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At least 1,261 records · Page 70

Characterization of SimulCam, a standoff Raman system for scientific support of SuperCam operations on Mars

During the development activities of SuperCam Calibration Target, target intended for one of the two first Raman instruments to be deployed on another planetary body, our group developed a laboratory instrument that could simulate to some extent the Raman capabilities of one of such instruments and could provide data with similar quality. The use of this kind of laboratory instruments has demonstrated its utility in the evaluation of potential calibration targets or anticipating the science outcome that an instrument could provide. The present work describes our laboratory setup to support SuperCam, evaluating similarities between both instruments, despite of differences in the hardware. Evaluation of data gathered by SuperCam on Mars and the availability of one replica of SuperCam’s Calibration Target allowed the comparison on the same set of targets, demonstrating how similar Signal-to-Noise Ratio (SNR) could be achieved from both instruments. The higher energy per pulse on SimulCam is compensated by a greater analytical footprint and the use of smaller collection optics. The results show how spectra obtained at representative distances of SuperCam are comparable. Operational principles are also comparable in terms of time resolution, and close in terms of spectral resolution. This similarity has allowed different science support works using SimulCam data, as well as the support to Mars detections using our setup. We provide examples of this support that will be shared with the community in different papers, as well as examples of possible operations activities that could benefit from experiments performed with SimulCam. We show how this setup can complement the two laboratory replicas in Los Alamos and Toulouse in providing support data to different experiments.

47 OTHER INSTRUMENTATION↗

P -wave π π scattering and the ρ resonance from lattice QCD

Here we calculate the parameters describing elastic I = 1, P-wave ππ scattering using lattice QCD with 2 +1 flavors of clover fermions. Our calculation is performed with a pion mass of m π ≈ 320 MeV and a lattice size of L ≈ 3.6 fm. We construct the two-point correlation matrices with both quark-antiquark and two-hadron interpolating fields using a combination of smeared forward, sequential and stochastic propagators. The spectra in all relevant irreducible representations for total momenta |$\vec{P}$| ≤ $\sqrt{3}\frac{2π}{L}$ are extracted with two alternative methods: a variational analysis as well as multiexponential matrix fits. We perform an analysis using Lüscher’s formalism for the energies below the inelastic thresholds, and investigate several phase shift models, including possible nonresonant contributions. We find that our data are well described by the minimal Breit-Wigner form, with no statistically significant nonresonant component. In determining the ρ resonance mass and coupling we compare two different approaches: fitting the individually extracted phase shifts versus fitting the t-matrix model directly to the energy spectrum. We find that both methods give consistent results, and at a pion mass of am π = 0.18295 (36) stat obtain gρππ = 5.69(13) stat (16) sys , am ρ = 0.4609(16) stat (14) sys , and am ρ /am N = 0.7476(38) stat (23) sys , where the first uncertainty is statistical and the second is the systematic uncertainty due to the choice of fit ranges.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dynamic Model of Elastoplastic Normal Collision of Spherical Particles under Nonlocal Plasticity

The problem of normal collision of a spherical particle with a half-space is considered with allowance for nonlocal plastic deformation in the case where the strength limit depends on the contact radius, as well as for the strengthening effect in the deformed material. The dimensionless coefficient of normal velocity restitution has been calculated numerically as a function of the initial velocity of the spherical particle. The obtained data coincide well with experimental results available in the literature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Elevation Grid for top Columbia River Basalt (CRBG) in the Portland Basin used in DDU Feasibility Study

The Portland Basin is a prime location to assess the feasibility of DDU-TES because natural geologic conditions provide thermal and hydraulic separation from overlying aquifers that would otherwise sweep away stored heat. Under the Portland Basin, the lower Columbia River Basalt Group (CRBG) aquifers contain brackish water (1,000-10,000 mg/L TDS), indicating low groundwater flow rates and poor connection with the overlying regional aquifer. Further, CRBG lavas tend to have comparatively low thermal conductivity, indicating that the 400-1,000 ft thick CRBG may be an effective thermal barrier to the overlying aquifer. A temporally and spatially limited previous study of a Portland Basin CRBG aquifer demonstrated that the injection of waste heat resulted in an increase in temperature by more than a factor of two, indicating a high potential for storing heat. This data submission includes ASCII grid surfaces for the Portland and Tualatin Basins including a DEM of modern topography, the top of Columbia River Basalt (CRB), the base of CRB, and basement. It also includes three isochore (thickness) maps between these intervals. In addition, there is an ArcGIS attribute table for associated data points, a map of data types used to constrain the top of CRB, and cross-sections, all made using IHS Kingdom Suite, Petrosys PRO, ESRI ArcGIS, and Adobe Illustrator software.

