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At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Using Ultrasound Image Augmentation and Ensemble Predictions to Prevent Machine-Learning Model Overfitting

Deep learning predictive models have the potential to simplify and automate medical imaging diagnostics by lowering the skill threshold for image interpretation. However, this requires predictive models that are generalized to handle subject variability as seen clinically. Here, we highlight methods to improve test accuracy of an image classifier model for shrapnel identification using tissue phantom image sets. Using a previously developed image classifier neural network—termed ShrapML—blind test accuracy was less than 70% and was variable depending on the training/test data setup, as determined by a leave one subject out (LOSO) holdout methodology. Introduction of affine transformations for image augmentation or MixUp methodologies to generate additional training sets improved model performance and overall accuracy improved to 75%. Further improvements were made by aggregating predictions across five LOSO holdouts. This was done by bagging confidences or predictions from all LOSOs or the top-3 LOSO confidence models for each image prediction. Top-3 LOSO confidence bagging performed best, with test accuracy improved to greater than 85% accuracy for two different blind tissue phantoms. This was confirmed by gradient-weighted class activation mapping to highlight that the image classifier was tracking shrapnel in the image sets. Overall, data augmentation and ensemble prediction approaches were suitable for creating more generalized predictive models for ultrasound image analysis, a critical step for real-time diagnostic deployment.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Application of Machine Learning and Data Augmentation Algorithms in the Discovery of Metal Hydrides for Hydrogen Storage

The development of efficient and sustainable hydrogen storage materials is a key challenge for realizing hydrogen as a clean and flexible energy carrier. Among various options, metal hydrides offer high volumetric storage density and operational safety, yet their application is limited by thermodynamic, kinetic, and compositional constraints. In this work, we investigate the potential of machine learning (ML) to predict key thermodynamic properties—equilibrium plateau pressure, enthalpy, and entropy of hydride formation—based solely on alloy composition using Magpie-generated descriptors. We significantly expand an existing experimental dataset from ~400 to 806 entries and assess the impact of dataset size and data augmentation, using the PADRE algorithm, on model performance. Models including Support Vector Machines and Gradient Boosted Random Forests were trained and optimized via grid search and cross-validation. Results show a marked improvement in predictive accuracy with increased dataset size, while data augmentation benefits are limited to smaller datasets and do not improve accuracy in underrepresented pressure regimes. Furthermore, clustering and cross-validation analyses highlight the limited generalizability of models across different material classes, though high accuracy is achieved when training and testing within a single hydride family (e.g., AB2). The study demonstrates the viability and limitations of ML for accelerating hydride discovery, emphasizing the importance of dataset diversity and representation for robust property prediction.

augmentation↗

NASA NTRS2012

Actuation Using Piezoelectric Materials: Application in Augmenters, Energy Harvesters, and Motors

Piezoelectric actuators are used in many manipulation, movement, and mobility applications as well as transducers and sensors. When used at the resonance frequencies of the piezoelectric stack, the actuator performs at its maximum actuation capability. In this Space Grant internship, three applications of piezoelectric actuators were investigated including hammering augmenters of rotary drills, energy harvesters, and piezo-motors. The augmenter shows improved drill performance over rotation only. The energy harvesters rely on moving fluid to convert mechanical energy into electrical power. Specific designs allow the harvesters more freedom to move, which creates more power. The motor uses the linear movement of the actuator with a horn applied to the side of a rotor to create rotational motion. Friction inhibits this motion and is to be minimized for best performance. Tests and measurements were made during this internship to determine the requirements for optimal performance of the studied mechanisms and devices.

drills↗

NASA NTRS2014

Effect of Control System Augmentation on Handling Qualities and Task Performance in Good and Degraded Visual Environments

