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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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NASA NTRS2016

Soil Moisture Active Passive Mission L4_SM Data Product Assessment (Version 2 Validated Release)

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the “Version 2” validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities.

SMAP L4_SM↗
NASA NTRS1984

Multi crop area estimation in Idaho using EDITOR

The use of LANDSAT multispectral scanner digital data for multi-crop acreage estimation in the central Snake River Plain of Idaho was examined. Two acquisitions of LANDSAT data covering ground sample units selected from a U.S. Department of Agriculture sampling frame in a four country study site were used to train a maximum likelihood classifier which, subsequently, classified all picture elements in the study site. Acreage estimates for six major crops, by county and for the four counties combined, were generated from the classification using the Battesse-Fuller model for estimation by regression in small areas. Results from the regression analysis were compared to those obtained by direct expansion of the ground data. Using the LANDSAT data significantly decreased the errors associated with the estimates for the three largest acreage crops. The late date of the second LANDSAT acquisition may have contributed to the poor results for three summer crops.

Sheffner, E. J.↗
NASA NTRSDate not supplied

Optical Time Transfer for Bistatic SAR Spacecraft

A spacecraft-to-spacecraft optical time-transfer simulation has been developed as a tool for informing NASA’s Surface Deformation and Change (SDC) mission architecture. The SDC mission will combine radar images from multiple spacecraft to improve understanding of the Earth’s sea-level and landscape changes. Spacecraft must be precisely synchronized in order to create sharp radar images. Simulation of multiple spacecraft time-synchronizing via laser communication can inform technology choices of a mission by providing a picosecond-precision level estimate of clock error. This timing and ranging simulation has been combined with a radar system performance analysis pipeline. The simulated timing errors are used to predict performance of bistatic SAR systems in the presence of oscillator noise and time synchronization in accuracy. This analysis includes both analytic approximation equations from existing literature, and a numerical radar simulation to extract key system performance parameters like phase error and signal-to-noise ratio (SNR)degradation. Precision time-transfer techniques facilitate the accurate synchronization of clocks between any combination of terminals. Most time-transfer technology for comparing two clocks at different terminals use radio frequencies (RF) to measure the time delay between the sending and receiving of signals. Laser technology offers the capability to transmit high data rates with systems that are of smaller size and lower power than comparable RF systems. The clocks on independent spacecraft will have some phase and frequency errors between them that result in clock drift. The two clock models that are included in this bi-directional MATLAB simulation are a cesium-based Chip-Scale Atomic Clock (CSAC) and a rubidium-based Miniature Atomic Clock (MAC). The CSAC has flown as hardware for small satellite missions such as the University of Florida’s CHOMPTT mission. A study of example orbits, including that of NASA NASA-ISRO Synthetic Aperture Radar Mission (NISAR) mission, and lasing rates demonstrate the impact of flight configuration parameters on the synchronization error between two spacecraft. The MATLAB timing simulation uses a Runge-Kutta 4th-order method to propagate spacecraft orbits and computes the light-travel time estimate between them. The simulation outputs the estimated range and estimated clock error based on a user-defined spacecraft cluster configuration. The radar simulation and analytic approximations are applied to evaluate a potential future NASA bistatic SAR constellation architecture. In the proposed architecture, satellites follow each other in the same orbit at 800 km altitude, with a 210 km baseline. We also baseline the CSAC as an ultra stable oscillator, and use NASA’s NISAR for baseline radar system parameters to compute a clock-system introduced phase error of 5.6 degrees without synchronization by frequent time transfer. We build on this base case with a sensitivity analysis of radar performance over a proposed range of constellation and radar system parameters. With this analysis pipeline, we comment on which radar parameters should or should not be changed to minimize synchronization requirements. This analysis technique could be extended or modified to evaluate the timing requirements of other geometries for other future multistatic SAR missions, or other interferometric satellite missions.

Surface Deformation and Change↗
NASA NTRS1987

Coastal Zone Color Scanner atmospheric correction algorithm - Multiple scattering effects

Errors due to multiple scattering which are expected to be encountered in application of the current Coastal Zone Color Scanner (CZCS) atmospheric correction algorithm are analyzed. The analysis is based on radiative transfer computations in model atmospheres, in which the aerosols and molecules are distributed vertically in an exponential manner, with most of the aerosol scattering located below the molecular scattering. A unique feature of the analysis is that it is carried out in scan coordinates rather than typical earth-sun coordinates, making it possible to determine the errors along typical CZCS scan lines. Information provided by the analysis makes it possible to judge the efficacy of the current algorithm with the current sensor and to estimate the impact of the algorithm-induced errors on a variety of applications.