15 GEOTHERMAL ENERGY↗

Observed and Imputed Volumetric Soil Water Content Timeseries for the New Mexico Elevation Gradient

Reliable soil water content (SWC) data are essential for understanding dryland ecosystem dynamics, but high-frequency SWC sensors often fail, creating gaps in critical datasets. To address this, we developed a Bayesian mixture model that imputes missing SWC using both linear interpolation and an ecosystem water balance model (SOILWAT2), tested across six AmeriFlux eddy covariance tower sites in the New Mexico Elevation Gradient, demonstrating its effectiveness in reconstructing SWC patterns while providing insights into the factors driving SWC variability. Daily volumetric soil water content (SWC) data are provided as csv-formatted spreadsheets for the six AmeriFlux sites (US-Seg, US-Ses, US-Wjs, US-Mpi, US-Vcp, and US-Vcs). For each site there is an observed SWC file (site_SWC_gapfill.csv) and a file that contains imputed SWC (imputed_SWC_site.csv). The observed SWC files contain temperature corrected sensor values, tower precipitation data, as well as outputs from SOILWAT2 simulations that were used to impute SWC. The imputed files contain the original observed SWC values and the imputed missing SWC values. When SWC was missing from the original data, the missing value was imputed based on the Bayesian imputation mixture model. The posterior mean of all imputed values is reported as "mean_X". When the observed SWC was NOT missing, mean_X = observed SWC value (original data). The standard deviation, 2.5th percentile and the 97.5th percentile for the imputed values are also reported in the imputed files. There are readme text files for each file type explaining the contents of each column.

54 ENVIRONMENTAL SCIENCES↗

An advanced joint inversion system for CO 2 storage modeling with large date sets for characterization and real-time monitoring-enhancing storage performance and reducing failure risks under uncertainties

As large-scale, commercial storage projects become operational, the problem of utilizing information from diverse sources becomes more critically important. In this project, we developed, tested, and applied an advanced joint data inversion system for CO 2 storage modeling with large data sets for use in site characterization and real-time monitoring. Emphasis was on the development of advanced and efficient computational algorithms for joint inversion of hydro-geophysical data, coupled with state-of-the-art forward process simulations. The developed system consists of (1) inversion tools using characterization data, such as 3D seismic survey (amplitude images), borehole log and core data, as well as hydraulic, tracer and thermal tests before CO 2 injection, (2) joint inversion tools for updating the geologic model with the distribution of rock properties, thus reducing uncertainty, using hydro-geophysical monitoring data, and (3) highly efficient algorithms for directly solving the dense or sparse linear algebra systems derived from the joint inversion. The system combines methods from stochastic analysis, fast linear algebra, and high performance computing. The developed joint inversion tools have been tested through synthetic CO 2 storage examples.

01 COAL, LIGNITE, AND PEAT↗

Recent Cycle Time Reduction at Langley Research Center

The NASA Langley Research Center (LaRC) has been engaged in an effort to reduce wind tunnel test cycle time in support of Agency goals and to satisfy the wind tunnel testing needs of the commercial and military aerospace communities. LaRC has established the Wind Tunnel Enterprise (WTE), with goals of reducing wind tunnel test cycle time by an order of magnitude by 2002, and by two orders of magnitude by 2010. The WTE also plans to meet customer expectations for schedule integrity, as well as data accuracy and quality assurance. The WTE has made progress towards these goals over the last year with a focused effort on technological developments balanced by attention to process improvements. This paper presents a summary of several of the WTE activities over the last year that are related to test cycle time reductions at the Center. Reducing wind tunnel test cycle time, defined here as the time between the freezing of loft lines and delivery of test data, requires that the relationship between high productivity and data quality assurance be considered. The efforts have focused on all of the drivers for test cycle time reduction, including process centered improvements, facility upgrades, technological improvements to enhance facility readiness and productivity, as well as advanced measurement techniques. The application of internet tools and computer modeling of facilities to allow a virtual presence of the customer team is also presented.