In June 2013, NASA and the U.S. Army jointly conducted a simulation experiment in the NASA-Ames Vertical Motion Simulator that examined and quantified the effects of limited-authority control system augmentation on handling qualities and task performance in both good and degraded visual environments (DVEs). The vehicle model used for the experiment was the OH-58D with similar size, weight and performance, and the same 4-blade rotor system as the Bell 407 civilian helicopter that is commonly used for medical evacuation and emergency medical services. The control systems investigated as part of this study included the baseline aircraft Rate Command system, a short-term Attitude Command/Attitude Hold system that uses lagged-rate feedback to provide a short-term attitude response, Modernized Control Laws that provide an Attitude Command/Attitude Hold control response type, and Modernized Control Laws with an additional Position Hold function. Evaluation tasks included the ADS-33 Hover, Sidestep, Acceleration/Deceleration, and Pirouette Mission Task Elements, as well as a new proposed Emergency Medical Services task that includes an approach and landing at a minimally prepared remote landing site. Degraded visual environments were simulated with night vision goggles and an unaided night scene. A total of nine experimental test pilots participated in the four-week simulation experiment. Data recorded during the evaluation included Cooper-Harper handling qualities ratings, Bedford Workload scale ratings, and task performance. The Usable Cue Environment (UCE) was measured for this simulation experiment, and found to be UCE equals 1 in good visual environments and UCE equals 2 in degraded visual environments with night vision goggles. Results showed that handling qualities ratings were improved with a control system providing short-term attitude response over a rate command system, although the improvements were not sufficient to produce Level 1 handling qualities in degraded visual environments. Results for an Attitude Command/Attitude Hold control system showed that borderline Level 1 handling qualities could be achieved in degraded visual environments, and the 10 percent authority stability augmentation system was adequate to obtain these handling qualities ratings.

Handling Qualities↗

NASA NTRS2023

Using Virtual Reality to Envision Deployment of Spacesuit-Compatible Augmented Reality Displays for Lunar Surface Operations

The National Aeronautics and Space Administration (NASA) will soon land crew on the lunar surface to establish a sustainable presence and develop operational concepts for future long-duration missions. New technologies will be necessary to extend planning and execution capabilities for lunar surface activities. The Joint Augmented Reality Visual Informatics System (Joint AR) at NASA Johnson Space Center (JSC) is one such technology. Joint AR is a suit-mounted augmented reality (AR) display and compute system which facilitates unprecedented information exchange and data visualization capabilities between mission support operators and suited crew. This paper describes challenges associated with developing an AR technology for an envisioned work domain by applying a sociotechnical lens to the iterative testing and development of novel AR technology through virtual reality (VR). A foundational VR testbed was established, providing a high-fidelity approximation of the lunar surface and enabling testing of envisioned AR system features in parallel with real world product development. Using this environment, a series of human-in-the-loop experiments were conducted using VR to deploy a notional AR system supporting use cases envisioned for lunar exploration extravehicular activity (xEVA). Our findings indicate VR is a powerful and immersive tool for testing capabilities which extend beyond the limitations of current AR technology. Our VR testbed enables early testing of proposed system features, advancing identification of high-value features and driving present-day development of Joint AR. Future work directions are discussed, including lessons learned and a roadmap for an iterative research and development approach applying VR (among other testbeds) to accelerate Joint AR system maturation.

Augmented reality↗

NASA NTRS2023

Trades, Architecture, and Design of the Joint Augmented Reality Visual Informatics (Joint AR) Product