Gordon, Howard R.↗
NASA NTRS1973

Induced shock pulse testing by transient waveform control

A method of synthesizing an arbitrarily shaped transient time pulse on vibration exciters is described. The transient waveform control technique is based on recent developments in digital time series analysis, the real-time FFT processor. A brief description of the theory, error estimates and hardware/software implementation to the JPL Dynamic Environmental Testing Laboratory is presented.

Kim, B. K.↗
NASA NTRS1975

Reduced backscattering cross section (Sigma degree) data from the Skylab S-193 radar altimeter

Backscattering cross section per unit scattering area data, reduced from measurements made by the Skylab S-193 radar altimeter over the ocean surface are presented. Descriptions of the altimeter are given where applicable to the measurement process. Analytical solutions are obtained for the flat surface impulse response for the case of a nonsymmetrical antenna pattern. Formulations are developed for converting altimeter AGC outputs into values for the backscattering cross section. Reduced data are presented for Missions SL-2, 3 and 4 for all modes of the altimeter where sufficient calibration existed. The problem of interpreting land scatter data is also discussed. Finally, a comprehensive error analysis of the measurement is presented and worst case random and bias errors are estimated.

Brown, G. S.↗
NASA NTRS1987

Automated mesoscale winds determined from satellite imagery

A new automated technique for extracting mesoscale fields from GOES visible/infrared satellite imagery was developed. Quality control parameters were defined to allow objective editing of the wind fields. The system can produce equivalent or superior cloud wind estimates compared to the time consuming manual methods used on various interactive meteorological processing systems. Analysis of automated mesoscale cloud wind for a test case yields an estimated random error value one meter per second and produces both regional and mesoscale vector wind field structure and divergence patterns that are consistent in time and highly correlated with subsequent severe thunderstorm development.

Source record↗
NASA NTRS1989

Convergence results for pseudospectral approximations of hyperbolic systems by a penalty type boundary treatment

A new method of imposing boundary conditions in the pseudospectral approximation of hyperbolic systems of equations is proposed. It is suggested to collocate the equations, not only at the inner grid points, but also at the boundary points and use the boundary conditions as penalty terms. In the pseudo-spectral Legrendre method with the new boundary treatment, a stability analysis for the case of a constant coefficient hyperbolic system is presented and error estimates are derived.

Funaro, Daniele↗
NASA NTRS1994

Analyses and forecasts with LAWS winds

Horizontal fluxes of atmospheric water vapor are studied for summer months during 1989 and 1992 over North and South America based on analyses from European Center for Medium Range Weather Forecasts, US National Meteorological Center, and United Kingdom Meteorological Office. The calculations are performed over 20 deg by 20 deg box-shaped midlatitude domains located to the east of the Rocky Mountains in North America, and to the east of the Andes Mountains in South America. The fluxes are determined from operational center gridded analyses of wind and moisture. Differences in the monthly mean moisture flux divergence determined from these analyses are as large as 7 cm/month precipitable water equivalent over South America, and 3 cm/month over North America. Gridded analyses at higher spatial and temporal resolution exhibit better agreement in the moisture budget study. However, significant discrepancies of the moisture flux divergence computed from different gridded analyses still exist. The conclusion is more pessimistic than Rasmusson's estimate based on station data. Further analysis reveals that the most significant sources of error result from model surface elevation fields, gaps in the data archive, and uncertainties in the wind and specific humidity analyses. Uncertainties in the wind analyses are the most important problem. The low-level jets, in particular, are substantially different in the different data archives. Part of the reason for this may be due to the way the different analysis models parameterized physical processes affecting low-level jets. The results support the inference that the noise/signal ratio of the moisture budget may be improved more rapidly by providing better wind observations and analyses than by providing better moisture data.

