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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 163 records · Page 9

All sources NASA NTRS DOE OSTI

NASA NTRS2001

Natural abundance deuterium and 18-oxygen effects on the precision of the doubly labeled water method

The doubly labeled water method for measuring total energy expenditure is subject to error from natural variations in the background 2H and 18O in body water. There is disagreement as to whether the variations in background abundances of the two stable isotopes covary and what relative doses of 2H and 18O minimize the impact of variation on the precision of the method. We have performed two studies to investigate the amount and covariance of the background variations. These were a study of urine collected weekly from eight subjects who remained in the Madison, WI locale for 6 wk and frequent urine samples from 14 subjects during round-trip travel to a locale > or = 500 miles from Madison, WI. Background variation in excess of analytical error was detected in six of the eight nontravelers, and covariance was demonstrated in four subjects. Background variation was detected in all 14 travelers, and covariance was demonstrated in 11 subjects. The median slopes of the regression lines of delta2H vs. delta18O were 6 and 7, respectively. Modeling indicated that 2H and 18O doses yielding a 6:1 ratio of final enrichments should minimize this error introduced to the doubly labeled water method.

NASA Discipline Regulatory Physiology↗

NASA NTRS1999

Validation of fluorescent-labeled microspheres for measurement of relative blood flow in severely injured lungs

The aim of the study was to validate a nonradioactive method for relative blood flow measurements in severely injured lungs that avoids labor-intensive tissue processing. The use of fluorescent-labeled microspheres was compared with the standard radiolabeled-microsphere method. In seven sheep, lung injury was established by using oleic acid. Five pairs of radio- and fluorescent-labeled microspheres were injected before and after established lung injury. Across all animals, 175 pieces were selected randomly. The radioactivity of each piece was determined by using a scintillation counter. The fluorescent dye was extracted from each piece with a solvent without digestion or filtering. The fluorescence was determined with an automated fluorescent spectrophotometer. Perfusion was calculated for each piece from both the radioactivity and fluorescence and volume normalized. Correlations between flow determined by the two methods were in the range from 0.987 +/- 0.007 (SD) to 0.991 +/- 0.002 (SD) after 9 days of soaking. Thus the fluorescent microsphere technique is a valuable tool for investigating regional perfusion in severely injured lungs and can replace radioactivity.

Non-NASA Center↗

NASA NTRS2005

Multiple Layer Identification Label Using Stacked Identification Symbols

An automatic identification system and method are provided which employ a machine readable multiple layer label. The label has a plurality of machine readable marking layers stacked one upon another. Each of the marking layers encodes an identification symbol detectable using one or more sensing technologies. The various marking layers may comprise the same marking material or each marking layer may comprise a different medium having characteristics detectable by a different sensing technology. These sensing technologies include x-ray, radar, capacitance, thermal, magnetic and ultrasonic. A complete symbol may be encoded within each marking layer or a symbol may be segmented into fragments which are then divided within a single marking layer or encoded across multiple marking layers.

Harry F Schramm↗

NASA NTRS1982

Protein specific fluorescent microspheres for labelling a protein

Highly fluorescent, stable and biocompatible microspheres are obtained by copolymerizing an acrylic monomer containing a covalent bonding group such as hydroxyl, amine or carboxyl, for example, hydroxyethylmethacrylate, with an addition polymerizable fluorescent comonomer such as dansyl allyl amine. A lectin or antibody is bound to the covalent site to provide cell specificity. When the microspheres are added to a cell suspension the marked microspheres will specifically label a cell membrane by binding to a specific receptor site thereon. The labeled membrane can then be detected by fluorescence of the fluorescent monomer.

Rembaum, Alan↗

NASA NTRS2005

Multiple layer identification label using stacked identification symbols

Schramm, Harry F.↗

NASA NTRS2022

Mars Terrain Segmentation with Less Labels

Planetary rover systems need to perform terrain segmentation to identify drivable areas as well as identify specific types of soil for sample collection. The latest Martian terrain segmentation methods rely on supervised learning which is very data hungry and difficult to train where only a small number of labeled samples are available. Moreover, the semantic classes are defined differently for different applications (e.g., rover traversal vs. geological) and as a result the network has to be trained from scratch each time, which is an inefficient use of resources. This research proposes a semi-supervised learning framework for Mars terrain segmentation where a deep segmentation network trained in an unsupervised manner on unlabeled images is transferred to the task of terrain segmentation trained on few labeled images. The network incorporates a backbone module which is trained using a contrastive loss function and an output atrous convolution module which is trained using a pixel-wise cross-entropy loss function. Evaluation results using the metric of segmentation accuracy show that the proposed method with contrastive pre-training outperforms plain supervised learning by 2%-10%. Moreover, the proposed model is able to achieve a segmentation accuracy of 91.1% using only 161 training images (1% of the original dataset) compared to 81.9% with plain supervised learning.

