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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

A novel analysis method for paired-sample microbial ecology experiments

Many microbial ecology experiments use sequencing data to measure a community s response to an experimental treatment. In a common experimental design, two units, one control and one experimental, are sampled before and after the treatment is applied to the experimental unit. The four resulting samples contain information about the dynamics of organisms that respond to the treatment, but there are no analytical methods designed to extract exactly this type of information from this configuration of samples. Here we present an analytical method specifically designed to visualize and generate hypotheses about microbial community dynamics in experiments that have paired samples and few or no replicates. The method is based on the Poisson lognormal distribution, long studied in macroecology, which we found accurately models the abundance distribution of taxa counts from 16S rRNA surveys. To demonstrate the method s validity and potential, we analyzed an experiment that measured the effect of crude oil on ocean microbial communities in microcosm. Our method identified known oil degraders as well as two clades, Maricurvus and Rhodobacteraceae, that responded to amendment with oil but do not include known oil degraders. Furthermore, our approach is sensitive to organisms that increased in abundance only in the experimental unit but less sensitive to organisms that increased in both control and experimental units, thus mitigating the role of bottle effects .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Protein-ligand binding affinity prediction using multi-instance learning with docking structures

Recent advances in 3D structure-based deep learning approaches demonstrate improved accuracy in predicting protein-ligand binding affinity in drug discovery. These methods complement physics-based computational modeling such as molecular docking for virtual high-throughput screening. Despite recent advances and improved predictive performance, most methods in this category primarily rely on utilizing co-crystal complex structures and experimentally measured binding affinities as both input and output data for model training. Nevertheless, co-crystal complex structures are not readily available and the inaccurate predicted structures from molecular docking can degrade the accuracy of the machine learning methods. We introduce a novel structure-based inference method utilizing multiple molecular docking poses for each complex entity. Our proposed method employs multi-instance learning with an attention network to predict binding affinity from a collection of docking poses. We validate our method using multiple datasets, including PDBbind and compounds targeting the main protease of SARS-CoV-2. The results demonstrate that our method leveraging docking poses is competitive with other state-of-the-art inference models that depend on co-crystal structures. This method offers binding affinity prediction without requiring co-crystal structures, thereby increasing its applicability to protein targets lacking such data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Calibration of AGN Reverberation Distance Measurements

In Yoshii et al., we described a new method for measuring extragalactic distances based on dust reverberation in active galactic nuclei (AGNs), and we validated our new method with Cepheid variable stars. In this Letter, we validate our new method with Type Ia supernovae (SNe Ia) that occurred in two of the AGN host galaxies during our AGN monitoring program: SN 2004bd in NGC 3786 and SN 2008ec in NGC 7469. Their multicolor light curves were observed and analyzed using two widely accepted methods for measuring SN distances, and the distance moduli derived are μ=33.47±0.15 for SN 2004bd and 33.83 ± 0.07 for SN 2008ec. These results are used to obtain independently the distance measurement calibration factor, g. The g value obtained from the SN Ia discussed in this Letter is g{sub SN}=10.61±0.50, which matches, within the range of 1σ uncertainty, g{sub DUST}=10.60, previously calculated ab initio in Yoshii et al. Having validated our new method for measuring extragalactic distances, we use our new method to calibrate reverberation distances derived from variations of Hβ emission in the AGN broad-line region, extending the Hubble diagram to z≈0.3 where distinguishing between cosmologies is becoming possible.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Fast Algorithm for Evaluating Critical Current of High-Temperature Superconducting Pancake Coil

Second-generation (2G) high-temperature superconducting (HTS) tapes are now capable of carrying very high transport current and promising for a wide range of applications. The critical current of HTS coils is important for applications, such as superconducting electric machines, superconducting magnetic energy storage, and superconducting magnets. Therefore, precisely and quickly calculating critical current of HTS coils is very important for designing HTS devices. This paper provides a fast algorithm for evaluating critical current of HTS pancake coil. The fast algorithm is realized through a stationary model, which is based on finite element method (FEM) software. The stationary model means that the model is solved by stationary study instead of time-dependent study. To validate this method, a pancake HTS coil was wound and its critical current was measured. Meanwhile, an axial symmetric stationary model was built according to the geometry of the measured HTS coil. By comparing measured and calculated results, the effectiveness of the stationary model was demonstrated. Moreover, the stationary model is compared with H formulation model. The calculated results by the two models are nearly the same. However, by using stationary calculation, the stationary model can remarkably speed up the computational process. Due to the advantage of calculating speed, the stationary model can be used to characterize and design large-scale HTS applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Assessing time-of-flight signal-to-noise ratio gains within the myocardium and subsequent reductions in administered activity in cardiac PET studies