Wang, Muyin↗
NASA NTRS1996

Evaluation of high temperature superconductive thermal bridges for space borne cryogenic detectors

Infrared sensor satellites are used to monitor the conditions in the earth's upper atmosphere. In these systems, the electronic links connecting the cryogenically cooled infrared detectors to the significantly warmer amplification electronics act as thermal bridges and, consequently, the mission lifetimes of the satellites are limited due to cryogenic evaporation. High-temperature superconductor (HTS) materials have been proposed by researchers at the National Aeronautics and Space Administration Langley's Research Center (NASA-LaRC) as an alternative to the currently used manganin wires for electrical connection. The potential for using HTS films as thermal bridges has provided the motivation for the design and the analysis of a spaceflight experiment to evaluate the performance of this superconductive technology in the space environment. The initial efforts were focused on the preliminary design of the experimental system which allows for the quantitative comparison of superconductive leads with manganin leads, and on the thermal conduction modeling of the proposed system. Most of the HTS materials were indicated to be potential replacements for the manganin wires. In the continuation of this multi-year research, the objectives of this study were to evaluate the sources of heat transfer on the thermal bridges that have been neglected in the preliminary conductive model and then to develop a methodology for the estimation of the thermal conductivities of the HTS thermal bridges in space. The Joule heating created by the electrical current through the manganin wires was incorporated as a volumetric heat source into the manganin conductive model. The radiative heat source on the HTS thermal bridges was determined by performing a separate radiant interchange analysis within a high-T(sub c) superconductor housing area. Both heat sources indicated no significant contribution on the cryogenic heat load, which validates the results obtained in the preliminary conduction model. A methodology was presented for the estimation of the thermal conductivities of the individual HTS thermal bridge materials and the effective thermal conductivities of the composite HTS thermal bridges as functions of temperature. This methodology included a sensitivity analysis and the demonstration of the estimation procedure using simulated data with added random errors. The thermal conductivities could not be estimated as functions of temperature; thus the effective thermal conductivities of the HTS thermal bridges were analyzed as constants.

Scott, Elaine P.↗
NASA NTRS2009

Elemental Composition of 433 Eros: New Calibration of the NEAR-Shoemaker XRS Data

We present a new calibration of the elemental-abundance data for Asteroid 433 Fros taken by the X-ray spectrometer (XRS) aboard the NEAR-Shoemaker spacecraft. (NEAR is an acronym for "Near-Earth Asteroid Rendezvous,") Quintification of the asteroid surface elemental abundance ratios depends critically on accurate knowledge of the incident solar X-ray spectrum, which was monitored simultaneously with asteroid observations. Previously published results suffered from incompletely characterized systematic uncertainties due to an imperfect ground calibrations of the NEAR gas solar monitor. The solar monitor response function and associated uncertainties have now been characterized by cross-calibration of a large sample of NEAR solar monitor flight data against. contemporary broadband solar X-ray data from the Earth-orbiting GOES-8 (Geostationary Operational Environmental Satellite). The results have been used to analyze XRS spectra acquired from Eros during eight major solar flares (including three that have not previously been reported). The end product of this analysis is a revised set of Eros surface elemental abundance ratios with new error estimates that more accurately reflect the remaining uncertainties in the solar flare spectra: Mg/Si=.753 +0.078/-0.055, Al/Si=0.069 +/-0.055, S/Si=0.005+/-0.008, Ca/Si=0.060+0.023/-0.024, and Fe/Si= 1.578+0.338/-0.320. These revised abundance ratios are consitent within cited uncertainties with the results of Nittler et al. [Nittler, L.R., and 14 colleagues, 2001. Meteorit Planet. Sci 36, 1673-1695] and thus support the prior conclusions that 433 Eros has major-element composition simular to ordinary chondrites with the exception of a stong depletoin in sulfur, most likely caused by space weathering.

Lim, Lucy F.↗
NASA NTRS2014

Self-Calibration of BICEP1 Three-Year Data and Constraints on Astrophysical Polarization Rotation

