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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Pollen structure visualization using high-resolution laboratory-based hard X-ray tomography

A laboratory-based X-ray microscope is used to investigate the 3D structure of unstained whole pollen grains. For the first time, high-resolution laboratory-based hard X-ray microscopy is applied to study pollen grains. Based on the efficient acquisition of statistically relevant information-rich images using Zernike phase contrast, both surface- and internal structures of pine pollen - including exine, intine and cellular structures - are clearly visualized. The specific volumes of these structures are calculated from the tomographic data. The systematic three-dimensional study of pollen grains provides morphological and structural information about taxonomic characters that are essential in palynology. Such studies have a direct impact on disciplines such as forestry, agriculture, horticulture, plant breeding and biodiversity. - Highlights: • The unstained whole pine pollen was visualized by high-resolution laboratory-based HXRM for the first time. • The comparison study of pollen grains by LM, SEM and high-resolution laboratory-based HXRM. • Phase contrast imaging provides significantly higher contrast of the raw images compared to absorption contrast imaging. • Surface and internal structure of the pine pollen including exine, intine and cellular structures are clearly visualized. • 3D volume data of unstained whole pollen grains are acquired and the specific volumes of the different layer are calculated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Visualization of glucagon secretion from pancreatic α cells by bioluminescence video microscopy: Identification of secretion sites in the intercellular contact regions

We have firstly visualized glucagon secretion using a method of video-rate bioluminescence imaging. The fusion protein of proglucagon and Gaussia luciferase (PGCG-GLase) was used as a reporter to detect glucagon secretion and was efficiently expressed in mouse pancreatic α cells (αTC1.6) using a preferred human codon-optimized gene. In the culture medium of the cells expressing PGCG-GLase, luminescence activity determined with a luminometer was increased with low glucose stimulation and KCl-induced depolarization, as observed for glucagon secretion. From immunochemical analyses, PGCG-GLase stably expressed in clonal αTC1.6 cells was correctly processed and released by secretory granules. Luminescence signals of the secreted PGCG-GLase from the stable cells were visualized by video-rate bioluminescence microscopy. The video images showed an increase in glucagon secretion from clustered cells in response to stimulation by KCl. The secretory events were observed frequently at the intercellular contact regions. Thus, the localization and frequency of glucagon secretion might be regulated by cell-cell adhesion. - Highlights: • The fused protein of proglucagon to Gaussia luciferase was used as a reporter. • The fusion protein was highly expressed using a preferred human-codon optimized gene. • Glucagon secretion stimulated by depolarization was determined by luminescence. • Glucagon secretion in α cells was visualized by bioluminescence imaging. • Glucagon secretion sites were localized in the intercellular contact regions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Quantitative visualization of synchronized insulin secretion from 3D-cultured cells

Quantitative visualization of synchronized insulin secretion was performed in an isolated rat pancreatic islet and a spheroid of rat pancreatic beta cell line using a method of video-rate bioluminescence imaging. Video-rate images of insulin secretion from 3D-cultured cells were obtained by expressing the fusion protein of insulin and Gaussia luciferase (Insulin-GLase). A subclonal rat INS-1E cell line stably expressing Insulin-GLase, named iGL, was established and a cluster of iGL cells showed oscillatory insulin secretion that was completely synchronized in response to high glucose. Furthermore, we demonstrated the effect of an antidiabetic drug, glibenclamide, on synchronized insulin secretion from 2D- and 3D-cultured iGL cells. The amount of secreted Insulin-GLase from iGL cells was also determined by a luminometer. Thus, our bioluminescence imaging method could generally be used for investigating protein secretion from living 3D-cultured cells. In addition, iGL cell line would be valuable for evaluating antidiabetic drugs. - Highlights: • An imaging method for protein secretion from 3D-cultured cells was established. • The fused protein of insulin to GLase, Insulin-GLase, was used as a reporter. • Synchronous insulin secretion was visualized in rat islets and spheroidal beta cells. • A rat beta cell line stably expressing Insulin-GLase, named iGL, was established. • Effect of an antidiabetic drug on insulin secretion was visualized in iGL cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Cherenkov Video Imaging Allows for the First Visualization of Radiation Therapy in Real Time

