Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “GANs”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Muscone suppresses inflammatory responses and neuronal damage in a rat model of cervical spondylotic myelopathy by regulating Drp1‐dependent mitochondrial fission

Abstract Cervical spondylotic myelopathy (CSM) is a common cause of disability with few treatments. Aberrant mitochondrial dynamics play a crucial role in the pathogenesis of various neurodegenerative diseases. Thus, regulation of mitochondrial dynamics may offer therapeutic benefit for the treatment of CSM. Muscone, the active ingredient of an odoriferous animal product, exhibits anti‐inflammatory and neuroprotective effects for which the underlying mechanisms remain obscure. We hypothesized that muscone might ameliorate inflammatory responses and neuronal damage by regulating mitochondrial dynamics. To this end, the effects of muscone on a rat model of chronic cervical cord compression, as well as activated BV2 cells and injured neurons, were assessed. The results showed that muscone intervention improved motor function compared with vehicle‐treated rats. Indeed, muscone attenuated pro‐inflammatory cytokine expression, neuronal‐apoptosis indicators in the lesion area, and activation of the nod‐like receptor family pyrin domain‐containing 3 inflammasome, nuclear transcription factor‐κB, and dynamin‐related protein 1 in Iba1‐ and βIII‐tubulin‐labeled cells. Compared with vehicle‐treated rats, compression sites of muscone‐treated animals exhibited elongated mitochondrial morphologies in individual cell types and reduced reactive oxygen species. In vitro results indicated that muscone suppressed microglial activation and neuronal damage by regulating related‐inflammatory or apoptotic molecules. Moreover, muscone inhibited dynamin‐related protein 1 activation in activated BV2 cells and injured neurons, whereby it rescued mitochondrial fragmentation and reactive oxygen species production, which regulate a wide range of inflammatory and apoptotic molecules. Our findings reveal that muscone attenuates neuroinflammation and neuronal damage in rats with chronic cervical cord compression by regulating mitochondrial fission events, suggesting its promise for CSM therapy. image

Zhou, Long‐yun↗
DOE OSTI2025

Environmental factors have a greater influence on photosynthetic capacity in C 4 plants than biochemical subtypes or growth forms

Our understanding of how photosynthetic capacity varies among C 4 species and across growth and measurement conditions remains limited. We collated 1696 CO 2 response curves of net CO 2 assimilation rate (A/C i curves) from C 4 species grown and measured at various environmental conditions and used these data to estimate the apparent maximum carboxylation activity of phosphoenolpyruvate carboxylase (V pmaxA ) and CO 2 -saturated net photosynthetic rate (A max ), two key parameters describing photosynthetic capacity. We examined how V pmaxA and A max vary with species-specific traits, growth and measurement conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

OsHUB2 inhibits function of OsTrx1 in heading date in rice

SUMMARY Heading date is one of the most pivotal agronomic traits for rice ( Oryza sativa ) yield and adaptation. Little is known about the crosstalk between histone ubiquitination and histone methylation in rice heading date regulation. Here, we reported HISTONE MONOUBIQUITINATION 1 ( OsHUB1 ) and OsHUB2 are involved in heading date regulation via the Hd1 and Ehd1 pathway. Loss of OsHUB1 and OsHUB2 function resulted in early heading under long‐day and short‐day photoperiods. The expression of Hd3a , RFT1 , and Ehd1 was induced and the transcript levels of Hd1 , Ghd7 , OsCCA1 , OsGI , OsFKF1 , and OsTOC1 were reduced under long‐day conditions, whereas RFT1 and Ehd1 expression was induced in oshub2 mutants under short‐day conditions. OsHUB2 interacted with OsTrx1 and repressed the gene expression of OsTrx1 . OsHUB2 directly bound to Ehd1 to ubiquitinate H2B at Ehd1 , and H2B ubiquitination levels were reduced in oshub2‐2 and oshub2‐3 mutants. OsTrx1 were highly enriched at Ehd1 , and H3K4me3 levels of Ehd1 were upregulated in oshub2‐2 . Mutations of OsTrx1 in the oshub2‐2 background rescued the early‐heading phenotype of oshub2‐2 . The increases in Ehd1 H3K4me3 levels and transcript levels in oshub2‐2 mutants were attenuated in oshub2‐2 ostrx1‐2 double mutants. Together, our results (i) reveal that OsHUB2 represses the function of OsTrx1 and H3K4me3 levels at Ehd1 and (ii) suggest that OsHUB2‐mediated H2B ubiquitination plays critical roles together with H3K4me3 in rice heading date regulation.