Kegelman, Jerome T.↗

Maquoketa Shale Caprock Integrity Evaluation

The Knox Project objective is to evaluate the potential of formations within the Cambrian-Ordovician strata above the Mt. Simon Sandstone (St. Peter Sandstone and Potosi Dolomite) as potential targets for carbon dioxide (CO2) sequestration in the Illinois and Michigan Basins. The suitability of the St. Peter Sandstone and Potosi Dolomite to serve as reservoirs for CO2 sequestration is discussed in separate reports. In this report the data gathered from the Knox project, the Illinois Basin – Decatur Project (IBDP) and Illinois Industrial Carbon Capture and Sequestration project (IL-ICCS) are used to make some conclusions about the suitability of the Maquoketa shale as a confining layer for CO2 sequestration. These conclusions are then upscaled to basin-wide inferences based on regional knowledge. Data and interpretations (stratigraphic, petrophysical, fractures, geochemical, risk, seismic) applicable to the Maquoketa Shale from the above mentioned projects was inventoried and summarized. Based on the analysis of these data and interpretations, the Maquoketa Shale is considered to be an effective caprock for a CO2 injection project in either the Potosi Dolomite or St. Peter Sandstone because it has a suitable thickness (~200ft. ~61m), advantageous petrophysical properties (low effective porosity and low permeability), favorable geomechanical properties, an absence of observable fractures and is regionally extensive. Because it is unlikely that CO2 would migrate upward through the Maquoketa Shale, CO2, impact to above lying fresh water aquifers is unlikely. Furthermore, the observations indicate that CO2 injected into the St. Peter Sandstone or Potosi Dolomite may never even migrate up into the Maquoketa Shale at a high enough concentrations or pressure to threaten the integrity of the caprock. Site specific conclusions were reached by unifying the data and conclusions from the IBDP, ICCS and the Knox projects. In the Illinois Basin, as one looks further away from these sites, the formation characteristics are expected to vary. The degree of how well this data can be extrapolated throughout the Basins (regionalized) is difficult to quantify because of the limited amount of data collected on the Maquoketa Shale away from IBDP, IL-ICCS and the Knox projects. Data gathered from the IBDP/IL-ICCS/Knox projects were used to make conclusions about the suitability of the Maquoketa shale as a confining layer for CO2 sequestration. This study indicates that the Maquoketa Shale would be a suitable caprock for a CO2 injection program in either the Potosi Dolomite or St. Peter Sandstone.

Leetaru, Hannes↗

THE RADIAL VELOCITY DETECTION OF EARTH-MASS PLANETS IN THE PRESENCE OF ACTIVITY NOISE: THE CASE OF {alpha} CENTAURI Bb

We present an analysis of the publicly available HARPS radial velocity (RV) measurements for {alpha} Cen B, a star hosting an Earth-mass planet candidate in a 3.24 day orbit. The goal is to devise robust ways of extracting low-amplitude RV signals of low-mass planets in the presence of activity noise. Two approaches were used to remove the stellar activity signal which dominates the RV variations: (1) Fourier component analysis (pre-whitening), and (2) local trend filtering (LTF) of the activity using short time windows of the data. The Fourier procedure results in a signal at P = 3.236 days and K = 0.42 m s{sup -1}, which is consistent with the presence of an Earth-mass planet, but the false alarm probability for this signal is rather high at a few percent. The LTF results in no significant detection of the planet signal, although it is possible to detect a marginal planet signal with this method using a different choice of time windows and fitting functions. However, even in this case the significance of the 3.24 day signal depends on the details of how a time window containing only 10% of the data is filtered. Both methods should have detected the presence of {alpha} Cen Bb at a higher significance than is actually seen. We also investigated the influence of random noise with a standard deviation comparable to the HARPS data and sampled in the same way. The distribution of the noise peaks in the period range 2.8-3.3 days has a maximum of Almost-Equal-To 3.2 days and amplitudes approximately one-half of the K-amplitude for the planet. The presence of the activity signal may boost the velocity amplitude of these signals to values comparable to the planet. It may be premature to attribute the 3.24 day RV variations to an Earth-mass planet. A better understanding of the noise characteristics in the RV data as well as more measurements with better sampling will be needed to confirm this exoplanet.

