77).

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Development and testing of a fission-like neutron field for dosimetry and instrument calibrations based on deuterium-tritium generator

For nearly five decades 252 Cf sources have been used for testing and calibration over a wide range of neutron detection devices used for nuclear safety and radiation protection. However, the vastly increased cost of 252 Cf sources, its short half-life, and concerns about future shortage have prompted nuclear facilities and radiological calibration laboratories that rely on high-intensity neutron sources to seek alternatives. There appear to be no other radionuclide neutron sources that would match “like-to-like” 252 Cf performance characteristics. Alternatives of producing a fission-like neutron spectrum based on commercially available deuterium-tritium (D-T) generators, and without any fissionable materials or beryllium, have been explored. This paper describes efforts of designing the spectrum shaping assembly, its construction and installation. The produced neutron field was evaluated both from the perspective of the neutron fluence spectrum and the resulting dosimetric outcome. Finally, it was tested for practical application by examining response of various health physics instruments and personal monitoring devices in comparison to the response of those devices when exposed to 252 Cf. In conclusion, the response of survey-type instruments tested within the prototype, surrogate fission, reference field are acceptably close to their response in the targeted 252 Cf field.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

The electric vehicles-solar photovoltaics Nexus: Driving cross-sectoral adoption of sustainable technologies

Residential and transportation energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics [PVs]) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market shares for both EVs and PVs continue to grow, both of these emerging technologies are deployed rather disjointly, without considering the existence of potential similarities among users who own (or aspire to own) these technologies. This might be due to lack of understanding of the behavioral interdependence in consumer preferences toward these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores interactive EV and PV adoption behaviors. A structural equation model is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values, and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive bundled adoption of EV-PV systems could accelerate the adoption of both of these sustainable technologies. In conclusion, this study highlights the need to consider transport and building energy-efficient technology adoption behavior in a single integrated structure.

14 SOLAR ENERGY↗