Cosmic microwave background (CMB) polarimeters aspire to measure the faint B-mode signature predicted to arise from inflationary gravitational waves. They also have the potential to constrain cosmic birefringence, rotation of the polarization of the CMB arising from parity-violating physics, which would produce nonzero expectation values for the CMB's temperature to B-mode correlation (TB) and E-mode to B-mode correlation (EB) spectra. However, instrumental systematic effects can also cause these TB and EB correlations to be nonzero. In particular, an overall miscalibration of the polarization orientation of the detectors produces TB and EB spectra which are degenerate with isotropic cosmological birefringence, while also introducing a small but predictable bias on the BB spectrum. We find that BICEP1 three-year spectra, which use our standard calibration of detector polarization angles from a dielectric sheet, are consistent with a polarization rotation of alpha = −2.77deg +/- 0.86deg (statistical) +/- 1.3deg (systematic). We have revised the estimate of systematic error on the polarization rotation angle from the two-year analysis by comparing multiple calibration methods. We also account for the (negligible) impact of measured beam systematic effects. We investigate the polarization rotation for the BICEP1 100 GHz and 150 GHz bands separately to investigate theoretical models that produce frequency-dependent cosmic birefringence. We find no evidence in the data supporting either of these models or Faraday rotation of the CMB polarization by the Milky Way galaxy's magnetic field. If we assume that there is no cosmic birefringence, we can use the TB and EB spectra to calibrate detector polarization orientations, thus reducing bias of the cosmological B-mode spectrum from leaked E-modes due to possible polarization orientation miscalibration. After applying this "self-calibration" process, we find that the upper limit on the tensor-to-scalar ratio decreases slightly, from r < 0.70 to r < 0.65 at 95% confidence.

three-year↗
NASA NTRS1993

Spectral characteristics of time-dependent orbit errors in altimeter height measurements

A mean reference surface and time-dependent orbit errors are estimated simultaneously for each exact-repeat ground track from the first two years of Geosat sea level estimates based on the Goddard Earth model (GEM)-T2 orbits. Motivated by orbit theory and empirical analysis of Geosat data, the time-dependent orbit errors are modeled as 1 cycle per revolution (cpr) sinusoids with slowly varying amplitude and phase. The method recovers the known 'bow tie effect' introduced by the existence of force model errors within the precision orbit determination (POD) procedure used to generate the GEM-T2 orbits. The bow tie pattern of 1-cpr orbit errors is characterized by small amplitudes near the middle and larger amplitudes (up to 160 cm in the 2 yr of data considered here) near the ends of each 5- to 6-day orbit arc over which the POD force model is integrated. A detailed examination of these bow tie patterns reveals the existence of daily modulations of the amplitudes of the 1-cpr sinusoid orbit errors with typical and maximum peak-to-peak ranges of about 14 cm and 30 cm, respectively. The method also identifies a daily variation in the mean orbit error with typical and maximum peak-to-peak ranges of about 6 and 30 cm, respectively, that is unrelated to the predominant 1-cpr orbit error. Application of the simultaneous solution method to the much less accurate Geosat height estimates based on the Naval Astronautics Group orbits concludes that the accuracy of POD is not important for collinear altimetric studies of time-dependent mesoscale variability (wavelengths shorter than 1000 km), as long as the time-dependent orbit errors are dominated by 1-cpr variability and a long-arc (several orbital periods) orbit error estimation scheme such as that presented here is used.

Chelton, Dudley B.↗
DOE OSTI2025

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1972

Evaluation of errors in prior mean and variance in the estimation of integrated circuit failure rates using Bayesian methods

The critical point of any Bayesian analysis concerns the choice and quantification of the prior information. The effects of prior data on a Bayesian analysis are studied. Comparisons of the maximum likelihood estimator, the Bayesian estimator, and the known failure rate are presented. The results of the many simulated trails are then analyzed to show the region of criticality for prior information being supplied to the Bayesian estimator. In particular, effects of prior mean and variance are determined as a function of the amount of test data available.

Fletcher, B. C.↗
NASA NTRS1986

Precise orbit determination of a geosynchronous satellite with differential very-long-baseline interferometry

The use of differential VLBI (DVLBI) to determine the orbit of a U.S. geosynchronous satellite with a position accuracy of a few meters is examined. DVLBI was employed to track the geosynchronous satellite DSCS-II; two observation channels with 2 MHz bandwidth each in a 2 GHz band were used to receive the telemetry signal of the satellite and quasar radio signals. The random observation, delay, station location, and quasar position errors are discussed. The correlation processing of the quasar and satellite signals is described. The accuracy of the estimated satellite position is evaluated using a covariance analysis. It is determined that the satellite position was estimated with an accuracy of about 4 m at the center of the observation arc. It is noted that the modeling error of the solar radiation pressure factor, ionospheric correction error, and observation error need to be corrected in order to provide more accurate orbit determinations.

Shiomi, Tadashi↗