Results for “Artifact reduction” — Page 4

NASA NTRS1992

Water Relations, Gas Exchange, and Nutrient Response to a Long Term Constant Water Deficit

Wheat plants (Triticum aestivum) were grown for 43 days in a micro-porous tube nutrient delivery system. Roots were unable to penetrate the microporous tube, but grew on the surface and maintained capillary contact with the nutrient solution on the inside of the tube through the 5-microns pores of the porous tube. Water potential in the system was controlled at -0.4, -0.8, and -3.0 kPa by adjusting the applied pressure (hydrostatic head) to the nutrient solution flowing through the microporous tubes. A relatively small decrease in applied water potential from -0.4 to -3.0 kPa resulted in a 34% reduction of shoot growth but only a moderate reduction in the mid-day leaf water potential from - 1.3 to - 1.7 MPa. Carbon dioxide assimilation decreased and water use efficiency increased with the more negative applied water Potentials, while intercellular C02 concentration remained constant. The physiological responses observed in this study in response to small constant differences in applied water potentials were much greater than expected from either the applied water potential or the observed plant water potential. Even though the micro-porous tube may not represent natural conditions and could possibly introduce morphological and physiological artifacts , it enables a high degree of control of water potential that facilitates the investigation of many aspects of water relations not practical with other experimental systems.

Berry, Wade L.↗

NASA NTRSDate not supplied

xEMU Suit Integrated Audio Communications System: Ambient and EVA Pressure Testing System Performance

Testing across several airlock and EVA thermal and pressure scenarios has demonstrated that the Integrated Audio System of NASA’s Exploration Extravehicular Mobility Unit (xEMU) spacesuits transmits and receives intelligible audio communications without the use of a commcap or similar worn device. The xEMU audio system consists of internal loudspeakers and digital microphones (Integrated Communications System –ICS) combined with an adaptive Acoustic Echo Canceller (AEC), outbound voice operated transmission (VOX), and automatic gain control (AGC). Transducers are mounted in an “exploded commcap” configuration with helmet-attached speakers near the ears and three microphones positioned at the collar. The AGC removes inbound audio signals (e.g.,suit, Mission Control, Lander, C&W tones) from the outbound comms stream, reducing echo and feedback (squeal) in low-noise suit environments. The reduction of worn communication equipment increases crewmember comfort, range of movement, and situational awareness. However, test results also highlight the need for proper fan, duct, pump, and gas flow integration with suit acoustics and audio. Ductwork may serve as waveguides for various component and structure-borne noise. Sharply angled ducts can generate turbulent-flow noise. Gas flow from inlets above the crewmember’s head can generate noise when cascading over the faceplate and collar (or commcap) microphones. Sufficient acoustic noise levels (1) require increased gain to boost inbound audio, and (2) may distort signals resulting in AEC disruption or artifacts. Suit-noise levels decline with reduced pressure (density), but then elevated speech and audio effort/power become necessary. Whether the Integrated Audio System, commcap, or other device is used, suit acoustic noise can mask speech in outbound comms. This reduces intelligibility and requires other AECs/devices to suppress comms noise. Yet, adjusting a few components may yield significant improvement. We discuss xEMU audio functionality, demonstrate how acoustical treatment combined with inbound signal conditioning improved clarity during tests, and discuss future modifications.

xEMU↗

NASA NTRSDate not supplied

xEMU Suit Integrated Audio Communications System: Ambient and EVA Pressure Testing System Performance

Testing across several airlock and EVA thermal and pressure scenarios has demonstrated that the Integrated Audio System of NASA’s Exploration Extravehicular Mobility Unit (xEMU) spacesuits transmits and receives intelligible audio communications without the use of a commcap or similar worn device. The xEMU audio system consists of internal loudspeakers and digital microphones (Integrated Communications System –ICS) combined with an adaptive Acoustic Echo Canceller (AEC), outbound voice operated transmission (VOX), and automatic gain control (AGC). Transducers are mounted in an “exploded commcap” configuration with helmet-attached speakers near the ears and three microphones positioned at the collar. The AGC removes inbound audio signals (e.g.,suit, Mission Control, Lander, C&W tones) from the outbound comms stream, reducing echo and feedback (squeal) in low-noise suit environments. The reduction of worn communication equipment increases crewmember comfort, range of movement, and situational awareness. However, test results also highlight the need for proper fan, duct, pump, and gas flow integration with suit acoustics and audio. Ductwork may serve as waveguides for various component and structure-borne noise. Sharply angled ducts can generate turbulent-flow noise. Gas flow from inlets above the crewmember’s head can generate noise when cascading over the faceplate and collar (or commcap) microphones. Sufficient acoustic noise levels (1) require increased gain to boost inbound audio, and (2) may distort signals resulting in AEC disruption or artifacts. Suit-noise levels decline with reduced pressure (density), but then elevated speech and audio effort/power become necessary. Whether the Integrated Audio System, commcap, or other device is used, suit acoustic noise can mask speech in outbound comms. This reduces intelligibility and requires other AECs/devices to suppress comms noise. Yet, adjusting a few components may yield significant improvement. We discuss xEMU audio functionality, demonstrate how acoustical treatment combined with inbound signal conditioning improved clarity during tests, and discuss future modifications.