Xu, Zuntao↗
DOE OSTI2022

Citrus FRIGIDA cooperates with its interaction partner dehydrin to regulate drought tolerance

SUMMARY Drought is a major environmental stress that severely affects plant growth and crop productivity. FRIGIDA ( FRI ) is a key regulator of flowering time and drought tolerance in model plants. However, little is known regarding its functions in woody plants, including citrus. Thus, we explored the functional role of the citrus FRI ortholog ( CiFRI ) under drought. Drought treatment induced CiFRI expression. CiFRI overexpression enhanced drought tolerance in transgenic Arabidopsis and citrus, while CiFRI suppression increased drought susceptibility in citrus. Moreover, transcriptomic profiling under drought conditions suggested that CiFRI overexpression altered the expression of numerous genes involved in the stress response, hormone biosynthesis, and signal transduction. Mechanistic studies revealed that citrus dehydrin likely protects CiFRI from stress‐induced degradation, thereby enhancing plant drought tolerance. In addition, a citrus brassinazole‐resistant (BZR) transcription factor family member ( CiBZR1 ) directly binds to the CiFRI promoter to activate its expression under drought conditions. CiBZR1 also enhanced drought tolerance in transgenic Arabidopsis and citrus. These findings further our understanding of the molecular mechanisms underlying the CiFRI ‐mediated drought stress response in citrus.

Xu, Yuan‐Yuan↗
DOE OSTI2023

Optical information transfer through random unknown diffusers using electronic encoding and diffractive decoding

Free-space optical information transfer through diffusive media is critical in many applications, such as biomedical devices and optical communication, but remains challenging due to random, unknown perturbations in the optical path. We demonstrate an optical diffractive decoder with electronic encoding to accurately transfer the optical information of interest, corresponding to, e.g., any arbitrary input object or message, through unknown random phase diffusers along the optical path. This hybrid electronic-optical model, trained using supervised learning, comprises a convolutional neural network-based electronic encoder and successive passive diffractive layers that are jointly optimized. After their joint training using deep learning, our hybrid model can transfer optical information through unknown phase diffusers, demonstrating generalization to new random diffusers never seen before. The resulting electronic-encoder and optical-decoder model was experimentally validated using a 3D-printed diffractive network that axially spans <70λ, where λ = 0.75 mm is the illumination wavelength in the terahertz spectrum, carrying the desired optical information through random unknown diffusers. The presented framework can be physically scaled to operate at different parts of the electromagnetic spectrum, without retraining its components, and would offer low-power and compact solutions for optical information transfer in free space through unknown random diffusive media.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Commissioning of the large-scale lead tungstate scintillating calorimeter

Here, we report on the installation and initial commissioning of a large-scale lead tungstate (PbWO4) scintillating crystal calorimeter developed for high-rate photon detection and precise energy measurement. The calorimeter comprises 1596 high-granularity, high-resolution scintillating crystals optimized for electromagnetic-shower detection over a wide energy range. Scintillation light from each crystal is read out by Hamamatsu R4125 photomultiplier tubes equipped with a custom voltage divider and front-end amplifier to ensure stable gain at high rates. All calorimeter modules were fabricated and characterized using a light-emitting diode–based optical test system prior to installation to verify uniformity and photodetector performance. After installation, the electromagnetic calorimeter was fully integrated into the experiment data acquisition and energy-based trigger systems. The optical response of the modules was equalized using the light-monitoring system, cosmic-ray muons, and photons from Compton-scattering events. Commissioning results demonstrate a reliably calibrated optical response and stable detector performance during the first run. These results validate the calorimeter design and commissioning methodology for large-scale scintillator-based photonic instrumentation.

Analog to digital converters↗
DOE OSTI2020

Precision measurement of the neutral pion lifetime

The explicit breaking of the axial symmetry by quantum fluctuations gives rise to the so-called axial anomaly. This phenomenon is solely responsible for the decay of the neutral pion π0 into two photons (γγ), leading to its unusually short lifetime. Here, we precisely measured the decay width Γ of the π 0 → γγ process. The differential cross sections for π0 photoproduction at forward angles were measured on two targets, carbon-12 and silicon-28, yielding Γ(π 0 → γγ)=7.798±0.056(stat.)±0.109(syst.) eV, where stat. denotes the statistical uncertainty and syst. the systematic uncertainty. We combined the results of this and an earlier experiment to generate a weighted average of Γ(π 0 → γγ)=7.802±0.052(stat.)±0.105(syst.) eV. Our final result has a total uncertainty of 1.50% and confirms the prediction based on the chiral anomaly in quantum chromodynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Lightweight, strong, moldable wood via cell wall engineering as a sustainable structural material