Background: Time-of-flight (TOF) is known to increase signal-to-noise ratio (SNR) and facilitate reductions in administered activity. Established measures of SNR gain are derived from areas of uniform uptake, which is not applicable to the heterogeneous uptake in cardiac PET images using fluoro-deoxyglucose (FDG). This study aimed to develop a technique to quantify SNR gains within the myocardium due to TOF. Methods: Reference TOF SNR gains were measured in 88 FDG oncology patients. Phantom data were used to translate reference SNR gains and validate a method of quantifying SNR gains within the myocardium from parametric images produced from multiple replicate images. This technique was applied to 13 FDG cardiac viability patients. Results: Reference TOF SNR gains of +23% ± 8.5% were measured in oncology patients. Measurements of SNR gain from the phantom data were in agreement and showed the parametric image technique to be sufficiently robust. SNR gains within the myocardium in the viability patients were +21% ± 2.8%. Conclusion: A method to quantify SNR gains from TOF within the myocardium has been developed and evaluated. SNR gains within the myocardium are comparable to those observed by established methods. This allows guidance for protocol optimization for TOF systems in cardiac PET.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

A rapid and efficient newly established method to detect COL1A1-PDGFB gene fusion in dermatofibrosarcoma protuberans

Highlights: Black-Right-Pointing-Pointer We developed new method to rapidly identify COL1A1-PDGFB fusion in DFSP. Black-Right-Pointing-Pointer New PCR method using a single primer pair detected COL1A1-PDGFB fusion in DFSP. Black-Right-Pointing-Pointer This is the first report of DFSP with a novel COL1A1 breakpoint in exon 5. -- Abstract: The detection of fusion transcripts of the collagen type 1{alpha}1 (COL1A1) and platelet-derived growth factor-BB (PDGFB) genes by genetic analysis has recognized as a reliable and valuable molecular tool for the diagnosis of dermatofibrosarcoma protuberans (DFSP). To detect the COL1A1-PDGFB fusion, almost previous reports performed reverse transcription polymerase chain reaction (RT-PCR) using multiplex forward primers from COL1A1. However, it has possible technical difficulties with respect to the handling of multiple primers and reagents in the procedure. The objective of this study is to establish a rapid, easy, and efficient one-step method of PCR using only a single primer pair to detect the fusion transcripts of the COL1A1 and PDGFB in DFSP. To validate new method, we compared the results of RT-PCR in five patients of DFSP between the previous method using multiplex primers and our established one-step RT-PCR using a single primer pair. In all cases of DFSP, the COL1A1-PDGFB fusion was detected by both previous method and newly established one-step PCR. Importantly, we detected a novel COL1A1 breakpoint in exon 5. The newly developed method is valuable to rapidly identify COL1A1-PDGFB fusion transcripts in DFSP.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Three-dimensional traction microscopy accounting for cell-induced matrix degradation

Tractions exerted by cells on the extracellular matrix (ECM) are critical in many important physiological and pathological processes such as embryonic morphogenesis, wound healing, and cancer metastasis. Three-dimensional Traction Microscopy (3DTM) is a tool to quantify cellular tractions by first measuring the displacement field in the ECM in response to these tractions, and then using this measurement to infer tractions. Most applications of 3DTM have assumed that the ECM has spatially-uniform mechanical properties, but cells secrete enzymes that can locally degrade the ECM. In this work, a novel computational method is developed to quantify both cellular tractions and ECM degradation. In particular, the ECM is modeled as a hyperelastic, Neo-Hookean solid, whose material parameters are corrupted by a single degradation parameter. The feasibility of determining both the traction and the degradation parameter is first demonstrated by showing the existence and uniqueness of the solution. An inverse problem is then formulated to determine the nodal values of the traction vector and the degradation parameter, with the objective of minimizing the difference between a predicted and measured displacement field, under the constraint that the predicted displacement field satisfies the equation of equilibrium. The inverse problem is solved by means of a gradient-based optimization approach, and the gradient is computed efficiently using appropriately derived adjoint fields. The computational method is validated in-silico using a geometrically realistic neuronal cell model and synthetic traction and degradation fields. It is found that the method accurately recovers both the traction and degradation fields. Moreover, it is found that neglecting ECM degradation can yield significant errors in traction measurements. Finally, our method can extend the range of context where tractions can be appropriately measured.