xEMU↗

DOE OSTI2024

Hydrodynamic Test Requirements Process Improvements

Hydrodynamic testing at Los Alamos National Laboratory would benefit from a process improvement for the requirements process. Cameo was used as a digital solution for requirements management to allow Lead Engineers to track requirements more effectively. This was identified as a process improvement throughout this Capstone project. This report includes a project proposal, business case, literature review, methodology, project plan, data analysis, decision-making report, financial analysis report, discussion, and conclusion. Initially, this project focused on figuring out a solution for the hydrotest requirement process improvements. The scope narrowed to focus on the use of Cameo for requirement capture and management. During this Capstone, four tests had digital models produced for requirements management in Cameo. The initial model was the baseline, with core requirements used across the tests. Commonalities in tests were used and the core requirements allowed for process efficiencies. In the data analysis, it was seen that overall, the implementation of using Cameo for requirements resulted in a decreasing trend for both schedule and normalized cost. Tests have different complexity levels which is also a factor in how long the requirements process will take. Additional data is needed to continue analyzing process improvements. Through decisionmaking and financial analysis, the recommendation was to use Cameo for requirements process improvement. Multiple experts provided feedback for requirements that were then captured within models. Numerous tangible and intangible benefits were identified with this process improvement. For return on investment, the metric of success was schedule reduction, which was overall seen. Four tests were analyzed, so future analysis will be needed. There is also not a great financial risk because the main cost would be purchasing more licenses. Individuals must generate requirements whether using this software or not. Overall, training is needed to help improve the skillsets of Lead Engineers but is already being supported on a regular frequency. A desktop guide was started associated with explaining the process, however, it is a work in progress. The team plans on adding additional information in the digital models to help status when requirements are met using verification methods and artifacts. From working on this project an improved understanding of Cameo and requirements was the result. There are future opportunities to extend the usage for requirements management and progress will continue after this project.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Inactivation of Fluorescent Lipid Bilayers by Irradiation With 300 keV Electrons Using Liquid Cell Transmission Electron Microscopy

Liquid cell transmission electron microscopy allows for imaging of samples in a fully hydrated state at high resolution and has the potential for visualizing static or dynamic biological structures. However, the ionizing nature of the electron beam makes it difficult to discern real physiological dynamics from radiation induced artifacts within liquid cell samples. Electron flux thresholds for achieving high resolution structures from biological samples frozen in ice have been described extensively by the cryo-electron microscopy field, while electron flux thresholds which do not result in a functional change for biological samples within the hydrated environment of a transmission electron microscope liquid cell is less clear. Establishing these functional thresholds for biologically relevant samples is important for accurate interpretation of results from liquid cell experiments. Here we demonstrate the electron damage threshold of fluorescently tagged lipid bilayers by quantifying the change in fluorescence before and after electron exposure. We observe the reduction of fluorescent signal in bilayers by 25% after only 0.0005 e − /Å 2 and a reduction of over 90% after 0.01 e − /Å 2 . These results indicate that the loss of function occurs at irradiation thresholds far below a typical single high resolution (scanning) transmission electron microscopy image and orders of magnitude below fluxes used for preserving structural features with cryo-electron microscopy.