Turning wood into honeycombs Wood is an attractive material for structural applications, but it usually works best as boards or sheets. Xiao et al . have developed a process for engineering hardwood that allows these sheets to be manipulated into complex structures (see the Perspective by Tajvidi and Gardner). The key is to manipulate the cell wall structure by shrinking and blasting open the fibers and vessels by drying and “water-shocking” them. This process creates a window wherein the wood can be manipulated without ripping or tearing. Honeycomb, corrugated, or other complex structures are locked in once the wood dries. —BG

Science & Technology - Other Topics↗
DOE OSTI2022

Topological supramolecular network enabled high-conductivity, stretchable organic bioelectronics

Intrinsically stretchable bioelectronic devices based on soft and conducting organic materials have been regarded as the ideal interface for seamless and biocompatible integration with the human body. A remaining challenge is to combine high mechanical robustness with good electrical conduction, especially when patterned at small feature sizes. We develop a molecular engineering strategy based on a topological supramolecular network, which allows for the decoupling of competing effects from multiple molecular building blocks to meet complex requirements. We obtained simultaneously high conductivity and crack-onset strain in a physiological environment, with direct photopatternability down to the cellular scale. We further collected stable electromyography signals on soft and malleable octopus and performed localized neuromodulation down to single-nucleus precision for controlling organ-specific activities through the delicate brainstem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

FutureTense

Protective vaccines and reliable diagnostics are essential tools for controlling viral diseases. However, the efficacy of these tools can be diminished by mutations in viral genomes. The delay between the emergence of new viral strains and the redesign of vaccines and diagnostics allows for continued viral transmission. Is it possible to address this challenge by computationally predicting viral genome sequence evolution? Can we “future-proof” vaccines and diagnostics by targeting both current and anticipated future sequence variants? While predicting viral evolution is still an unsolved, “grand challenge” problem in biology, the large, and rapidly growing, number of SARS-CoV-2 genome sequences provide an opportunity to quantify the ability of machine learning to predict viral genome sequence evolution. Towards this end, we have developed a simple computational model for predicting viral evolution at the level of individual nucleotides. The key metric for quantifying the per-base, prediction accuracy for viral evolution is the Mann-Whitney U statistic (or, equivalently, the area under the receiver operator curve). Since the Mann-Whitney U statistic is not a differentiable function, existing deep leaning packages (like Pytorch and Keras/TensorFlow) are not useful, as they require that the accuracy metric/objective function be analytically differentiable with respect to the model parameters. To overcome this challenge, we have implemented custom software, “FutureTense”, that can train a machine learning model by maximizing the non-differentiable Mann-Whitney U statistic. This software trains a machine learning model by exploring along the direction of the discrete gradient of the Mann-Whitney U statistic in the model parameter space. Parallel computing and genome sequence-specific optimizations are used to accelerate model training. The resulting machine learning model learns the observed high C->U mutation rates in the SARS-CoV-2 genome (which are potentially induced by host defenses) and provides prediction accuracies that are significantly better than one would expect from random chance. While predicting viral evolution is still quite far from a solved problem, the surprising performance of this simple model gives hope that the accuracy of predicting viral genome evolution can be further increased by more sophisticated approaches.

Gans, Jason↗
DOE OSTI2021

Development of Distributed Microgrid Controllers Using HELICS [SWR-21-94]

Development of Distributed Microgrid Controllers Using HELICS uses HELICS framework develop distributed microgrid controllers (DMCs) for coordinated grid service. Development of Distributed Microgrid Controllers Using HELICS includes thirteen agents, including OpenDSS agent, data manager agent, and eleven DMC agents. Development of Distributed Microgrid Controllers Using HELICS can be used as a standard framework to develop fully distributed control solutions that dispatches simulated DERs in simulation platform.

Wang, Jing↗
DOE OSTI2024

BIORAD

Machine learning prediction of protein-protein binding affinity

Gans, Jason [Los Alamos National Laboratory]↗
DOE OSTI2026

poppler-science

The “Poppler-science” software is a fork of the existing open-source Poppler project (https://poppler.freedesktop.org/) for converting PDF files to text. Modifications to the Poppler source code include (a) per-glyph optical character recognition (for correcting the non-standard font glyph remapping that is common in the scientific literature), (b) inference of text markup for commonly used scientific formatting (like superscripts and subscripts), (c) table and figure recognition, and (d) improved ordering of text output for complex scientific manuscripts (e.g., multi-column text, figure and table captions, etc.).

Gans, Jason [Los Alamos National Laboratory]↗
DOE OSTI2022

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2022 Excel)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