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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Multiple signaling systems target a core set of transition metal homeostasis genes using similar binding motifs

Bacterial response to metals can require complex regulation. We report an overlapping regulation for copper and zinc resistance genes in the denitrifying bacterium, Pseudomonas stutzeri RCH2, by three two-component regulatory proteins CopR1, CopR2 and CzcR. We conducted genome-wide evaluations to identify gene targets of two paralogous regulators, CopR1 and CopR2, annotated for copper signaling, and compared the results with the gene targets for CzcR, implicated in zinc signaling. We discovered that the CopRs and CzcR have largely common targets, and crossregulate a core set of P. stutzeri copper and zinc responsive genes. We established that this crossregulation is enabled by a conserved binding motif in the upstream regulatory regions of the target genes. The crossregulation is physiologically relevant as these regulators synergistically and antagonistically target multicopper oxidases, metal efflux and sequestration systems. CopR1 and CopR2 upregulate two cop operons encoding copper tolerance genes, while all three regulators downregulate a putative copper chaperone, Psest_1595. CzcR also upregulated the oprD gene and the CzcIABC Zn 2+ efflux system, while CopR1 and CopR2 downregulated these genes. Lastly, our study suggests that crossregulation of copper and zinc homeostasis can be advantageous, and in P. stutzeri this is enabled by shared binding motifs for multiple response regulators.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2003

Visual and Vestibular Determinants of Perceived Eye-Level

Both gravitational and optical sources of stimulation combine to determine the perceived elevations of visual targets. The ways in which these sources of stimulation combine with one another in operational aeronautical environments are critical for pilots to make accurate judgments of the relative altitudes of other aircraft and of their own altitude relative to the terrain. In a recent study, my colleagues and I required eighteen observers to set visual targets at their apparent horizon while they experienced various levels of G(sub z) in the human centrifuge at NASA-Ames Research Center. The targets were viewed in darkness and also against specific background optical arrays that were oriented at various angles with respect to the vertical; target settings were lowered as Gz was increased; this effect was reduced when the background optical array was visible. Also, target settings were displaced in the direction that the background optical array was pitched. Our results were attributed to the combined influences of otolith-oculomotor mechanisms that underlie the elevator illusion and visual-oculomotor mechanisms (optostatic responses) that underlie the perceptual effects of viewing pitched optical arrays that comprise the background. In this paper, I present a mathematical model that describes the independent and combined effects of G(sub z) intensity and the orientation and structure of background optical arrays; the model predicts quantitative deviations from normal accurate perceptions of target localization under a variety of conditions. Our earlier experimental results and the mathematical model are described in some detail, and the effects of viewing specific optical arrays under various gravitational-inertial conditions encountered in aeronautical environments are discussed.

Cohen, Malcolm Martin↗
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 OSTI2023

Exploring for Superhot Geothermal Targets in Magmatic Settings: 2022 Field Campaign at Newberry Volcano

This paper presents preliminary results from a subset of work carried out as part of a multinational research project entitled DErisking Exploration for multiple geothermal Plays in magmatic ENvironments (DEEPEN), supported by the U.S. Department of Energy (DOE) and Geothermica, a joint effort by EU member states and associated countries. The DEEPEN project will develop a customized approach to exploration for supercritical and superhot geothermal plays in magmatic systems, which will be applied to two demonstration sites. This paper summarizes field activities carried out at the U.S. demonstration site, Newberry Volcano in central Oregon. The objective of this work effort is to refine the subsurface model of Newberry Volcano, with special focus on deeper zones including the magmatic plumbing system and other key geologic elements. New data collection included gravity and wideband magnetotelluric (MT) surveys, as well as reinstallation of a seismic network. The National Renewable Energy Laboratory (NREL) and Enthalpion Energy LLC (Enthalpion) worked with the Deschutes National Forest Fort Rock District to use a low ground disturbance method of MT deployment to collect MT data inside the caldera and other restricted areas inside the National Volcanic Monument. This opened these areas to geophysical exploration for the first time in decades. Sites along and adjacent to the south rim of the volcano constituted the primary survey objectives. A team from Lawrence Berkeley National Laboratory (LBNL), the U.S. Geological Survey (USGS), and AltaRock also began the process of reinstalling the seismic network from the AltaRock enhanced geothermal system (EGS) demonstration in anticipation of further development activities at the site. The data ingestion, reduction, and analysis phase of the project is ongoing. We are currently processing the MT and gravity data and are developing a new, highly GPU-accelerated, 3D joint MT and gravity inversion to better localize the south rim/south flank conductive target and better understand its relationship to deep heat, fluid sources, and surface extrusive features. Joint inversions, which have not yet been undertaken at Newberry, will allow us to obtain constraints on the geologic model that cannot be determined from each method in isolation, improving our ability to image key geologic features at depth.