Moser, Trevor↗

DOE OSTI2020

Boosting solid oxide fuel cell performance via electrolyte thickness reduction and cathode infiltration

Increasing the power density and reducing the operating temperature of solid oxide fuel cells (SOFCs) is important for improving commercial viability. Here we discuss two strategies for achieving such improvements in Ni–YSZ supported SOFCs – electrolyte thickness reduction and cathode infiltration. Microstructural and electrochemical results are presented showing the effect of reducing YSZ/GDC electrolyte thickness from 8 to 2.5 μm, and the effect of PrO x infiltration into the LSCF–GDC cathode. Both of these measures are effective, particularly at lower temperatures, leading to an increase in the maximum power density at 650 °C from 0.4 to 0.95 W cm –2 , for example. Electrochemical impedance spectroscopy utilizing subtractive analysis shows that PrO x enhances the cathode charge transfer process. Reducing the electrolyte thickness reduces not only the cell ohmic resistance but also the electrode polarization resistance. Furthermore, the latter effect appears to be an artifact associated with a slight increase in the steam partial pressure at the anode due to minor gas leakage across the thinner electrolyte.

25 ENERGY STORAGE↗

NASA NTRSDate not supplied

How Can We Harness the Power of Machine Learning With TEMPO Data?

There are many potential applications of machine learning for TEMPO data that include - Improve retrievals by reducing the effect of random instrument noise - Expand coverage by producing data in moderately cloudy conditions (see also Fasnacht et al. poster) - Help diagnose impacts of instrumental artifacts - Produce value-added products quickly by training on existing products from other sensors (land and ocean) - Speed up processing by training on products produced with full-physics algorithms (e.g., NO 2 slant column fitting may take ~1 hour/orbit but with a neural net it may take only minutes)

NO2↗

DOE OSTI2026

Transplatformer: translating toxicogenomic profiles between generations of platforms

Background Transcriptomic profiling technologies have advanced the analysis of biological and toxicological responses. However, substantial differences in probe design, dynamic range, gene coverage, and preprocessing pipelines across platforms introduce artifacts that limit cross-study integration and hinder the reuse of historical datasets. We aim to develop computational methods for accurate cross-platform translation to maximize the value of legacy resources. Results We present TransPlatformer a deep learning framework for translating gene expression profiles across heterogeneous toxicogenomics platforms. TransPlatformer employs a novel attention-based architecture to map high-dimensional fold-change vectors from legacy microarray technologies to current platforms. Models are trained and evaluated using DrugMatrix, spanning three technological generations. We investigate mixed-tissue, single-tissue, and cross-tissue training paradigms and benchmark performance against multilayer perceptron and matrix-completion baselines. In mixed-tissue training, TransPlatformer achieves a greater than 50% reduction in mean absolute error (0.043 vs. 0.09) and nearly doubles Pearson correlation ( ≈ 0.71 vs. 0.37) relative to baseline methods. Importantly, TransPlatformer preserves rare but biologically meaningful over- and under-expressed signals, with mean absolute error below 0.22. Single-tissue models yield further improvements for well-represented organs, such as a 10% reduction in liver mean absolute error, while underscoring the need for data augmentation strategies in low-sample tissues.ra Conclusions TransPlatformer provides an effective and scalable computational solution for cross-platform transcriptomic translation. By enabling biologically faithful harmonization of gene expression data, the proposed approach facilitates the reuse of legacy toxicogenomics datasets, enhances downstream biomarker discovery, and supports more reproducible predictive modeling in toxicology.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1992

SkICAT: A cataloging and analysis tool for wide field imaging surveys

We describe an integrated system, SkICAT (Sky Image Cataloging and Analysis Tool), for the automated reduction and analysis of the Palomar Observatory-ST ScI Digitized Sky Survey. The Survey will consist of the complete digitization of the photographic Second Palomar Observatory Sky Survey (POSS-II) in three bands, comprising nearly three Terabytes of pixel data. SkICAT applies a combination of existing packages, including FOCAS for basic image detection and measurement and SAS for database management, as well as custom software, to the task of managing this wealth of data. One of the most novel aspects of the system is its method of object classification. Using state-of-theart machine learning classification techniques (GID3* and O-BTree), we have developed a powerful method for automatically distinguishing point sources from non-point sources and artifacts, achieving comparably accurate discrimination a full magnitude fainter than in previous Schmidt plate surveys. The learning algorithms produce decision trees for classification by examining instances of objects classified by eye on both plate and higher quality CCD data. The same techniques will be applied to perform higher-level object classification (e.g., of galaxy morphology) in the near future. Another key feature of the system is the facility to integrate the catalogs from multiple plates (and portions thereof) to construct a single catalog of uniform calibration and quality down to the faintest limits of the survey. SkICAT also provides a variety of data analysis and exploration tools for the scientific utilization of the resulting catalogs. We include initial results of applying this system to measure the counts and distribution of galaxies in two bands down to Bj is approximately 21 mag over an approximate 70 square degree multi-plate field from POSS-II. SkICAT is constructed in a modular and general fashion and should be readily adaptable to other large-scale imaging surveys.