Future expeditions will enable exploration and study of the planetary surfaces of the Moon and Mars by performing extravehicular activity (EVA) operations. Present-day International Space Station (ISS) EVA operations require an intricate and tight choreography of crew, space suits, tools, systems, and flight teams to plan, train, and execute with limited advanced informatics. Additionally, EVA operations, aside from the Apollo Lunar surface missions, have predominately focused on maintenance and construction tasks where success criteria are clearly measurable. However, future exploration missions expect to enable crew to carry out scientific objectives in increasingly Earth-independent ways. In this paper, the Joint Augmented Reality Visual Informatics System (Joint AR) characterizes the design space for developing a modular augmented reality (AR) device for a spacesuit form factor that can support crew decision-making for EVA. This paper highlights the project’s experience with a product-focused management style and use-case centered systems engineering approach to iteratively design, build, and test. The Joint AR product features were defined via trade studies and market analysis of previous EVA display efforts, various AR components such as optics, commercial AR systems, light engines, data interfaces, graphics engine software and analog test beds. We outline the defining architectural design decisions, including safety criticality considerations, suit mounting interfaces, computer architectures, and partnership contracting mechanisms. The outcomes of these studies, architecture decisions, and management requirements result in a recommended design which is the Joint AR product. We discuss the evolution, development of these system components, and what work remains. We hope to share a unified understanding of various design decisions and how they impact the future of crew members’ access to data during Lunar and Martian EVAs. This ongoing effort can enable a community-wide discovery process toward realizing necessary AR features and capabilities for future missions.

Augmented Reality↗

NASA NTRS2023

Energy Augmentation Concepts for Advanced Airspace Mobility Vehicles

This introductory paper describes several concepts that could be used for augmenting the energy state of electric Vertical Take-Off and Landing (eVTOL) vehicles. Advanced Air Mobility (AAM) electric vehicles, just like conventional vehicles, could need additional charge due to depleted batteries (e.g., strong winds along the way) while approaching their destination. There are three indirect charging and five direct charging concepts presented in this paper. The concepts are in preliminary research stage and are being refined. Considering the concepts are for the year 2045 timeframe, there is sufficient time to evolve them, along with the designs of the AAM vehicles. The paper describes more details and discussion on the desirability, viability, and feasibility of these energy augmentation concepts. A discussion of barriers and initial investigation approach for three concepts is presented.

AAM vehicles↗

NASA NTRS2023

Energy Augmentation Concepts for Advanced Airspace Mobility Vehicles

AAM vehicles↗

DOE OSTI2019

Ionic current in nanochannels grafted with pH-responsive polyelectrolyte brushes modeled using augmented strong stretching theory

Here, we provide a theory to quantify the ionic current (i ion ) in nanochannels grafted with pH-responsive polyelectrolyte (PE) brushes. We consider the PE brushes to be modelled by our recently proposed augmented strong stretching theory (SST) model that improves the existing SST models by incorporating the effects of excluded volume interactions and an extended mass action law. Use of such augmented SST for this problem implies that this is the first study on computing i ion in PE-brush-grafted nanochannels accounting for the appropriate coupled con guration-electrostatic description of the PE brushes. i ion is obtained as functions of PE brush grafting density, medium pH and salt concentration (c ∞ ), and the density of polyelectrolyte chargeable sites (PECS). For large c ∞ , i ion increases linearly with c ∞ (as for such c ∞ , i ion becomes independent of the PE charge and is dominated by the bulk mobility and number density of the electrolyte ions), while iion is independent of c ∞ at small c ∞ (where the EDL electrostatics and the total number of ions in the system is dominated by the hydrogen ions). We further witness an enhancement of i ion for smaller pH and larger grafting density at low and moderate c ∞ , while there is little to no effect of the PECS density on the ionic current except for weakly grafted brushes at low c ∞ . We believe that this study will serve as a theoretical foundation for a large number of applications that are based on the brush-induced modification of the ionic current in a nanochannel.