Purpose: To determine whether Cherenkov light imaging can visualize radiation therapy in real time during breast radiation therapy. Methods and Materials: An intensified charge-coupled device (CCD) camera was synchronized to the 3.25-μs radiation pulses of the clinical linear accelerator with the intensifier set × 100. Cherenkov images were acquired continuously (2.8 frames/s) during fractionated whole breast irradiation with each frame an accumulation of 100 radiation pulses (approximately 5 monitor units). Results: The first patient images ever created are used to illustrate that Cherenkov emission can be visualized as a video during conditions typical for breast radiation therapy, even with complex treatment plans, mixed energies, and modulated treatment fields. Images were generated correlating to the superficial dose received by the patient and potentially the location of the resulting skin reactions. Major blood vessels are visible in the image, providing the potential to use these as biological landmarks for improved geometric accuracy. The potential for this system to detect radiation therapy misadministrations, which can result from hardware malfunction or patient positioning setup errors during individual fractions, is shown. Conclusions: Cherenkoscopy is a unique method for visualizing surface dose resulting in real-time quality control. We propose that this system could detect radiation therapy errors in everyday clinical practice at a time when these errors can be corrected to result in improved safety and quality of radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Pore habit of methane hydrate and its evolution in sediment matrix – Laboratory visualization with phase-contrast micro-CT

Describing the pore habit of methane hydrate in sediment matrices is essential for understanding natural distribution of methane hydrate, methane trace (transport and solidification) in the hydrate stability zone, physical properties of hydrate-bearing sediments, and the associated influence on potential gas production. Pore habit visualization in natural media at pore scale even with laboratory synthesized cores has been challenging due to the similar densities of methane hydrate from pore liquid. In this work, we used phase-contrast assisted micro-CT with potassium iodine-doped brine to visualize four phases: sand particles, pore fluid, methane hydrate and methane gas. This study visualizes the pore habit of methane hydrate at various stages including during hydrate formation in excess-gas systems, its evolution after brine injection to replace pore fluid, and hydrate formation in excess-water systems. Hydrate tends to adopt round and smooth surfaces when in contact with water while exhibits relatively angular interfaces when in contact with methane gas. Hydrate formation in excess-gas systems results in a partial cementing and partial mineral-coating pore habit, while hydrate in excess-water systems develops mainly as pore-filling, and locally cementing or mineral-coating where big gas pockets exist at the initial state. Pore liquid replacement from methane gas to brine triggers a shift of hydrate pore habit towards pore-filling. Methane hydrate evolution over time produces bigger hydrate particles but with less contact area with sand particles. The effects of hydrate pore habit become less important as hydrate particle size exceeds the pore size. Additionally, hydrate formation could trap residual methane gas and brine as inclusions.

58 GEOSCIENCES↗
DOE OSTI2015

The neurotoxic effects of N-methyl-N-nitrosourea on the electrophysiological property and visual signal transmission of rat's retina

The neurotoxic effects of N-methyl-N-nitrosourea (MNU) on the inner retinal neurons and related visual signal circuits have not been described in any animal models or human, despite ample morphological evidences about the MNU induced photoreceptor (PR) degeneration. With the helping of MEA (multielectrode array) recording system, we gained the opportunity to systemically explore the neural activities and visual signal pathways of MNU administrated rats. Our MEA research identified remarkable alterations in the electrophysiological properties and firstly provided instructive information about the neurotoxicity of MNU that affects the signal transmission in the inner retina. Moreover, the spatial electrophysiological functions of retina were monitored and found that the focal PRs had different vulnerabilities to the MNU. The MNU-induced PR dysfunction exhibited a distinct spatial- and time-dependent progression. In contrast, the spiking activities of both central and peripheral RGCs altered synchronously in response to the MNU administration. Pharmacological tests suggested that gap junctions played a pivotal role in this homogeneous response of RGCs. SNR analysis of MNU treated retina suggested that the signaling efficiency and fidelity of inner retinal circuits have been ruined by this toxicant, although the microstructure of the inner retina seemed relatively consolidated. The present study provided an appropriate example of MEA investigations on the toxicant induced pathological models and the effects of the pharmacological compounds on neuron activities. The positional MEA information would enrich our knowledge about the pathology of MNU induced RP models, and eventually be instrumental for elucidating the underlying mechanism of human RP. - Highlights: • We systemically explored the neural activities and visual signal pathways of MNU administrated retinas. • The focal photoreceptors had different vulnerabilities to the MNU administration. • Pharmacological tests suggested that gap junctions played a pivotal role in this homogeneous response of RGCs. • The present study provided an appropriate example of MEA investigations on the toxicant induced pathological models. • The MEA information would enrich our knowledge about the pathology of MNU induced RP models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Visualizing double-stranded RNA distribution and dynamics in living cells by dsRNA binding-dependent fluorescence complementation