79 ASTRONOMY AND ASTROPHYSICS↗

Mapping use cases and dataset needs for benchmarking buildings data

A perennial challenge in buildings research is the lack of high-quality datasets that can be relied upon for a wide array of tasks, including model calibration and improving energy efficiency and load flexibility. Instrumenting a building for data collection is resource intensive, so it is important to be methodical in the approach and ensure that resulting data are flexible and useful for a broad range of analyses. This study aims to fill the gaps in characterizing potential use cases for buildings datasets and mapping them to dataset needs using a well-defined data infrastructure. Here, we have developed a systematic mapping strategy between buildings dataset needs and use cases to help streamline the processes of efficiently targeting datasets, designing building sensing systems, and determining buildings research use cases. We selected 14 prospective use cases and 11 refined buildings data categories for developing the preliminary dataset-needs-to-use-cases mapping matrix (‘DN-UC mapping matrix’) with generic ‘Tags’—a detailed sub-level of data categories extracted by justifying the needs of an aspect of the datasets to use cases. We present two example applications of the developed mapping matrix to demonstrate use of the mapping matrix and its effectiveness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Enhancing nuclear data validation analysis by using machine learning

In this work, we demonstrate how machine learning (ML) techniques can be used as an auxiliary tool for nuclear data validation analysis. The output of the ML analysis can inform evaluators and validators on the quality, or lack thereof, of specific nuclear data and benchmark experiments with respect to simulating these experimental benchmark values. To this end, measured and simulated effective neutron multiplication factors, k eff , of 875 selected ICSBEP critical assemblies and the latter's sensitivities with respect to nuclear data as well as benchmarks' features (e.g., material nuclide, core geometry) are used as input for a random forest (RF) regression model. The RF is used to encode the complex inter-dependencies between thousands of nuclear data features (i.e., sensitivity profiles and aspects describing the measurements) and 875 simulated and experimental k eff values in order to understand what nuclear data features are most informative for predicting bias. The complexity of relationships and high-dimensional space is difficult-to-impossible to search fully using simply expert judgment. As a first proof-of-concept—step, it is demonstrated that this technique is able to correctly trace large discrepancies between simulated and experimental k eff back to fabricated shortcomings in nuclear data that were perturbed to simulated k eff values. In a second, real-case scenario, step, the RF algorithm is used to validate the ENDF/B-VIII.0 library in comparison to ENDF/B-VII.1 nuclear data. One case is showcased where the chosen ML algorithms highlighted nuclear data (the 19 F(n,inl) cross section from 0.4–0.9 MeV) that are shown to be problematic by comparing them to associated differential experimental data and nuclear data from other libraries. In addition to that, it is shown that the RF results point towards poor benchmark experiments and associated underestimated uncertainties (e.g., the PU-SOL-THERM-028 series). However, using the RF algorithm for validating nuclear data with respect to k eff is currently limited to pinpointing groups of questionable nuclear data due to the inherent correlations between features introduced by the nuclear data themselves and how k eff is simulated. Due to this, we recommend that the ML methods presented be used to augment—rather than replace—the expert knowledge of evaluators and validators.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Manipulating Magnetism: Ru-2(5+) Paddlewheels Devoid of Axial Interactions

Variable-temperature magnetic and structural data of two pairs of diruthenium isomers, one pair having an axial ligand and the formula Ru-2(DArF)(4)Cl (where DArF is the anion of a diarylformamidine isomer and Ar = p-anisyl or m-anisyl) and the other one being essentially identical but devoid of axial ligands and having the formula [Ru-2(DArF)(4)]BF4, show that the axial ligand has a significant effect on the electronic structure of the diruthenium unit. Variable temperature crystallographic and magnetic data as well as density functional theory calculations unequivocally demonstrate the occurrence of pi interactions between the p orbitals of the chlorine ligand and the pi* orbitals in the Ru-2(5+) units. The magnetic and structural data are consistent with the existence of combined ligand sigma/metal sigma and ligand p pi/metal-d pi interactions. Electron paramagnetic resonance data show unambiguously that the unpaired electrons are in metal-based molecular orbitals.