Wilson, Brian D↗

DOE OSTI2021

Unleashing the Power of Industrial Big Data through Scalable Manual Labeling

Big Data plays a central role in the remarkable results achieved by Machine Learning (ML) and especially Deep Learning (DL) in the recent years. However, the difficulty in obtaining a reasonable amount of labeled samples limits ML/DL application in various domains, including industrial equipment and system monitoring. In this paper the need for methods that turn manual labeling into a scalable process is highlighted. A real world problem is analyzed for which weak supervision methods, successfully employed in other domains, did not produce acceptable results. An alternative approach based on clustering ensembles is described and tested, achieving good performance.

Paes Leao, Bruno↗

DOE OSTI2024

From Simple Labels to Time-Use Integrations: Supporting the Spectrum of Qualitative Travel Behavior Data

In transportation research, applications of travel behavior data collection are context-specific and require different types of qualitative inputs. These inputs can be viewed as spanning a spectrum of user burden and data quality, from simple trip labels to complex time-use surveys. However, each currently active smartphone-based travel diary platform appears to only support one type of qualitative input, and the effort required for customization is unclear. In this paper, we characterize the spectrum by defining four canonical use cases: (i) trip labels, (ii) trip questionnaire, (iii) counterfactual trips, and (iv) time-use surveys. We then outline a mechanism for supporting configurable user inputs on the same underlying smartphone-based sensing mechanism and demonstrate that it can support all the use cases without any code changes. We further demonstrate that the flexible data model that underpins this mechanism can enable real-time monitoring and analysis. Finally, we evaluate per-user data collection and engagement metrics for large-scale deployments of three canonical use cases, spanning 10 programs, 435 users, and 251,041 trips, and a maximum duration of 800 days. Future efforts may support additional use cases through an expanded configuration and provide greater insight into user engagement. We hope that these insights enable the research community to look at qualitative inputs through a new lens and experiment with novel use cases to fill in the spectrum.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

DOE OSTI2025

RINO: Renormalization Group Invariance with No Labels

A common challenge with supervised machine learning (ML) in high energy physics (HEP) is the reliance on simulations for labeled data, which can often mismodel the underlying collision or detector response. To help mitigate this problem of domain shift, we propose RINO (Renormalization Group Invariance with No Labels), a self-supervised learning approach that can instead pretrain models directly on collision data, learning embeddings invariant to renormalization group flow scales. In this work, we pretrain a transformer-based model on jets originating from quantum chromodynamic (QCD) interactions from the JetClass dataset, emulating real QCD-dominated experimental data, and then finetune on the JetNet dataset -- emulating simulations -- for the task of identifying jets originating from top quark decays. RINO demonstrates improved generalization from the JetNet training data to JetClass data compared to supervised training on JetNet from scratch, demonstrating the potential for RINO pretraining on real collision data followed by fine-tuning on small, high-quality MC datasets, to improve the robustness of ML models in HEP.

Hao, Zichun [Caltech] (ORCID:0000000256244907)↗

DOE OSTI2021

D-Band EPR and ENDOR Spectroscopy of 15 N-Labeled Photosystem I

For billions of years, nature has optimized the photosynthetic machinery that converts light energy into chemical energy. Key primary reactions of photosynthesis occur in large membrane protein-cofactor complexes. The light-induced sequential electron transfer reactions occur through a chain of donor/acceptor cofactors embedded in the protein matrix resulting in a long-lived transmembrane charge-separated state. EPR is the method of choice to study electron transfer and the interaction of protein environment with redox-active cofactors. However, the spectra of organic cofactor radicals typically are not fully resolved and severely overlap at conventional X-band EPR. Even at Q-band EPR, this overlap is present and often a serious problem. As a result, there is a large variation of the reported EPR data and limited understanding of electronic structures of several redox-active cofactors. These serious problems can often be overcome by the excellent spectral resolution provided by high-frequency EPR (HF EPR). In this work, we study the electronic structure of the primary electron donor P 700 and the secondary electron acceptor A 1 of Photosystem I (PSI) using 130 GHz (D-band) EPR and Electron-Nuclear-Double-Resonance (ENDOR) spectroscopy. PSI was isotopically labeled with 15 N (I = $\frac{1/2}$) to avoid quadrupolar interactions in the most abundant nitrogen isotope 14 N (I = 1) and simplify the ENDOR spectra. ENDOR spectroscopy is central for determining the hyperfine coupling of nitrogen atoms of the two chlorophyll molecules comprising oxidized P 700 and the involvement of protein nitrogen atoms with reduced A 1 . While HF ENDOR of A 1 - allows identification of two nitrogen atoms, HF ENDOR of P 700 + still does not permit unique assignment of the recorded hyperfine couplings.