Double-stranded RNA (dsRNA) is an important type of RNA that plays essential roles in diverse cellular processes in eukaryotic organisms and a hallmark in infections by positive-sense RNA viruses. Currently, no in vivo technology has been developed for visualizing dsRNA in living cells. Here, we report a dsRNA binding-dependent fluorescence complementation (dRBFC) assay that can be used to efficiently monitor dsRNA distribution and dynamics in vivo. The system consists of two dsRNA-binding proteins, which are fused to the N- and C-terminal halves of the yellow fluorescent protein (YFP). Binding of the two fusion proteins to a common dsRNA brings the split YFP halves in close proximity, leading to the reconstitution of the fluorescence-competent structure and restoration of fluorescence. Using this technique, we were able to visualize the distribution and trafficking of the replicative RNA intermediates of positive-sense RNA viruses in living cells. - Highlights: • A live-cell imaging system was developed for visualizing dsRNA in vivo. • It uses dsRNA binding proteins fused with two halves of a fluorescent protein. • Binding to a common dsRNA enables the reporter to become fluorescent. • The system can efficiently monitor viral RNA replication in living cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

InteraChem: Virtual Reality Visualizer for Reactive Interactive Molecular Dynamics

Interactive molecular dynamics in virtual reality (IMD-VR) simulations provide a digital molecular playground for students as an alternative or complement to traditional molecular modeling kits or 2D illustrations. Previous IMD-VR studies have used molecular mechanics to enable simulations of macromolecules such as proteins and nanostructures for the classroom setting with considerable success. Here, we present the InteraChem molecular visualizer, intended for reactive IMD-VR simulation using semiempirical and ab initio methods. InteraChem visualizes not only the molecular geometry but also (1) isosurfaces such as molecular orbitals and electrostatic potentials and (2) two-dimensional graphs of time-varying simulation quantities such as kinetic/potential energy, internal coordinates, and user-applied force. Additionally, InteraChem employs speech recognition to facilitate user interaction and introduces a novel “atom happiness” visualization using emojis to indicate the energetic feasibility of a particular bonding arrangement. Furthermore, we include a set of accompanying exercises that we have used to teach chemical reactivity in small molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Dense, continuous membrane labeling and expansion microscopy visualization of ultrastructure in tissues

Abstract Lipid membranes are key to the nanoscale compartmentalization of biological systems, but fluorescent visualization of them in intact tissues, with nanoscale precision, is challenging to do with high labeling density. Here, we report ultrastructural membrane expansion microscopy (umExM), which combines an innovative membrane label and optimized expansion microscopy protocol, to support dense labeling of membranes in tissues for nanoscale visualization. We validate the high signal-to-background ratio, and uniformity and continuity, of umExM membrane labeling in brain slices, which supports the imaging of membranes and proteins at a resolution of ~60 nm on a confocal microscope. We demonstrate the utility of umExM for the segmentation and tracing of neuronal processes, such as axons, in mouse brain tissue. Combining umExM with optical fluctuation imaging, or iterating the expansion process, yields ~35 nm resolution imaging, pointing towards the potential for electron microscopy resolution visualization of brain membranes on ordinary light microscopes.