42 ENGINEERING↗

DOE OSTI2025

Kernel Manifolds: Nonlinear‐Augmentation Dimensionality Reduction Using Reproducing Kernel Hilbert Spaces

This paper generalizes recent advances on quadratic manifold (QM) dimensionality reduction by developing kernel methods-based nonlinear-augmentation dimensionality reduction. QMs, and more generally feature map-based nonlinear corrections, augment linear dimensionality reduction with a nonlinear correction term in the reconstruction map to overcome approximation accuracy limitations of purely linear approaches. While feature map-based approaches typically learn a least squares optimal polynomial correction term, we generalize this approach by learning an optimal nonlinear correction from a user-defined reproducing kernel Hilbert space. Our approach allows one to impose arbitrary nonlinear structure on the correction term, including polynomial structure, and includes feature map and radial basis function-based corrections as special cases. Furthermore, our method has relatively low training cost and has monotonically decreasing error as the latent space dimension increases. In conclusion, we compare our approach to proper orthogonal decomposition and several recent QM approaches on data from several example problems.

kernel methods↗

DOE OSTI2019

Laboratory Monitoring of Bone Tissue Remodeling after Augmentation of Impression Intraarticular Fracture with Different Types of Bone Graft

The effects of bone graft materials on the inflammatory response and biochemical markers of bone remodeling were studied on a rabbit model of fracture augmentation with the following grafts: β-tricalcium phosphate, demineralized bone matrix, nanostructured carbon implant, and porous titanium implant made by additive 3D printing. The markers of bone remodeling and the blood system response in the postoperative period were studied. It was found that porous titanium implant and β-tricalcium phosphate induced osteogenesis and minimized osteoclastic resorption. Augmentation with nanostructured carbon implant and demineralized bone matrix stimulated the processes of osteoclastic resorption.

3D PRINTING↗

DOE OSTI2015

Acidic environment augments FcεRI-mediated production of IL-6 and IL-13 in mast cells

Although blood pH is maintained in a narrow range of around pH 7.4 in living organisms, inflammatory loci are characterized by acidic conditions. Mast cells tend to reside close to the surface of the body in areas such as the mucosa and skin where they may be exposed to exogenous acids, and they play an important role in immune responses. However, little is known about the effects of extracellular acidification on the functions of mast cell. Here, we found that extracellular acidification increased the dinitrophenyl-conjugated human serum albumin (DNP-HSA)-induced production of interleukin (IL)-6 and IL-13 in MC/9 cells or bone marrow-derived mouse mast cells sensitized with anti-DNP IgE. Extracellular acidification also inhibited migration of MC/9 cells toward DNP-HSA. In addition, acidic pH stimulated antigen-induced activation of p38 mitogen-activated protein kinase (MAPK) and protein kinase B (Akt). These findings suggest that extracellular acidification augmented antigen/IgE-induced and FcεRI-mediated production of IL-6 and IL-13 in mast cells, and that this was associated with the enhancement of p38 MAPK and Akt activation. - Highlights: • Antigen-induced IL-6 and IL-13 production was augmented by acidic pH in mast cells. • Acidic pH-induced actions were associated with activation of p38 MAPK and Akt. • Inhibition of p38 MAPK and Akt attenuated cytokine responses to acidic pH. • Acidic pH effects are not attributable to actions of known proton-sensing GPCRs.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Augmented neutrophil extracellular traps formation promotes atherosclerosis development in socially defeated apoE −/− mice