42 ENGINEERING↗
DOE OSTI2019

Arctic Vegetation Mapping Using Unsupervised Training Datasets and Convolutional Neural Networks

Land cover datasets are essential for modeling and analysis of Arctic ecosystem structure and function and for understanding land–atmosphere interactions at high spatial resolutions. However, most Arctic land cover products are generated at a coarse resolution, often limited due to cloud cover, polar darkness, and poor availability of high-resolution imagery. A multi-sensor remote sensing-based deep learning approach was developed for generating high-resolution (5 m) vegetation maps for the western Alaskan Arctic on the Seward Peninsula, Alaska. The fusion of hyperspectral, multispectral, and terrain datasets was performed using unsupervised and supervised classification techniques over a ~343 km 2 area, and a high-resolution (5 m) vegetation classification map was generated. An unsupervised technique was developed to classify high-dimensional remote sensing datasets into cohesive clusters. We employed a quantitative method to add supervision to the unlabeled clusters, producing a fully labeled vegetation map. We then developed convolutional neural networks (CNNs) using the multi-sensor fusion datasets to map vegetation distributions using the original classes and the classes produced by the unsupervised classification method. To validate the resulting CNN maps, vegetation observations were collected at 30 field plots during the summer of 2016, and the resulting vegetation products developed were evaluated against them for accuracy. Our analysis indicates the CNN models based on the labels produced by the unsupervised classification method provided the most accurate mapping of vegetation types, increasing the validation score (i.e., precision) from 0.53 to 0.83 when evaluated against field vegetation observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Revised single-spacecraft method for determining wave vector k and resolving space-time ambiguity

A practical method is proposed for determining the wave vector of waves from single-spacecraft measurements. This wave vector knowledge can then be used to remove the space-time ambiguity produced by frequency Doppler shift associated with spacecraft motion. The method involves applying the Wiener-Khinchin theorem to cross correlations of the current and magnetic field oscillations and to autocorrelations of the magnetic field oscillations. Lastly, the method requires that each wave frequency component map to a unique wave vector, a condition presumed true in many spacecraft measurement situations. Examples validating the method are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Accurate and Sensitive Analytical Strategy for the Determination of Antimony: Hydrogen Assisted T-Shaped Slotted Quartz Tube-Atom Trap-Flame Atomic Absorption Spectrometry

Antimony is known to have some adverse health effects on human health. Flame atomic absorption spectrometry (FAAS) is a widely used instrumental for the determination of antimony and other metals. However, it lacks the sensitivity to determine these metals at trace levels. This study was aimed at overcoming this setback by using hydrogen assisted T-shaped slotted quartz tube technique to preconcentrate and determine antimony by FAAS. All the system parameters were optimized to enhance the detection power of the system. Under the optimum experimental conditions, the limits of detection and quantification were found to be 0.75 and 2.49 µg L{sup −1}, respectively with R{sup 2} value of 0.9999. Accuracy of the developed method was validated by experimental results agreeing to the certified value of a standard reference material. Recovery studies were also carried out to determine the method’s applicability to tap and mineral water samples, and the results obtained were appreciable.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

An automated target species selection method for dynamic adaptive chemistry simulations

The relative importance index (RII) approach for determining appropriate target species for dynamic adaptive chemistry (DAC) simulations using the directed relation graph with error propagation (DRGEP) method is developed. The adequacy and effectiveness of this RII method is validated for two fuels: n-heptane and isopentanol, representatives of a ground transportation fuel component and bio-alcohol, respectively. The conventional method of DRGEP target species selection involves picking an unchanging (static) set of target species based on the combustion processes of interest; however, these static target species may not remain important throughout the entire combustion simulation, adversely affecting the accuracy of the method. In particular, this behavior may significantly reduce the accuracy of the DRGEP-based DAC approach in complex multidimensional simulations where the encountered combustion conditions cannot be known a priori with high certainty. Moreover, testing multiple sets of static target species to ensure the accuracy of the method is generally computationally prohibitive. Instead, the RII method determines appropriate DRGEP target species solely from the local thermo-chemical state of the simulation, ensuring that accuracy will be maintained. Further, the RII method reduces the expertise required of users to select DRGEP target species sets appropriate to the combustion phenomena under consideration. Constant volume autoignition simulations run over a wide range of initial conditions using detailed reaction mechanisms for n-heptane and isopentanol show that the RII method is able to maintain accuracy even when traditional static target species sets fail, and are even more accurate than expert-selected target species sets. Additionally, the accuracy and efficiency of the RII method are compared to those of static target species sets in single-cell engine simulations under homogeneous charge compression ignition conditions. For simulations using more stringent DRGEP thresholds, the RII method performs similarly to that of the static target species sets. With a larger DRGEP threshold, the RII method is significantly more accurate than the static target species sets without imposing significant computational overhead. Moreover, the applicability of the RII method to a DRG-based DAC scheme is discussed.