DIRUTHENIUM↗

Gas bulk motion in the Perseus Cluster measured with Suzaku

We present the results from Suzaku observations of the Perseus Cluster, which is relatively close, the brightest in the X-ray sky, and a relaxed object with a cool core. A number of exposures of central regions and offset pointing with the X-ray Imaging Spectrometer cover a region within radii of 20'-30'. The central data are used to evaluate the instrumental energy-scale calibration with accuracy confirmed to within around 300 km s{sup –1} by the spatial and temporal variation of the instruments. These deep and well-calibrated data are used to measure X-ray redshifts of the intracluster medium. A hint of gas bulk motion, with radial velocity of about –(150-300) km s{sup –1} relative to the main system, was found at 2'-4' (45-90 kpc) west of the cluster center, where an X-ray excess and a cold front were found previously. No other velocity structure was discovered. Over spatial scales of 50-100 kpc and within 200 kpc radii of the center, the gas-radial-velocity variation is below 300 km s{sup –1}, while over scales of 400 kpc within 600 kpc radii, the variation is below 600 km s{sup –1}. These X-ray redshift distributions are compared spatially with those of optical member galaxies for the first time in galaxy clusters. Based on X-ray line widths, gas turbulent velocities within these regions are also constrained within 1000-3000 km s{sup –1}. These results of gas dynamics in the core and larger scales in association with cluster merger activities are discussed, and the future potential of high-energy resolution spectroscopy with ASTRO-H is considered.

79 ASTRONOMY AND ASTROPHYSICS↗

Reliable and Efficient Machine Learning (Final Technical Report)

Modern scientific experiments generate massive amounts of data at a pace much faster than humans can manually analyze. While machine learning has revolutionized commercial data analysis (such as recommending movies or recognizing faces), applying these tools to complex scientific discovery is challenging because scientific answers must be precise, interpretable, and adhere to physical laws. The research under this project aims to develop new mathematical tools and computer algorithms specifically designed for scientific applications. Major progress has been made in automatically cleaning and deconstructing messy experimental data, analyzing the visual information of physical phenomena, determining the underlying physical variables, and providing rig orous mathematical analysis of interesting algorithms and concepts widely used in machine learning. This project addressed the critical gap between our ability to generate massive scientific data and our ability to extract interpretable information from it. We established mathematical foundations for Scientific Machine Learning (SciML) aimed at effective data analytics and automated discovery. Our work focused on three core objectives: (1) developing reliable feature extraction methods for dynamic high-dimensional data, (2) establishing mathematical foundations for discovering dynamics via neural networks, and (3) creating rigorous optimization techniques for these models. Key outcomes come from two fronts. On the practical side, they include the development of algorithms that significantly enhance the extraction of signals from field data, as well as the capability to handle situations that exhibit smooth variations or physical stretching due to temperature changes. They also include the creation of an automated framework for discovering fundamental state variables from raw experimental data, demonstrating the ability to identify intrinsic physical dimensions without prior knowledge of the governing laws. On the theoretical front, the research results in theoretical advances in Optimal Transport, a widely used notion in SciML, specifically regarding functions with fixed-size nodal sets, provide sharp bounds relevant to uncertainty quantification. Meanwhile, the outcomes also include the establishment of convergence theories for nonlocal gradient descent methods, enabling robust optimization with noisy data in high-dimensional settings commonly encountered in scientific modeling. The project also helps creating opportunities to train the next generation of researchers, equipping them with the necessary technical skills for today’s workplace and preparing them for future advances.

97 MATHEMATICS AND COMPUTING↗

Behavioral characteristics of effective crew leaders

The behaviors of effective versus less effective captains as they form and lead their crews in line operations are analyzed. The research examines real work groups in an actual organization with a specific and consequential task to perform and is based on a normative model of work group effectiveness. Selection of captains is outlined, as well as data collection over the course of six months of crew and cockpit observations including over 300 hours of direct crew observations and 110 hours of actual flight time. Common characteristics of the effective leaders as well as the deviations of the less effective are described, and organizational implications are assessed. The concept of 'shells' depicted as a series of concentric circles moving outward from the group's task execution at the center is introduced and discussed.