Highlights: • Repeated social defeat exaggerates plaque size in apoE{sup −/−} mice. • Proportion of circulating neutrophils is significantly increased in defeated mice. • In vivo NETs formation is exaggerated within the atherosclerotic lesions in defeated mice. • DNase I treatment abrogates pro-atherogenic effect of RSD exposure. • In vitro NETs formation is exaggerated in BM PMN-MDSC from defeated mice. Depression is an independent risk factor of cardiovascular disease (CVD); however, the causal association remains undefined. We exposed mice to repeated social defeat (RSD) to precipitate depressive-like behaviors, and investigated the effects on atherosclerosis. Eight-week-old male apoE{sup −/−} mice were exposed to RSD by housing with a larger CD-1 mouse in a shared home cage. They were subjected to vigorous physical contact daily for 10 consecutive days and fed a high-cholesterol diet (HCD) for 6 weeks. The social interaction ratio and immobility time showed dramatic social avoidance before and after HCD feeding. Defeated mice showed higher increase in atherosclerotic lesion areas in the aortic root and entire aorta than control mice. Mean blood pressure and lipid profile were equivalent in both groups. While Ly-6G- and Mac3-positive areas in the aortic root were comparable between the groups, citrullinated histone H3 (Cit-H3)- and myeloperoxidase (MPO)-positive areas, markers of neutrophil extracellular traps (NETs), were significantly increased in the defeated mice. Treatment with DNase I completely diminished the exaggerated atherosclerosis. The proportion of peripheral blood polymorphonuclear myeloid-derived suppressor cells (PMN-MDSC), but not of inflammatory monocytes, was markedly increased. Moreover, in vitro NETs formation from bone marrow (BM) PMN-MDSC was markedly augmented, accompanied by higher expression of Nox2 gene and reactive oxygen species. Our findings demonstrate that exposure to RSD promotes atherosclerosis by augmenting NETs formation within the plaque. This provides new insight into the underlying mechanism of depression-related CVD.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Augmented Lagrangian formulation of orbital-free density functional theory

We present an Augmented Lagrangian formulation and its real-space implementation for non-periodic Orbital-Free Density Functional Theory (OF-DFT) calculations. In particular, we rewrite the constrained minimization problem of OF-DFT as a sequence of minimization problems without any constraint, thereby making it amenable to powerful unconstrained optimization algorithms. Further, we develop a parallel implementation of this approach for the Thomas–Fermi–von Weizsacker (TFW) kinetic energy functional in the framework of higher-order finite-differences and the conjugate gradient method. With this implementation, we establish that the Augmented Lagrangian approach is highly competitive compared to the penalty and Lagrange multiplier methods. Additionally, we show that higher-order finite-differences represent a computationally efficient discretization for performing OF-DFT simulations. Overall, we demonstrate that the proposed formulation and implementation are both efficient and robust by studying selected examples, including systems consisting of thousands of atoms. We validate the accuracy of the computed energies and forces by comparing them with those obtained by existing plane-wave methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Augmented Adam-Gibbs model for glass melt viscosity and configuration entropy as functions of temperature and composition

As the temperature of glass melt increases, its structure approaches the state of a simple liquid while the configuration entropy approaches a maximum value. We describe this gradual change using a power law function of inverse temperature. The Adam-Gibbs model for glass viscosity as a function of temperature and glass composition augmented in this way is greatly simplified when applied to common glass families occupying moderate composition regions, such as float glass or nuclear waste glasses, on which properties can be approximated as linear functions of composition. The parsimonious model thus obtained is preferable for use in optimizing glass formulation and mathematical modeling of glass melting and forming. For multicomponent glasses with N viscosity-affecting components, the augmented Adam-Gibbs model requires 2N + 3 adjustable parameters. The model efficacy is demonstrated by fitting the model to a viscosity-temperature-composition dataset for low-activity nuclear waste glasses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

A new augmentation based algorithm for extracting maximal chordal subgraphs

If every cycle of a graph is chordal length greater than three then it contains an edge between non-adjacent vertices. Chordal graphs are of interest both theoretically, since they admit polynomial time solutions to a range of NP-hard graph problems, and practically, since they arise in many applications including sparse linear algebra, computer vision, and computational biology. A maximal chordal subgraph is a chordal subgraph that is not a proper subgraph of any other chordal subgraph. Existing algorithms for computing maximal chordal subgraphs depend on dynamically ordering the vertices, which is an inherently sequential process and therefore limits the algorithms’ parallelizability. In our paper we explore techniques to develop a scalable parallel algorithm for extracting a maximal chordal subgraph. We demonstrate that an earlier attempt at developing a parallel algorithm may induce a non-optimal vertex ordering and is therefore not guaranteed to terminate with a maximal chordal subgraph. We then give a new algorithm that first computes and then repeatedly augments a spanning chordal subgraph. After proving that the algorithm terminates with a maximal chordal subgraph, we then demonstrate that this algorithm is more amenable to parallelization and that the parallel version also terminates with a maximal chordal subgraph. That said, the complexity of the new algorithm is higher than that of the previous parallel algorithm, although the earlier algorithm computes a chordal subgraph which is not guaranteed to be maximal. Finally, we experimented with our augmentation-based algorithm on both synthetic and real-world graphs. We provide scalability results and also explore the effect of different choices for the initial spanning chordal subgraph on both the running time and on the number of edges in the maximal chordal subgraph.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Augmented atherogenesis in ApoE-null mice co-exposed to polychlorinated biphenyls and 2,3,7,8-tetrachlorodibenzo-p-dioxin