Weir, N.↗

NASA NTRS1999

Modeling of polychromatic attenuation using computed tomography reconstructed images

This paper presents a procedure for estimating an accurate model of the CT imaging process including spectral effects. As raw projection data are typically unavailable to the end-user, we adopt a post-processing approach that utilizes the reconstructed images themselves. This approach includes errors from x-ray scatter and the nonidealities of the built-in soft tissue correction into the beam characteristics, which is crucial to beam hardening correction algorithms that are designed to be applied directly to CT reconstructed images. We formulate this approach as a quadratic programming problem and propose two different methods, dimension reduction and regularization, to overcome ill conditioning in the model. For the regularization method we use a statistical procedure, Cross Validation, to select the regularization parameter. We have constructed step-wedge phantoms to estimate the effective beam spectrum of a GE CT-I scanner. Using the derived spectrum, we computed the attenuation ratios for the wedge phantoms and found that the worst case modeling error is less than 3% of the corresponding attenuation ratio. We have also built two test (hybrid) phantoms to evaluate the effective spectrum. Based on these test phantoms, we have shown that the effective beam spectrum provides an accurate model for the CT imaging process. Last, we used a simple beam hardening correction experiment to demonstrate the effectiveness of the estimated beam profile for removing beam hardening artifacts. We hope that this estimation procedure will encourage more independent research on beam hardening corrections and will lead to the development of application-specific beam hardening correction algorithms.

NASA Discipline Musculoskeletal↗

NASA NTRS2011

Principal Component Noise Filtering for NAST-I Radiometric Calibration

The National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed- Interferometer (NAST-I) instrument is a high-resolution scanning interferometer that measures emitted thermal radiation between 3.3 and 18 microns. The NAST-I radiometric calibration is achieved using internal blackbody calibration references at ambient and hot temperatures. In this paper, we introduce a refined calibration technique that utilizes a principal component (PC) noise filter to compensate for instrument distortions and artifacts, therefore, further improve the absolute radiometric calibration accuracy. To test the procedure and estimate the PC filter noise performance, we form dependent and independent test samples using odd and even sets of blackbody spectra. To determine the optimal number of eigenvectors, the PC filter algorithm is applied to both dependent and independent blackbody spectra with a varying number of eigenvectors. The optimal number of PCs is selected so that the total root-mean-square (RMS) error is minimized. To estimate the filter noise performance, we examine four different scenarios: apply PC filtering to both dependent and independent datasets, apply PC filtering to dependent calibration data only, apply PC filtering to independent data only, and no PC filters. The independent blackbody radiances are predicted for each case and comparisons are made. The results show significant reduction in noise in the final calibrated radiances with the implementation of the PC filtering algorithm.

Tian, Jialin↗

DOE OSTI2020

Dimensionality Reduction of SDSS Spectra with Variational Autoencoders

High-resolution galaxy spectra contain much information about galactic physics, but the high dimensionality of these spectra makes it difficult to fully utilize the information they contain. We apply variational autoencoders (VAEs), a nonlinear dimensionality reduction technique, to a sample of spectra from the Sloan Digital Sky Survey (SDSS). In contrast to principal component analysis (PCA), a widely used technique, VAEs can capture nonlinear relationships between latent parameters and the data. We find that a VAE can reconstruct the SDSS spectra well with only six latent parameters, outperforming PCA with the same number of components. Different galaxy classes are naturally separated in this latent space, without class labels having been given to the VAE. The VAE latent space is interpretable because the VAE can be used to make synthetic spectra at any point in latent space. For example, making synthetic spectra along tracks in latent space yields sequences of realistic spectra that interpolate between two different types of galaxies. Using the latent space to find outliers may yield interesting spectra: in our small sample, we immediately find unusual data artifacts and stars misclassified as galaxies. In this exploratory work, we show that VAEs create compact, interpretable latent spaces that capture nonlinear features of the data. While a VAE takes substantial time to train (≈1 day for 48,000 spectra), once trained, VAEs can enable the fast exploration of large astronomical data sets.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

NXREFINE

NXRefine implements a complete workflow for both data acquisition and reduction of single crystal diffuse x-ray scattering collected as a series of area detector frames during continuous sample rotation. The data are stored in HDF5 files, which conform to the NeXus data format standard. These files contain a comprehensive set of metadata, including the incident wavelength, powder calibration scans used to define detector distances, beam centers, and yaw, pitch, and roll corrections. Automated peak searches of the three-dimensional data arrays define a set of Bragg peaks that are used to define an orientation matrix, defined according to Busing and Levy, which is then used to transform the data from angular coordinates to reciprocal space coordinates using the CCTW program. Multiple rotations at different detector translations and offset rotation axes are combined to ensure that there are no gaps in the reconstructed data, and allow the construction of masks to eliminate detector artifacts due to Compton scattering within the sensor layers. Finally, the data can be transformed into 3D-ΔPDF maps using the punch-and-fill method after symmetrization.