Science & Technology - Other Topics↗
DOE OSTI2023

Deep material network via a quilting strategy: visualization for explainability and recursive training for improved accuracy

Recent developments integrating micromechanics and neural networks offer promising paths for rapid predictions of the response of heterogeneous materials with similar accuracy as direct numerical simulations. The deep material network is one such approaches, featuring a multi-layer network and micromechanics building blocks trained on anisotropic linear elastic properties. Once trained, the network acts as a reduced-order model, which can extrapolate the material’s behavior to more general constitutive laws, including nonlinear behaviors, without the need to be retrained. However, current training methods initialize network parameters randomly, incurring inevitable training and calibration errors. Here, we introduce a way to visualize the network parameters as an analogous unit cell and use this visualization to “quilt” patches of shallower networks to initialize deeper networks for a recursive training strategy. The result is an improvement in the accuracy and calibration performance of the network and an intuitive visual representation of the network for better explainability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

rNets: a standalone package to visualize reaction networks

In the study of chemical processes, visualizing reaction networks is pivotal for identifying crucial compounds and transformations. Traditional methods, such as network schematics and reaction path linear plots, often struggle to effectively represent complex reaction networks due to their size and intricate connectivity. Alternatives capable of leading with complexity include graph methods, but they are not user-friendly, lacking simplicity and modularity, which hinders their integration with widely-used research software. This work introduces rNets an innovative tool designed for the efficient visualization of reaction networks with a user-friendly interface, modularity, and seamless integration with existing software packages. The effectiveness of rNets is demonstrated through its application in analyzing three catalytic reactions, showcasing its potential to significantly enhance research both in homogeneous and heterogeneous catalysis fields. This tool not only simplifies the visualization process but also opens new avenues for exploring complex reaction networks in diverse research contexts.

Pablo-García, Sergio↗
DOE OSTI2018

Hierarchical visualization of materials space with graph convolutional neural networks

The combination of high throughput computation and machine learning has led to a new paradigm in materials design by allowing for the direct screening of vast portions of structural, chemical, and property spaces. The use of these powerful techniques leads to the generation of enormous amounts of data, which in turn calls for new techniques to efficiently explore and visualize the materials space to help identify underlying patterns. In this work, we develop a unified framework to hierarchically visualize the compositional and structural similarities between materials in an arbitrary material space with representations learned from different layers of graph convolutional neural networks. We demonstrate the potential for such a visualization approach by showing that patterns emerge automatically that reflect similarities at different scales in three representative classes of materials: perovskites, elemental boron, and general inorganic crystals, covering material spaces of different compositions, structures, and both. For perovskites, elemental similarities are learned that reflects multiple aspects of atom properties. For elemental boron, structural motifs emerge automatically showing characteristic boron local environments. For inorganic crystals, the similarity and stability of local coordination environments are shown combining different center and neighbor atoms. The method could help transition to a data-centered exploration of materials space in automated materials design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Applications of visualization technology in the structural sciences

The structural sciences are undergoing a transformation driven by advancements in visualization technologies that aid researchers in understanding and communicating experimental data from complex molecular systems. New applications of integrative structural biological and biophysical approaches add a wide variety of complementary information from a broad range of scientific disciplines. These approaches extend structural biophysical methodologies to enable research by the incorporation of a variety of data streams and utilization of tools like molecular graphics, virtual reality, and machine learning. To redefine how structural data—particularly from cryo-electron microscopy and x-ray crystallography—are fed forward for scientific exploration and communication, the advances in tools for data visualization and interpretation have been critical. By bringing molecular systems into an interactive three-dimensional space, these novel technologies enhance research workflows, facilitate structure-based drug design, and create engaging educational experiences. Taken together, these visualization innovations are essential tools for advancing the field by making concepts more accessible and compelling.

Eng, Edward T. [New York Structural Biology Center↗
DOE OSTI2021

Toward 3D data visualization using virtual reality tools

Virtual Reality (VR) offers the opportunity to display data, instrumentation, and experimental setups in three dimensions and gives the user the ability to interact with the objects. This technology moves visualization beyond two-dimensional projections on a flat screen with a fixed field of view in which a keyboard or another similar controller is needed to change the view. Advances in both hardware and software for VR make it possible for the non-expert to develop visualization tools for scientific applications both for viewing and for sharing data or diagnostic hardware between users in three dimensions. Furthermore, this manuscript describes application development using two VR software tools, Unity gaming engine and A-frame, for visualizing data and high energy physics targets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Radial velocities of southern visual multiple stars

