SEARCH · Engineering Papers
Results for “VISION”
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.
Deep hybrid model with satellite imagery: How to combine demand modeling and computer vision for travel behavior analysis?
Not provided.
Challenges and Vision for Standardization of Biopolymer Data Sets for Machine Learning
Machine learning (ML) is transforming materials research, yet potential for biopolymer discovery remains constrained by fragmented data and nonstandardized reporting. Biopolymers differ significantly from synthetic polymers, requiring specialized approaches to represent their biosynthetic origins, hierarchical structures, and application-specific metrics. In this Perspective, we identify three core challenges limiting biopolymer representation: information encoding, data quality, and data sharing. We describe the most pressing issues and propose commensurate approaches to address each key challenge. Recommendations include the design and adoption of biopolymer-specific fingerprinting and representation frameworks, development of hybrid human-large language model (LLM) data extraction strategies, and expanding Findable, Accessible, Interoperable, Reusable (FAIR)-compliant repositories. We propose a robust foundation to define interoperable, high-quality data sets that capture the full context of biopolymer materials. Standardized metadata, shared ontologies, and community-driven infrastructure would enable scalable, reproducible workflows and accelerate the ML-driven development of biopolymers.
A U.S. Scientific Community Vision for Sustained Earth Observations of Greenhouse Gases to Support Local to Global Action
Managing carbon stocks in the land, ocean, and atmosphere under changing climate requires a globally‐integrated view of carbon cycle processes at local and regional scales. The growing Earth Observation (EO) record is the backbone of this multi‐scale system, providing local information with discrete coverage from surface measurements and regional information at global scale from satellites. Carbon flux information, anchored by inverse estimates from spaceborne Greenhouse Gas (GHG) concentrations, provides an important top‐down view of carbon emissions and sinks, but currently lacks global continuity at assessment and management scales (<100 km). Partial‐column data can help separate signals in the boundary layer from the overlying atmosphere, providing an opportunity to enhance surface sensitivity and bring flux resolution down from that of column‐integrated data (100–500 km). Based on a workshop held in September 2024, the carbon cycle community envisions a carbon observation system leveraging GHG partial columns in the lower and upper troposphere to weave together information across scales from surface and satellite EO data, and integration of top‐down/bottom‐up analyses to link process understanding to global assessment.
Optogenetic Vision Restoration Using Rhodopsin for Enhanced Sensitivity
Retinal disease is one of the most active areas of gene therapy, with clinical trials ongoing in the United States for five diseases. There are currently no treatments for patients with late-stage disease in which photoreceptors have been lost. Optogenetic gene therapies are in development, but, to date, have suffered from the low light sensitivity of microbial opsins, such as channelrhodopsin and halorhodopsin, and azobenzene-based photoswitches. Several groups have shown that photoreceptive G-protein-coupled receptors (GPCRs) can be expressed heterologously, and photoactivate endogenous G i/o signaling. We hypothesized such a GPCR could increase sensitivity due to endogenous signal amplification. We targeted vertebrate rhodopsin to retinal ON-bipolar cells of blind rd1 mice and observed restoration of: (i) light responses in retinal explants, (ii) visually-evoked potentials in visual cortex in vivo , and (iii) two forms of visually-guided behavior: innate light avoidance and discrimination of temporal light patterns in the context of fear conditioning. Importantly, both the light responses of the retinal explants and the visually-guided behavior occurred reliably at light levels that were two to three orders of magnitude dimmer than required for channelrhodopsin. Thus, gene therapy with native light-gated GPCRs presents a novel approach to impart light sensitivity for visual restoration in a useful range of illumination.
Automatic detection of methane emissions in multispectral satellite imagery using a vision transformer
Curbing methane emissions is among the most effective actions that can be taken to slow down global warming. However, monitoring emissions remains challenging, as detection methods have a limited quantification completeness due to trade-offs that have to be made between coverage, resolution and detection accuracy. Here we show that deep learning can overcome the trade-off in terms of spectral resolution that comes with multi-spectral satellite data, resulting in a methane detection tool with global coverage and high temporal and spatial resolution. We compare our detections with airborne methane measurement campaigns, which suggests that our method can detect methane point sources in Sentinel-2 data down to plumes of 0.01 km 2 , corresponding to 200 to 300 kg CH 4 /h -1 sources. Our model shows an order of magnitude improvement over the state-of-the-art, providing a significant step towards the automated, high resolution detection of methane emissions at a global scale, every few days.
An atomistic vision of the Mass Action Law: Prediction of carbon/oxygen defects in silicon
We introduce an atomistic description of the kinetic Mass Action Law to predict concentrations of defects and complexes. We demonstrate in this paper that this approach accurately predicts carbon/oxygen related defect concentrations in silicon upon annealing. The model requires binding and migration energies of the impurities and complexes, here obtained from density functional theory (DFT) calculations. Vacancy-oxygen complex kinetics are studied as a model system during both isochronal and isothermal annealing. Results are in good agreement with experimental data, confirming the success of the methodology. More importantly, it gives access to the sequence of chain reactions by which oxygen and carbon related complexes are created in silicon. Beside the case of silicon, the understanding of such intricate reactions is a key to develop point defect engineering strategies to control defects and thus semiconductors properties.