OSBORN, RAYMOND↗

DOE OSTI2025

Distributed Stochastic Optimization of a Neural Representation Network for Time-Space Tomography Reconstruction

4D time-space reconstruction of dynamic events or deforming objects using X-ray computed tomography (CT) is an important inverse problem in non-destructive evaluation. Conventional back-projection based reconstruction methods assume that the object remains static for the duration of several tens or hundreds of X-ray projection measurement images (reconstruction of consecutive limited-angle CT scans). However, this is an unrealistic assumption for many in-situ experiments that causes spurious artifacts and inaccurate morphological reconstructions of the object. To solve this problem, we propose to perform a 4D time-space reconstruction using a distributed implicit neural representation (DINR) network that is trained using a novel distributed stochastic training algorithm. Our DINR network learns to reconstruct the object at its output by iterative optimization of its network parameters such that the measured projection images best match the output of the CT forward measurement model. Here, we use a forward measurement model that is a function of the DINR outputs at a sparsely sampled set of continuous valued 4D object coordinates. Unlike previous neural representation architectures that forward and back propagate through dense voxel grids that sample the object's entire time-space coordinates, we only propagate through the DINR at a small subset of object coordinates in each iteration resulting in an order-of-magnitude reduction in memory and compute for training. DINR leverages distributed computation across several compute nodes and GPUs to produce high-fidelity 4D time-space reconstructions. We use both simulated parallel-beam and experimental cone-beam X-ray CT datasets to demonstrate the superior performance of our approach.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Analysis of Narrow Bipolar Events Using Mode Decomposition Methods

Multi-resolution analysis methods can reveal the underlying physical dynamics of nonstationary signals, such as those from lightning. In this paper we demonstrate the application of two multi-resolution analysis methods: Ensemble Empirical Mode Decomposition (EEMD) and Variational Mode Decomposition (VMD) in a comparative way in the analysis of electric field change waveforms from lightning. EEMD and VMD decompose signals into a set of Intrinsic Mode Functions (IMFs). The IMFs can be combined using distance and divergence metrics to obtain noise reduction or to obtain new waveforms that isolate the physical processes of interest while removing irrelevant components of the original signal. We apply the EEMD and VMD methods to the observations of three close Narrow Bipolar Events (NBEs) that were reported by Rison et al. The ΔE observations reveal the occurrence of complex oscillatory processes after the main NBE sferic. We show that both EEMD and VMD are able to isolate the oscillations from the main NBE, with VMD being more effective of the two methods since it requires the least user supervision. The oscillations are found to begin at the end of the NBEs' downward fast positive breakdown and appear to be produced by a half-wavelength standing wave within a weakly-conducting resonant ionization cavity left behind in the wake of the streamer-based NBE event. In conclusion, additional analysis shows that one of the NBEs was likely initiated by an energetic cosmic ray shower, and also corrects a misinterpretation in the literature that fast breakdown is an artifact of NBE-like events in interferometer observations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2017

New-Generation NASA Aura Ozone Monitoring Instrument (OMI) Volcanic SO2 Dataset: Algorithm Description, Initial Results, and Continuation with the Suomi-NPP Ozone Mapping and Profiler Suite (OMPS)