15N↗

DOE OSTI2023

Lignin-based carbon quantum dots with high fluorescence performance prepared by supercritical catalysis and solvothermal treatment for tumor-targeted labeling

The poor fluorescence performance of lignin-based carbon quantum dots (L-CQDs) prepared using the bottom-up method has hindered their development. Here, in this study, a two-step strategy was proposed to efficiently enhance the fluorescence properties of L-CQDs. Lignin was first cracked using an ethanol supercritical/noble metal catalyst; then, the L-CQDs were prepared with the cracked lignin fragments as carbon precursors without adding any modified reagents. Compared with the OL-CQDs prepared by the traditional one-pot hydrothermal method, the L-CQDs-1 prepared from CL-1 containing much low molecular weight compounds, and have photoluminescence (increased from 63 to 975) and excellent up-conversion photoluminescence (enhanced by 16.3 to 963), which significantly enhanced by about 15 times and 60 times, respectively. They can emit bright blue fluorescence under both ultraviolet and near-infrared light irradiation owing to a large amount of surface defects caused by the rich compound composition. When L-CQDs-1 were combined with, and quenched by folic acid (FA), the prepared FA@L-CQDs-1 show the ability to target and label tumor cells. This study opens new avenues for the preparation of L-CQDs with high fluorescence performance using lignocellulosic material without heteroatom additives.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Coupling Microdroplet-Based Sample Preparation, Multiplexed Isobaric Labeling, and Nanoflow Peptide Fractionation for Deep Proteome Profiling of the Tissue Microenvironment

There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity in a cell-type-specific manner to better understand and predict the function of complex biological systems such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverage due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (microdroplet processing in one pot for trace samples), multiplexed isobaric labeling, and a nanoflow peptide fractionation approach. The integrated workflow allowed us to maximize proteome coverage of laser-isolated tissue samples containing nanogram levels of proteins. We demonstrated that the deep spatial proteomics platform can quantify more than 5000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 μm2) and differentiate unique protein abundance patterns in pancreas. Furthermore, the use of the microPOTS chip eliminated the requirement for advanced microfabrication capabilities and specialized nanoliter liquid handling equipment, making it more accessible to proteomic laboratories.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Label-free functional analysis of root-associated microbes with dynamic quantitative oblique back-illumination microscopy

The increasing global demand for food, coupled with concerns about the environmental impact of synthetic fertilizers, underscores the urgency of developing sustainable agricultural practices. Nitrogen-fixing bacteria, known as diazotrophs, offer a potential solution by converting atmospheric nitrogen into bioavailable forms, reducing the reliance on synthetic fertilizers. However, a deeper understanding of their interactions with plants and other microbes is needed. In this study, we introduce a recently developed label-free 3D quantitative phase imaging technology called dynamic quantitative oblique back-illumination microscopy (DqOBM) to assess the functional dynamic activity of diazotrophs in vitro and in situ. Our experiments involved three different diazotrophs (Sinorhizobium meliloti, Azotobacter vinelandii, and Rahnella aquatilis) cultured on media with amendments of carbon and nitrogen sources. Over 5 days, we observed increased dynamics in nutrient-amended media. These results suggest that the observed bacterial dynamics correlate with their metabolic activity. Furthermore, we applied qOBM to visualize microbial dynamics within the root cap and elongation zone of Arabidopsis thaliana primary roots. This allowed us to identify distinct areas of microbial infiltration in plant roots without the need for fluorescent markers. Our findings demonstrate that DqOBM can effectively characterize microbial dynamics and provide insights into plant-microbe interactions in situ, offering a valuable tool for advancing our understanding of sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Is the Kok effect a respiratory phenomenon? Metabolic insight using 13 C labeling in Helianthus annuus leaves