Multimodal Synchrotron Approach: Research Needs and Scientific Vision
Abstract not provided.
A million persons, a million dreams: a vision for a national center of radiation epidemiology and biology
Epidemiologic studies of radiation-exposed populations form the basis for human safety standards. Furthermore, they also help shape public health policy and evidence-based health practices by identifying and quantifying health risks of exposure in defined populations. For more than a century, epidemiologists have studied the consequences of radiation exposures, yet the health effects of low levels delivered at a low-dose rate remain equivocal.
PINGU: A vision for neutrino and particle physics at the South Pole
The Precision IceCube Next Generation Upgrade (PINGU) is a proposed low-energy in-fill extension to the IceCube Neutrino Observatory. With detection technology modeled closely on the successful IceCube example, PINGU will provide a 6 Mton effective mass for neutrino detection with an energy threshold of a few GeV. Also, with an unprecedented sample of over 60 000 atmospheric neutrinos per year in this energy range, PINGU will make highly competitive measurements of neutrino oscillation parameters in an energy range over an order of magnitude higher than long-baseline neutrino beam experiments. PINGU will measure the mixing parameters Θ 23 and Δm $2\atop{32}$ , including the octant of Θ 23 for a wide range of values, and determine the neutrino mass ordering at 3σ median significance within five years of operation. PINGU's high precision measurement of the rate of v T appearance will provide essential tests of the unitarity of the 3 ×3 PMNS neutrino mixing matrix. PINGU will also improve the sensitivity of searches for low mass dark matter in the Sun, use neutrino tomography to directly probe the composition of the Earth's core, and improve IceCube's sensitivity to neutrinos from Galactic supernovae. Finally, reoptimization of the PINGU design has permitted substantial reduction in both cost and logistical requirements while delivering performance nearly identical to configurations previously studied.
A unified vision of AI/ML at the Electron-Ion Collider: infrastructure and capabilities
Explore the source record for details and available documents.
A complex carotenoid palette tunes avian color vision.
The brilliantly coloured cone oil droplets of the avian retina function as long-pass cut-off filters that tune the spectral sensitivity of the photoreceptors and are hypothesized to enhance colour discrimination and improve colour constancy. Although it has long been known that these droplets are pigmented with carotenoids, their precise composition has remained uncertain owing to the technical challenges of measuring these very small, dense and highly refractile optical organelles. In this study, we integrated results from high-performance liquid chromatography, hyperspectral microscopy and microspectrophotometry to obtain a comprehensive understanding of oil droplet carotenoid pigmentation in the chicken ( Gallus gallus ). We find that each of the four carotenoid-containing droplet types consists of a complex mixture of carotenoids, with a single predominant carotenoid determining the wavelength of the spectral filtering cut-off. Consistent with previous reports, we find that the predominant carotenoid type in the oil droplets of long-wavelength-sensitive, medium-wavelength-sensitive and short-wavelength-sensitive type 2 cones are astaxanthin, zeaxanthin and galloxanthin, respectively. In addition, the oil droplet of the principal member of the double cone contains a mixture of galloxanthin and two hydroxycarotenoids (lutein and zeaxanthin). Short-wavelength-absorbing apocarotenoids are present in all of the droplet types, providing filtering of light in a region of the spectrum where filtering by hydroxy- and ketocarotenoids may be incomplete. Furthermore, birds rely on a complex palette of carotenoid pigments within their cone oil droplets to achieve finely tuned spectral filtering.
Driver Distraction Behavior Detection using a Vision Transformer Model based on Transfer Learning Strategy
Driver distraction behavior is one of the critical factors in traffic accidents. Thus, advanced driver state detection system has become the focus in the field of intelligent vehicle. However, in practical applications, insufficient samples of driving distraction behaviors bring great challenges to training a personalized behavior distraction detection model for a specific driver. To this end, a novel transformer model based on a transfer learning strategy is proposed in this paper to accurately recognize driver distraction behavior. Inspired by the effect of the transformer network in visual recognition, we firstly present a transformer behavior distraction detection system to identify the behavior categories that cause driver distraction. Then, for the specific driving dataset in practical application scenarios, the transfer learning strategy is introduced into the driver distraction detection model to further train the general transformer network. The effectiveness of the transformer based on the transfer learning strategy is validated compared with other traditional deep learning methods. The results show that the proposed detection method has better generalization ability and higher accuracy.
Leveraging Registers in Vision Transformers for Robust Adaptation
Explore the source record for details and available documents.
Advanced Synchrophasor-based Application for Potential Distributed Energy Resources Management: Key Technology, Challenge and Vision
With an increasing number of distributed energy resources (DERs) integrating into the power system, the power grid is becoming more complex and uncertain. Owing to most of DERs are through grid-connected converters to integrate into the power system, the intermittent nature and resource-depended characteristic of the DERs are challenging their monitoring and control. Conventional synchronized measurement devices (SMDs) may be difficult to provide qualified data for DERs management for its accuracy and reporting-rate limitation. The monitoring systems developed basing on SMDs may be insufficient for depicting detailed dynamic manifestations of power systems with a high proportion integration of DERs. This paper shares some advanced synchrophasor-based applications developed in FNET/GridEye, which have a broad prospect for assisting system operator on the control and integration of the DERs.