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

Extended real-time voltage instability identification method based on synchronized phasor measurements

This paper presents an extended adaptive approach designed to accurately estimate the Thévenin equivalent parameters using phasor measurements at a given bus for measurements lying in any of four quadrants of the PQ-plane. The improvement is achieved by using a new condition to properly update the estimated parameters after an initial guess. Based on an adaptive philosophy, the proposed approach can correctly account for the intrinsic nonlinearities of a power system, can provide a real-time estimation of Thévenin parameters, and does not require network topology knowledge. The method is validated using the Kundur 2-area system, showing estimation improvements compared to the current adaptive approach and the classical recursive least-squares method. The proposed approach is able to estimate both sides of the system with respect to the measurement bus. In addition, a data-driven voltage stability index is developed. To illustrate the performance of the proposed approach in a larger power system, a voltage stability assessment is carried out on the IEEE 39-bus system, considering the action of overexcitation limiters of generators and nonlinear loads. The proposed approach is suitable for applications that require an accurate Thévenin equivalent estimation in real-time, such as for voltage stability assessment. The new approach provides a reliable tool for the system operators to make proper and timely decisions.

42 ENGINEERING↗
DOE OSTI2015

Photoacoustic tomography based on the Green's function retrieval with ultrasound interferometry for sample partially behind an acoustically scattering layer

Acoustically inhomogeneous mediums with multiple scattering are often the nightmare of photoacoustic tomography. In order to break this limitation, a photoacoustic tomography scheme combining ultrasound interferometry and time reversal is proposed to achieve images in acoustically scattering medium. An ultrasound interferometry is developed to determine the unknown Green's function of strong scattering tissue. Using the determined Greens' function, a time-reversal process is carried out to restore images behind an acoustically inhomogeneous layer from the scattering photoacoustic signals. This method effectively decreases the false contrast, noise, and position deviation of images induced by the multiple scattering. Phantom experiment is carried out to validate the method. Therefore, the proposed method could have potential value in extending the biomedical applications of photoacoustic tomography in acoustically inhomogeneous tissue.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Nonadiabatic transition path sampling

Fewest-switches surface hopping (FSSH) is combined with transition path sampling (TPS) to produce a new method called nonadiabatic path sampling (NAPS). The NAPS method is validated on a model electron transfer system coupled to a Langevin bath. Numerically exact rate constants are computed using the reactive flux (RF) method over a broad range of solvent frictions that span from the energy diffusion (low friction) regime to the spatial diffusion (high friction) regime. The NAPS method is shown to quantitatively reproduce the RF benchmark rate constants over the full range of solvent friction. Integrating FSSH within the TPS framework expands the applicability of both approaches and creates a new method that will be helpful in determining detailed mechanisms for nonadiabatic reactions in the condensed-phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Fracture Toughness of Advanced Structural Ceramics: Applying ASTM C1421

The three methods of determining the quasi-static Mode I fracture toughness (K Ic ) (surface crack in flexure – SC, single-edge precracked beam – PB, and chevron notched beam – VB) found in ASTM C1421 were applied to a variety of advanced ceramic materials. All three methods produced valid and comparable KIc values for the Al 2 O 3 , SiC, Si 3 N 4 and SiAlON ceramics examined. However, not all methods could successfully be applied to B 4 C, ZrO 2 and WC ceramics due to a variety of material factors. The coarse-grained microstructure of one B 4 C hindered the ability to observe and measure the precracks generated in the SC and PB methods while the transformation toughening in the ZrO 2 prevented the formation of the SC and PB precracks and thus made it impossible to use either method on this ceramic. The high strength and elastic modulus of the WC made it impossible to achieve stable crack growth using the VB method because the specimen stored a tremendous amount of energy prior to fracture. Even though these methods have passed the rigors of the standardization process there are still some issues to be resolved when the methods are applied to certain classes of ceramics. We recommend that at least two of these methods be employed to determine the K Ic , especially when a new or unfamiliar ceramic is being evaluated.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Computer-aided detection of renal calculi from noncontrast CT images using TV-flow and MSER features