geophysics↗
DOE OSTI2024

UNDERSTANDING THE SEMI-PROBABILISTIC APPROACHES IN STRUCTURAL RELIABILITY USED TO SET DESIGN RELIABILITY TARGETS FOR GRAPHITE COMPONENTS USING ASME BPVC METHODS

Graphite is a quasi-brittle material, resulting in random variability in tensile strength distributions. To account for the random variability in strength, HHA-3000 of the ASME BPVC provides two semi-probabilistic methods for qualifying nuclear graphite components in the design stage, the simplified and full assessments. The full and simplified assessments apply statistical methods to engineering-based design problems. This is often referred to as reliability-based design. Reliability-based design (RBD) is a method to develop reliable designs by accounting for uncertainties and result in small chances of failure when also considering safety factors. RBDs provide reliability targets using semi-probabilistic approaches. RBD is implemented in ASME BPVC HHA-3000 for nuclear graphite components, but is not specific to that application. There has been much confusion around the methods implemented in ASME BPVC HHA-3000 for qualifying nuclear graphite components. To address the confusion, this paper takes a hierarchical approach. First, the general RBD framework is presented. Then, the semi-probabilistic methods and the underlying assumptions implemented in the assessments are presented. The semi-probabilistic methods are separated from the engineering modifications that have been made to the assessments. After building the framework and underlying assumptions, the specific methods in the full and simplified assessments are explained in three steps: inputs, methods, outputs. The methods are applied to an H-451 reflector block. Tensile strength properties for other graphite grades are provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Exploring for Superhot Geothermal Targets in Magmatic Settings: Developing a Methodology

This paper presents preliminary results from a subset of work carried out as part of a multinational research project entitled DErisking Exploration for multiple geothermal Plays in magmatic ENvironments (DEEPEN). One objective of DEEPEN is to develop a customized approach to exploration for superhot geothermal plays in magmatic systems. This paper summarizes key geologic components, risk factors, and exploration methods for geothermal plays in magmatic settings based on a review and comparative analysis of international training sites. As part of a Play Fairway Analysis (PFA) approach to exploring for multiple play types in a single magmatic system, training data were compiled and weights assigned to various evidence layers. Two different approaches for weighting exploration datasets are described in this paper - one based on expert opinions and the other using statistical learning. Weights produced by both approaches will be input into a 3D PFA workflow that combines multiple exploration datasets to generate 3D geothermal favorability models, which will be applied to two international demonstration sites.

GEOTHERMAL ENERGY↗
NASA NTRS2001

Effects of gravitational and optical stimulation on the perception of target elevation

To examine the combined effects of gravitational and optical stimulation on perceived target elevation, we independently altered gravitational-inertial force and both the orientation and the structure of a background visual array. While being exposed to 1.0, 1.5, or 2.0 Gz in the human centrifuge at NASA Ames Research Center, observers attempted to set a target to the apparent horizon. The target was viewed against the far wall of a box that was pitched at various angles. The box was brightly illuminated, had only its interior edges dimly illuminated, or was kept dark. Observers lowered their target settings as Gz was increased; this effect was weakened when the box was illuminated. Also, when the box was visible, settings were displaced in the same direction as that in which the box was pitched. We attribute our results to the combined influence of otolith-oculomotor mechanisms that underlie the elevator illusion and visual-oculomotor mechanisms (optostatic responses) that underlie the perceptual effects of viewing pitched visual arrays.