The Kok effect is a well-known phenomenon in which the quantum yield of photosynthesis changes abruptly at low light. This effect has often been interpreted as a shift in leaf respiratory metabolism and thus used widely to measure day respiration. However, there is still no formal evidence that the Kok effect has a respiratory origin. Here, both gas exchange and isotopic labeling were carried out on sunflower leaves, using glucose that was 13 C-enriched at specific C-atom positions. Position-specific decarboxylation measurements and NMR analysis of metabolites were used to trace the fate of C-atoms in metabolism. Decarboxylation rates were significant at low light (including above the Kok break point) and increased with decreasing irradiance below 100 µmol photons m –2 s –1 . The variation in several metabolite pools such as malate, fumarate or citrate, and flux calculations suggest the involvement of several decarboxylating pathways in the Kok effect, including the malic enzyme. Our results show that day respiratory CO 2 evolution plays an important role in the Kok effect. Furthermore, the increase in the apparent quantum yield of photosynthesis below the Kok break point is also probably related to malate metabolism, which participates in maintaining photosynthetic linear electron flow.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Interrogating Plant-Microbe Interactions with Chemical Tools: Click Chemistry Reagents for Metabolic Labeling and Activity-Based Probes

Continued expansion of the chemical biology toolbox presents many new and diverse opportunities to interrogate the fundamental molecular mechanisms driving complex plant–microbe interactions. This review will examine metabolic labeling with click chemistry reagents and activity-based probes for investigating the impacts of plant-associated microbes on plant growth, metabolism, and immune responses. While the majority of the studies reviewed here used chemical biology approaches to examine the effects of pathogens on plants, chemical biology will also be invaluable in future efforts to investigate mutualistic associations between beneficial microbes and their plant hosts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Covalent labeling of the Arabidopsis plasma membrane H + ‐ ATPase reveals 3D conformational changes involving the C‐terminal regulatory domain

The plasma membrane proton pump is the primary energy transducing, electrogenic ion pump of the plasma membrane in plants and fungi. Compared to its fungal counterpart, the plant plasma membrane proton pump's regulatory C‐terminal domain (CTD) contains an additional regulatory segment that links multiple sensory pathways regulating plant cell length through phosphorylation and recruitment of regulatory 14‐3‐3 proteins. However, a complete structural model of a plant proton pump is lacking. Here, we performed covalent labeling with mass spectrometric analysis (CL‐MS) on the Arabidopsis pump AHA2 to identify potential interactions between the CTD and the catalytic domains. Our results suggest that autoinhibition in the plant enzyme is much more structurally complex than in the fungal enzyme.

Blackburn, Matthew R. [Department of Biochemistry ↗

DOE OSTI2021

Synergistic Integration of Chemo-Resistive and SERS Sensing for Label-Free Multiplex Gas Detection

Practical sensing applications such as real-time safety alerts and clinical diagnoses require sensor devices to differentiate between various target molecules with high sensitivity and selectivity, yet conventional devices such as oxide-based chemo-resistive sensors and metal-based surface-enhanced Raman spectroscopy (SERS) sensors usually do not satisfy such requirements. In this report a label-free, chemo-resistive/SERS multimodal sensor based on a systematically assembled 3D cross-point multifunctional nanoarchitecture (3D-CMA), which has unusually strong enhancements in both “chemo-resistive” and “SERS” sensing characteristics is introduced. 3D-CMA combines several sensing mechanisms and sensing elements via 3D integration of semiconducting SnO 2 nanowire frameworks and dual-functioning Au metallic nanoparticles. It is shown that the multimodal sensor can successfully estimate mixed-gas compositions selectively and quantitatively at the sub-100 ppm level, even for mixtures of gaseous aromatic compounds (nitrobenzene and toluene) with very similar molecular structures. This is enabled by combined chemo-resistive and SERS multimodal sensing providing complementary information.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Surface Functionalization of Black Phosphorus with Nitrenes: Identification of P=N Bonds by Using Isotopic Labeling

Abstract Surface functionalization of two‐dimensional crystals is a key path to tuning their intrinsic physical and chemical properties. However, synthetic protocols and experimental strategies to directly probe chemical bonding in modified surfaces are scarce. Introduced herein is a mild, surface‐specific protocol for the surface functionalization of few‐layer black phosphorus nanosheets using a family of photolytically generated nitrenes (RN) from the corresponding azides. By embedding spectroscopic tags in the organic backbone, a multitude of characterization techniques are employed to investigate in detail the chemical structure of the modified nanosheets, including vibrational, X‐ray photoelectron, solid state 31 P NMR, and UV‐vis spectroscopy. To directly probe the functional groups introduced on the surface, R fragments were selected such that in conjunction with vibrational spectroscopy, 15 N‐labeling experiments, and DFT methods, diagnostic P=N vibrational modes indicative of iminophosphorane units on the nanosheet surface could be conclusively identified.

Walz Mitra, Kendahl L.↗