Purpose: Renal calculi are common extracolonic incidental findings on computed tomographic colonography (CTC). This work aims to develop a fully automated computer-aided diagnosis system to accurately detect renal calculi on CTC images. Methods: The authors developed a total variation (TV) flow method to reduce image noise within the kidneys while maintaining the characteristic appearance of renal calculi. Maximally stable extremal region (MSER) features were then calculated to robustly identify calculi candidates. Finally, the authors computed texture and shape features that were imported to support vector machines for calculus classification. The method was validated on a dataset of 192 patients and compared to a baseline approach that detects calculi by thresholding. The authors also compared their method with the detection approaches using anisotropic diffusion and nonsmoothing. Results: At a false positive rate of 8 per patient, the sensitivities of the new method and the baseline thresholding approach were 69% and 35% (p < 1e − 3) on all calculi from 1 to 433 mm{sup 3} in the testing dataset. The sensitivities of the detection methods using anisotropic diffusion and nonsmoothing were 36% and 0%, respectively. The sensitivity of the new method increased to 90% if only larger and more clinically relevant calculi were considered. Conclusions: Experimental results demonstrated that TV-flow and MSER features are efficient means to robustly and accurately detect renal calculi on low-dose, high noise CTC images. Thus, the proposed method can potentially improve diagnosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-602: Patient-Specific Online Dose Verification Based On Transmission Detector Measurements

Purpose: Intensity modulated radiotherapy requires a comprehensive quality assurance program in general and ideally independent verification of dose delivery. Since conventional 2D detector arrays allow only pre-treatment verification, there is a debate concerning the need of online dose verification. This study presents the clinical performance, including dosimetric plan verification in 2D as well as in 3D and the error detection abilities of a new transmission detector (TD) for online dose verification of 6MV photon beam. Methods: To validate the dosimetric performance of the new device, dose reconstruction based on TD measurements were compared to a conventional pre-treatment verification method (reference) and treatment planning system (TPS) for 18 IMRT and VMAT treatment plans. Furthermore, dose reconstruction inside the patient based on TD read-out was evaluated by comparing various dose volume indices and 3D gamma evaluations against independent dose computation and TPS. To investigate the sensitivity of the new device, different types of systematic and random errors for leaf positions and linac output were introduced in IMRT treatment sequences. Results: The 2D gamma index evaluation of transmission detector based dose reconstruction showed an excellent agreement for all IMRT and VMAT plans compared to reference measurements (99.3±1.2)% and TPS (99.1±0.7)%. Good agreement was also obtained for 3D dose reconstruction based on TD read-out compared to dose computation (mean gamma value of PTV = 0.27±0.04). Only a minimal dose underestimation within the target volume was observed when analyzing DVH indices (<1%). Positional errors in leaf banks larger than 1mm and errors in linac output larger than 2% could clearly identified with the TD. Conclusion: Since 2D and 3D evaluations for all IMRT and VMAT treatment plans were in excellent agreement with reference measurements and dose computation, the new TD is suitable to qualify for routine treatment plan verification. Funding Support, Disclosures, and Conflict of Interest: COIs: Frank Lohr: Elekta: research grant, travel grants, teaching honoraria IBA: research grant, travel grants, teaching honoraria, advisory board C-Rad: board honoraria, travel grants Frederik Wenz: Elekta: research grant, teaching honoraria, consultant, advisory board Zeiss: research grant, teaching honoraria, patent Hansjoerg Wertz: Elekta: research grant, teaching honoraria IBA: research grant.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

A geometric framework for momentum-based optimizers for low-rank training

Low-rank pre-training and fine-tuning have recently emerged as promising techniques for reducing the computational and storage costs of large neural networks. Training low-rank parameterizations typically relies on conventional optimizers such as heavy ball momentum methods or Adam. In this work, we identify and analyze potential difficulties that these training methods encounter when used to train low-rank parameterizations of weights. In particular, we show that classical momentum methods can struggle to converge to a local optimum due to the geometry of the underlying optimization landscape. To address this, we introduce novel training strategies derived from dynamical low-rank approximation, which explicitly account for the underlying geometric structure. Our approach leverages and combines tools from dynamical low-rank approximation and momentum-based optimization to design optimizers that respect the intrinsic geometry of the parameter space. We validate our methods through numerical experiments, demonstrating faster convergence, and stronger validation metrics at given parameter budgets.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