NASA Discipline Neuroscience↗
DOE OSTI2014

On the validity of density overrides for VMAT lung SBRT planning

Purpose: Modeling dose to a moving target in lung is a very difficult task. Current approaches to planning lung stereotactic body radiotherapy (SBRT) generally calculate dose on either free breathing or average computed tomography (CT) scans, which do not always accurately predict dose to parts of the target volume not occupied by tumor on the planning scan. In this work, the authors look at using density overrides of the target volumes to more accurately predict dose for lung SBRT using the analytic anisotropic algorithm (AAA). Methods: Volumetric modulated arc therapy plans were created on free breathing scans (FBP), time average scans (AVGP), free breathing scans with the internal target volume overridden to tumor density (ITVP), free breathing scans with the planning target volume overridden to tumor density (PTVP), and free breathing scan using a hybrid scheme with the internal target volume set to tumor density and the planning target volume minus the internal target volume set to a density intermediate between lung and tumor (HP) for the case of a 4D motion phantom and five patient cases. Radiochromic film measurements were made for the phantom plans, with gamma analysis used to compare the planned to delivered dose. The patient plans were recalculated on each of the phases of a 4DCT to evaluate tumor coverage and conformity index (CI). A modified modulation complexity score (MCSv) and average open area per control point (AA) metrics were used to evaluate multileaf collimator (MLC) modulation for each of the plans. Results: The HP plans showed significantly higher gamma passing rates (p < 0.05) than the FBP, AVGP, and ITVP for criteria of 2 mm/2% and 1 mm/1%. No significant correlation was observed between gamma values and AA or MCSv. The tumor volume was covered by the prescription dose on all phases of the 4DCT for all patient plans. The PTVP and HP yielded lower mean CI than the other plans for all five patients, with three of the cases showing statistically significant differences (p < 0.05). No meaningful correlation was observed between the mean CI and AA or MCSv. Conclusions: These measurements suggest that the HP planning method may provide more accurate dose modeling and decreased normal lung irradiation for lung SBRT compared to the commonly used FBP and AVG planning methods when used with the AAA. The HP method does not appear to have a strong relationship with MLC modulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Exploring the speed and performance of molecular replacement with AMPLE using QUARK ab initio protein models

Two ab initio modelling programs solve complementary sets of targets, enhancing the success of AMPLE with small proteins. AMPLE clusters and truncates ab initio protein structure predictions, producing search models for molecular replacement. Here, an interesting degree of complementarity is shown between targets solved using the different ab initio modelling programs QUARK and ROSETTA. Search models derived from either program collectively solve almost all of the all-helical targets in the test set. Initial solutions produced by Phaser after only 5 min perform surprisingly well, improving the prospects for in situ structure solution by AMPLE during synchrotron visits. Taken together, the results show the potential for AMPLE to run more quickly and successfully solve more targets than previously suspected.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

SU-F-I-03: Correction of Intra-Fractional Set-Up Errors and Target Coverage Based On Cone-Beam Computed Tomography for Cervical Cancer Patients

Purpose: The purpose of this study is to investigate the patient set-up error and interfraction target coverage in cervical cancer using image-guided adaptive radiotherapy (IGART) with cone-beam computed tomography (CBCT). Methods: Twenty cervical cancer patients undergoing intensity modulated radiotherapy (IMRT) were randomly selected. All patients were matched to the isocenter using laser with the skin markers. Three dimensional CBCT projections were acquired by the Varian Truebeam treatment system. Set-up errors were evaluated by radiation oncologists, after CBCT correction. The clinical target volume (CTV) was delineated on each CBCT, and the planning target volume (PTV) coverage of each CBCT-CTVs was analyzed. Results: A total of 152 CBCT scans were acquired from twenty cervical cancer patients, the mean set-up errors in the longitudinal, vertical, and lateral direction were 3.57, 2.74 and 2.5mm respectively, without CBCT corrections. After corrections, these were decreased to 1.83, 1.44 and 0.97mm. For the target coverage, CBCT-CTV coverage without CBCT correction was 94% (143/152), and 98% (149/152) with correction. Conclusion: Use of CBCT verfication to measure patient setup errors could be applied to improve the treatment accuracy. In addition, the set-up error corrections significantly improve the CTV coverage for cervical cancer patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Implications of climate change mitigation strategies on international bioenergy trade

Most climate change mitigation scenarios rely on increased use of bioenergy to decarbonize the energy system. Here we use results from the 33rd Energy Modeling Forum study (EMF-33) to investigate projected international bioenergy trade for different integrated assessment models across several climate change mitigation scenarios. Results show that in scenarios with no climate policy, international bioenergy trade is likely to increase over time, and becomes even more important when climate targets are set. More stringent climate targets, however, do not necessarily imply greater bioenergy trade compared to weaker targets, as final energy demand may be reduced. However, the scaling up of bioenergy trade happens sooner and at a faster rate with increasing climate target stringency. Across models, for a scenario likely to achieve a 2 °C target, 10–45 EJ/year out of a total global bioenergy consumption of 72–214 EJ/year are expected to be traded across nine world regions by 2050. While this projection is greater than the present trade volumes of coal or natural gas, it remains below the present trade of crude oil. This growth in bioenergy trade largely replaces the trade in fossil fuels (especially oil) which is projected to decrease significantly over the twenty-first century. As climate change mitigation scenarios often show diversified energy systems, in which numerous world regions can act as bioenergy suppliers, the projections do not necessarily lead to energy security concerns. Nonetheless, rapid growth in the trade of bioenergy is projected in strict climate mitigation scenarios, raising questions about infrastructure, logistics, financing options, and global standards for bioenergy production and trade.