High-resolution spectra of visual multiple stars were taken in 2008–2009 to detect or confirm spectroscopic subsystems and to determine their orbits. Radial velocities of 93 late-type stars belonging to visual multiple systems were measured by numerical cross-correlation. We provide the individual velocities, the width, and the amplitude of the Gaussians that approximate the correlations. The new information on the multiple systems resulting from these data is discussed. We discovered double-lined binaries in HD 41742B, HD 56593C, and HD 122613AB, confirmed several other known subsystems, and constrained the existence of subsystems in some visual binaries where both components turned out to have similar velocities. The orbits of double-lined subsystems with periods of 148 and 13 days are computed for HD 104471 Aa,Ab and HD 210349 Aa,Ab, respectively. We estimate individual magnitudes and masses of the components in these triple systems and update the outer orbit of HD 104471 AB.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Visualization of phase-space orbit topological boundary using imaging neutral particle analyzer

A newly-developed imaging neutral particle analyzer (INPA) in the DIII-D tokamak interrogates phase space occupied by fast ions on multiple different orbit topologies, including passing, stagnation, trapped and potato orbits. Depending on plasma parameters and beam injection geometries, this new INPA system is capable of visualizing distributions of fast ions on the selected orbit topology and its associated orbit topology boundaries. More importantly, the system is able to directly visualize the pitch angle scattering process in phase space by measuring fast ions that are scattered across the trapped-passing orbit topology boundaries. It also enables visualization of fast ion confined-loss boundaries, which are determined by particle energy, plasma current and magnetic field.The key goal of this new INPA system is to directly measure pitch angle scattering across phase space induced by drift waves and its interaction with Alfv'en eigenmodes, i.e., a key issue towards \redit{a} future fusion power plant.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Flexible visualization of a 3rd party Intrusion Prevention (Security) tool: A use case with the ELK stack

A difficult aspect of cyber security is the ability to achieve automated real time intrusion prevention across various sets of systems. To this extent, several companies are offering comprehensive solutions that leverage an "accuracy of scale" and moving much of the intelligence and detection on the Cloud, relying on an ever-growing set of data and analytics to increase decision accuracy. Often, they provide tools to visualize the decision workflows in attack prevention (as well as tune the algorithm) but those solutions are not always practical as companies see the problem as "global" that is, from a unified Cyber-security standpoint. However, a key to a successful Cyber-security program is transparency and trust: from an experimental team viewpoint, this specifically means having the ability to immediately see what and from where, who has been blocked and being able to inform the community in case of a revoked access without the need for filing a "ticket" (that may eventually be answered) – in other words, rapid response to their user-base is essential but solutions targeting "sub-groups" in an organization are not often available. We have come up with a versatile solution leveraging the ELK stack (Elasticsearch, Logstash, & Kibana) and an IPS (Intrusion Prevention System) based WAF (Web Application Firewall) from Signal Sciences. Signal Science allows the streaming of detailed logs in a Logstash format suitable for custom solutions for visualization. By combining these two tools, we have strengthened our security posture and enabled individual experiments to monitor their own traffic. Specifically, the IPS WAF provides unique data such as country of origin, protocol, response code, source IP, and paths accessed. In this contribution, we will show how we engineered a visualization solution so experiment groups could access a dashboard with predefined graphs but also, where they can create individual customizable dashboards used to display blocked traffic and troubleshoot latency issues. We will discuss the details and procedures for developing and configuring these tools and how it benefits cyber security postures across our scientific based environment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

RCSB Protein Data Bank: improved annotation, search and visualization of membrane protein structures archived in the PDB

Abstract Motivation Membrane proteins are encoded by approximately one fifth of human genes but account for more than half of all US FDA approved drug targets. Thanks to new technological advances, the number of membrane proteins archived in the PDB is growing rapidly. However, automatic identification of membrane proteins or inference of membrane location is not a trivial task. Results We present recent improvements to the RCSB Protein Data Bank web portal (RCSB PDB, rcsb.org) that provide a wealth of new membrane protein annotations integrated from four external resources: OPM, PDBTM, MemProtMD and mpstruc. We have substantially enhanced the presentation of data on membrane proteins. The number of membrane proteins with annotations available on rcsb.org was increased by ∼80%. Users can search for these annotations, explore corresponding tree hierarchies, display membrane segments at the 1D amino acid sequence level, and visualize the predicted location of the membrane layer in 3D. Availability and implementation Annotations, search, tree data and visualization are available at our rcsb.org web portal. Membrane visualization is supported by the open-source Mol* viewer (molstar.org and github.com/molstar/molstar). Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