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) and polychlorinated biphenyls (PCBs) are persistent organic pollutants found as complex mixtures in the environment throughout the world. Therefore, humans are ubiquitously and simultaneously exposed to TCDD and PCBs. TCDD and PCBs alone have been linked to atherosclerosis. However, the effects of interactions or synergism between TCDD and PCBs on atherogenesis are unknown. We investigated the possible enhanced atherogenesis by co-exposure to TCDD and PCBs and the potential mechanism(s) involved in this enhancement. Male ApoE{sup −/−} mice were exposed to TCDD (15 μg/kg) and Aroclor1254 (55 mg/kg, a representative mixture of PCBs) alone or in combination by intraperitoneal injection four times over six weeks of duration. Our results showed that mice exposed to TCDD alone, but not Aroclor1254 alone, developed atherosclerotic lesions. Moreover, we found that atherosclerotic disease was exacerbated to the greatest extent in mice co-exposed to TCDD and Aroclor1254. The enhanced lesions correlated with several pro-atherogenic changes, including a marked increase in the accumulation of the platelet-derived chemokine PF4, and the expression of the proinflammatory cytokine MCP-1 and the critical immunity gene-RIG-I. Our data demonstrated that co-exposure to TCDD and Aroclor1254 markedly enhanced atherogenesis in ApoE{sup −/−} mice. Significantly, our observations suggest that combined exposure to TCDD and PCBs may be a greater cardiovascular health risk than previously anticipated from individual studies. - Highlights: • Augmented atherogenesis was found in ApoE{sup −/−} mice co-exposed to Aroclor1254 and TCDD. • Enhanced expression of PF4, MCP-1 and RIG-I correlated with augmented lesions. • POPs combination may be a greater cardiovascular health risk than individual POPs.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Thermoosmotic Transport in Nanochannels Grafted with pH-responsive Polyelectrolyte Brushes Modelled Using Augmented Strong Stretching Theory

In this paper, we develop a theory to establish that the thermoosmotic (TOS) effects, induced by the application of an axial temperature gradient, leads to a massive enhancement in liquid transport in nanochannels grafted with charged polyelectrolyte (PE) brushes. Here, we quantify the TOS transport by quantifying the induced electric field and the induced TOS flow field. The different components of the electric field, namely the ionic component, the thermal component, and the osmotic component, as well as the contributions of different ions to these components, are quantified. Furthermore, we express the TOS velocity as a combination of chemiosmotic (COS), thermal, and electroosmotic (EOS) components. The COS and the thermal components augment each other and the overall strength and direction of the TOS flow are dictated by the direction and the relative strength of the EOS component. Most importantly, we compare the cases of brush-grafted nanochannels with those of the brush-free nanochannels of identical surface charge densities: the TOS transport is massively augmented in the brush-grafted nanochannels attributed to the combination of the localization of the EDL (and hence any body force that depends on the EDL charge density) away from the nanochannel wall (i.e., the location of the maximum drag force) and the presence of a possible molecular slip (experienced by the liquid) along the brush surface.

42 ENGINEERING↗