09 BIOMASS FUELS↗
DOE OSTI2020

Nonlinear Multiobjective MPC-Based Optimal Operation of a High Consistency Refining System in Papermaking

As one of the most important unit in the papermaking industry, the high consistency (HC) refining system is confronted with challenges such as improving pulp quality, energy saving, and emissions reduction in its operation processes. Here in this correspondence, an optimal operation of HC refining system is presented using nonlinear multiobjective model predictive control strategies that aim at set-point tracking objective of pulp quality, economic objective, and specific energy (SE) consumption objective, respectively. First, a set of input and output data at different times are employed to construct the subprocess model of the state process model for the HC refining system, and then the Wiener-type model can be obtained through combining the mechanism model of Canadian Standard Freeness and the state process model that determines their structures based on Akaike information criterion. Second, the multiobjective optimization strategy that optimizes both the set-point tracking objective of pulp quality and SE consumption is proposed simultaneously, which uses NSGA-II approach to obtain the Pareto optimal set. Furthermore, targeting at the set-point tracking objective of pulp quality, economic objective, and SE consumption objective, the sequential quadratic programming method is utilized to produce the optimal predictive controllers. In conclusion, the simulation results demonstrate that the proposed methods can make the HC refining system provide a better performance of set-point tracking of pulp quality when these predictive controllers are employed. In addition, while the optimal predictive controllers orienting with comprehensive economic objective and SE consumption objective, it has been shown that they have significantly reduced the energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

On Efficient Deployment of Wireless Sensors for Coverage and Connectivity in Constrained 3D Space

Sensor networks have been used in a rapidly increasing number of applications in many fields. This work generalizes a sensor deployment problem to place a minimum set of wireless sensors at candidate locations in constrained 3D space to k-cover a given set of target objects. By exhausting the combinations of discreteness/continuousness constraints on either sensor locations or target objects, we formulate four classes of sensor deployment problems in 3D space: deploy sensors at Discrete/Continuous Locations (D/CL) to cover Discrete/Continuous Targets (D/CT). We begin with the design of an approximate algorithm for DLDT and then reduce DLCT, CLDT, and CLCT to DLDT by discretizing continuous sensor locations or target objects into a set of divisions without sacrificing sensing precision. Furthermore, we consider a connected version of each problem where the deployed sensors must form a connected network, and design an approximation algorithm to minimize the number of deployed sensors with connectivity guarantee. For performance comparison, we design and implement an optimal solution and a genetic algorithm (GA)-based approach. Extensive simulation results show that the proposed deployment algorithms consistently outperform the GA-based heuristic and achieve a close-to-optimal performance in small-scale problem instances and a significantly superior overall performance than the theoretical upper bound.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Methods, compounds and systems for detecting a microorganism in a sample

Methods to identify a set of probe polynucleotides suitable for detecting a set of targets and in particular methods for identification of primers suitable for detection of target microorganisms related polynucleotides, set of polynucleotides and compositions, and related methods and systems for detection and/or identification of microorganisms in a sample.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Target Formulation and Construction in Mesh Quality Improvement

In the Target-matrix Optimization Paradigm (TMOP), it’s long been understood that one must create a set of target matrices before the mesh can be optimized. But there is still no general method to create correct, effective targets in response to a specific mesh quality improvement goal. The TMOP literature describes how certain sets of target matrices can be used to control the shape or size of mesh elements, but those examples address only a fraction of the problems that can occur in mesh quality improvement and were not derived from a general framework for target matrix construction. In this work, a general method of target construction is introduced based on an independent set of geometric parameters which are intrinsic to the Jacobian matrices upon which TMOP is based. The parameters enable a systematic approach to target definition and construction. The approach entails two parts. The first part defines correspondences between available raw data (stuff about the mesh and/or the physical solution) and intermediate data (e.g., a field of error estimates). Once the correspondences are established, the raw data is processed into intermediate field data existing on mesh sample points. The second part is to create a model that represents the values of the geometric target parameters as functions of the intermediate data. The model is then tested numerically to establish model constants and effectiveness. This systematic approach to target construction is illustrated in a set of examples to show how it can be applied to common problems in mesh optimization such as equidistribution of geometric properties, preservation of existing good quality, and adaptation of the mesh to the solution. The result is a systematic method of target construction for TMOP which can be applied to a wide variety of planar and volume mesh quality improvement tasks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2022