Ginnett, Robert C.↗

OSSE observations of 3C 273

We report results of multiple observations of the quasar 3C 273 with the Oriented Scintillation Spectrometer Experiment (OSSE) instrument on the Compton Gamma Ray Observatory. These observations span the period from 1991 June through 1993 January and represent the most sensitive observations to date in low-energy gamma rays. The source was detected at historically weak 100 keV fluxes compared with previous measurements. Variability by factors of approximately 3 on timescales of approximately equal 2 months was observed in the energy band 50-150 keV. The data are well described by a single power law with a proton number index Gamma = 1.7 +/- 0.1. No significant change of Gamma was observed during changes in intensity. Thermal models do not provide acceptable fits to the data. When the OSSE data are combined with contemporaneous measurements by COMPTEL and EGRET, the spectrum is seen to break at an energy of 1.0(+0.9, -0.4) MeV to a softer power law with Delta Gamma = 0.7(+0.06, -0.11), forming a power law with Gamma = 2.4 between approximately 1 MeV and several GeV.

Johnson, W. N.↗

Calibration of Sea Ice Motion from QuikSCAT with those from SSM/I and Buoy

QuikSCAT backscatter and DMSP SSM/I radiance data are used to derive sea ice motion for both the Arctic and Antarctic region using wavelet analysis method. This technique provides improved spatial coverage over the existing array of Arctic Ocean buoys and better temporal resolution over techniques utilizing satellite data from Synthetic Aperture Radar (SAR). Sea ice motion of the Arctic for the period from October 1999 to March 2000 derived from QuikSCAT and SSM/I data agrees well with that derived from ocean buoys quantitatively. Thus the ice tracking results from QuikSCAT and SSM/I are complement to each other, Then, three sea-ice drift daily results from QuikSCAT, SSM/I, and buoy data can be merged to generate composite maps with more complete coverage of sea ice motion than those from single data source. A series of composite sea ice motion maps for December 1999 show that the major circulation patterns of sea ice motion are changing and shifting significantly within every four days and they are dominated by wind forcing. Sea-ice drift in the summer can not be derived from NSCAT and SSM/I data. In later summer of 1999 (in September), however, QuikSCAT data can provide good sea ice motion information in the Arctic. QuiksCAT can also provide at least partial sea ice motion information until June 15 in early summer 1999. For the Antarctic, case study shows that sea ice motion derived from QuikSCAT data is predominantly forced by and is consistent with wind field derived from QuikSCAT around the polar region. These calibrated/validated results indicate that QuikSCAT, SSM/I, and buoy merged daily ice motion are suitably accurate to identify and closely locate sea ice processes, and to improve our current knowledge of sea ice drift and related processes through the data assimilation of ocean-ice numerical model.

Liu, Antony K.↗

Sixteen Years of Terra MODIS On-Orbit Operation, Calibration, and Performance

Terra MODIS has successfully operated for more than 16 years since its launch in December 1999. From its observations, many science data products have been generated in support of a broad range of research activities and remote sensing applications. Terra MODIS has operated in a number of configurations and experienced a few anomalies, including spacecraft and instrument related events. MODIS collects data in 36 spectral bands that are calibrated regularly by a set of on-board calibrators for their radiometric, spectral, and spatial performance. Periodic lunar observations and long-term radiometric trending over well-characterized ground targets are also used to support sensor on-orbit calibration. Dedicated efforts made by the MODIS Characterization Support Team (MCST) and continuing support from the MODIS Science Team have contributed to the mission success, enabling well-calibrated data products to be continuously generated and routinely delivered to users worldwide. This paper presents an overview of Terra MODIS mission operations, calibration activities, and instrument performance of the past 16 years. It illustrates and describes the results of key sensor performance parameters derived from on-orbit calibration and characterization, such as signal-to-noise ratio (SNR), noise equivalent temperature difference (NEdT), solar diffuser (SD) degradation, changes in sensor responses, center wavelengths, and band-to-band registration (BBR). Also discussed in this paper are the calibration approaches and strategies developed and implemented in support of MODIS Level 1B data production and re-processing, major challenging issues, and lessons learned. (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Xiong, X.↗