A New Machine Learning Based Analysis for Improving Satellite Retrieved Atmospheric Composition Data: OMI SO2 as an Example

Despite recent progress, satellite retrievals of anthropogenic SO2 still suffer from relatively low signal-tonoise ratios. In this study, we demonstrate a new machine learning data analysis method to improve the quality of satellite SO2 products. In the absence of large ground-truth datasets for SO2, we start from SO2 slant column densities (SCDs) retrieved from the Ozone Monitoring Instrument (OMI) using a data-driven, physically based algorithm and calculate the ratio between the SCD and the root mean square (rms) of the fitting residuals for each pixel. To build the training data, we select presumably clean pixels with small SCD / rms ratios (SRRs) and set their target SCDs to zero. For polluted pixels with relatively large SRRs, we set the target to the original retrieved SCDs. We then train neural networks (NNs) to reproduce the target SCDs using predictors including SRRs for individual pixels, solar zenith, viewing zenith and phase angles, scene reflectivity, and O3 column amounts, as well as the monthly mean SRRs. For data analysis, we employ two NNs: (1) one trained daily to produce analyzed SO2 SCDs for polluted pixels each day and (2) the other trained once every month to produce analyzed SCDs for less polluted pixels for the entire month. Test results for 2005 show that our method can significantly reduce noise and artifacts over background regions. Over polluted areas, the monthly mean NN-analyzed and original SCDs generally agree to within ±15 %, indicating that our method can retain SO2 signals in the original retrievals except for large volcanic eruptions. This is further confirmed by running both the NN-analyzed and original SCDs through a topdown emission algorithm to estimate the annual SO2 emissions for ∼ 500 anthropogenic sources, with the two datasets yielding similar results. We also explore two alternative approaches to the NN-based analysis method. In one, we employ a simple linear interpolation model to analyze the original SCD retrievals. In the other, we develop a PCA–NN algorithm that uses OMI measured radiances, transformed and dimension-reduced with a principal component analysis (PCA) technique, as inputs to NNs for SO2 SCD retrievals. While the linear model and the PCA–NN algorithm can reduce retrieval noise, they both underestimate SO2 over polluted areas. Overall, the results presented here demonstrate that our new data analysis method can significantly improve the quality of existing OMI SO2 retrievals. The method can potentially be adapted for other sensors and/or species and enhance the value of satellite data in air quality research and applications.

Can Li↗
DOE OSTI2014

Accumulated SET protein up-regulates and interacts with hnRNPK, increasing its binding to nucleic acids, the Bcl-xS repression, and cellular proliferation

Highlights: • hnRNPK is a new target of SET. • SET regulates hnRNPK. • SET and hnRNPK accumulation promotes tumorigenesis. • SET accumulation is a potential model to study genes regulated by SET-hnRNPK. - Abstract: SET and hnRNPK are proteins involved in gene expression and regulation of cellular signaling. We previously demonstrated that SET accumulates in head and neck squamous cell carcinoma (HNSCC); hnRNPK is a prognostic marker in cancer. Here, we postulate that SET and hnRNPK proteins interact to promote tumorigenesis. We performed studies in HEK293 and HNSCC (HN6, HN12, and HN13) cell lines with SET/hnRNPK overexpression and knockdown, respectively. We found that SET and/or hnRNPK protein accumulation increased cellular proliferation. SET accumulation up-regulated hnRNPK mRNA and total/phosphorylated protein, promoted hnRNPK nuclear location, and reduced Bcl-x mRNA levels. SET protein directly interacted with hnRNPK, increasing both its binding to nucleic acids and Bcl-xS repression. We propose that hnRNPK should be a new target of SET and that SET–hnRNPK interaction, in turn, has potential implications in cell survival and malignant transformation.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2018

Universal and Automated Monte Carlo Method Code for Uncertainty Propagation in Metrology Databases

A method of providing transformed target points for integrating a component into an assembly includes collecting a set of component target points, collecting a set of assembly target points, identifying target points common to the set of component target points and the set of assembly target points; performing a specified number of Monte Carlo transformations of selected ones of the common target points to yield a set of transformed target points and vectors and an associated uncertainty value for each transformed target point and vector, and using certain ones of the transformed target points for integrating the component into the assembly based on the associated uncertainty value for each of the transformed target points.

Hayden, Joseph↗