Since the fall of 2004, the Ozone Monitoring Instrument (OMI) has been providing global monitoring of volcanic SO2 emissions, helping to understand their climate impacts and to mitigate aviation hazards. Here we introduce a new-generation OMI volcanic SO2 dataset based on a principal component analysis (PCA) retrieval technique. To reduce retrieval noise and artifacts as seen in the current operational linear fit (LF) algorithm, the new algorithm, OMSO2VOLCANO, uses characteristic features extracted directly from OMI radiances in the spectral fitting, thereby helping to minimize interferences from various geophysical processes (e.g., O3 absorption) and measurement details (e.g., wavelength shift). To solve the problem of low bias for large SO2 total columns in the LF product, the OMSO2VOLCANO algorithm employs a table lookup approach to estimate SO2 Jacobians (i.e., the instrument sensitivity to a perturbation in the SO2 column amount) and iteratively adjusts the spectral fitting window to exclude shorter wavelengths where the SO2 absorption signals are saturated. To first order, the effects of clouds and aerosols are accounted for using a simple Lambertian equivalent reflectivity approach. As with the LF algorithm, OMSO2VOLCANO provides total column retrievals based on a set of predefined SO2 profiles from the lower troposphere to the lower stratosphere, including a new profile peaked at 13 km for plumes in the upper troposphere. Examples given in this study indicate that the new dataset shows significant improvement over the LF product, with at least 50% reduction in retrieval noise over the remote Pacific. For large eruptions such as Kasatochi in 2008 (approximately 1700 kt total SO2/ and Sierra Negra in 2005 (greater than 1100DU maximum SO2), OMSO2VOLCANO generally agrees well with other algorithms that also utilize the full spectral content of satellite measurements, while the LF algorithm tends to underestimate SO2. We also demonstrate that, despite the coarser spatial and spectral resolution of the Suomi National Polar-orbiting Partnership (Suomi-NPP) Ozone Mapping and Profiler Suite (OMPS) instrument, application of the new PCA algorithm to OMPS data produces highly consistent retrievals between OMI and OMPS. The new PCA algorithm is therefore capable of continuing the volcanic SO2 data record well into the future using current and future hyperspectral UV satellite instruments.

OMI↗

NASA NTRS1992

Water Relations, Gas Exchange, and Nutrient Response to a Long Term Constant Water Deficit

Wheat plants (Triticum aestivum) were grown for 43 days in a micro-porous tube nutrient delivery system. Roots were unable to penetrate the microporous tube, but grew on the surface and maintained capillary contact with the nutrient solution on the inside of the tube through the 5-micron pores of the porous tube. Water potential in the system was controlled at -0.4, -0.8, and -3.0 kPa by adjusting the applied pressure (hydrostatic head) to the nutrient solution flowing through the microporous tubes. A relatively small decrease in applied water potential from -0.4 to -3.0 kPa resulted in a 34% reduction of shoot growth but only a moderate reduction in the midday leaf water potential from -1.3 to -1.7 MPa. Carbon dioxide assimilation decreased and water use efficiency increased with the more negative applied water potentials, while intercellular CO2 concentration remained constant. This was associated with a decrease in stomatal conductance to water vapor from 1.90 to 0.98 mol/(sq m sec) and a decrease in total apparent hydraulic conductance from 47 to 12 (micro)mol/(sec MPa). Although the applied water potentials were in the -0.4 to -3.0 kPa range, the actual water potential perceived by the plant roots appeared to be in the range of -0.26 to -0.38 MPa as estimated by the leaf water potential of bagged plants. The amount of K, Ca, Mg, Zn, Cu, and B accumulated with each unit of transpired water increased as the applied water potential became less negative. The increase in accumulation ranged from 1.4-fold for K to 2.2-fold for B. The physiological responses observed in this study in response to small constant differences in applied water potentials were much greater than expected from either the applied water potential or the observed plant water potential. Even though the micro-porous tube may not represent natural conditions and could possibly introduce morphological and physiological artifacts, it enables a high degree of control of water potential that facilitates the investigation of many aspects of water relations not practical with other experimental systems.

Berry, Wade L.↗

DOE OSTI2020

Mitigation of LEO Satellite Brightness and Trail Effects on the Rubin Observatory LSST

In this work, we report studies on the mitigation of optical effects of bright low-Earth-orbit (LEO) satellites on Vera C. Rubin Observatory and its Legacy Survey of Space and Time (LSST). These include options for pointing the telescope to avoid satellites, laboratory investigations of bright trails on the Rubin Observatory LSST camera sensors, algorithms for correcting image artifacts caused by bright trails, experiments on darkening SpaceX Starlink satellites, and ground-based follow-up observations. The original Starlink v0.9 satellites are g ~ 4.5 mag, and the initial experiment "DarkSat" is g ~ 6.1 mag. Future Starlink darkening plans may reach g ~ 7 mag, a brightness level that enables nonlinear image artifact correction to well below background noise. However, the satellite trails will still exist at a signal-to-noise ratio ~ 100, generating systematic errors that may impact data analysis and limit some science. For the Rubin Observatory 8.4 m mirror and a satellite at 550 km, the full width at half maximum of the trail is about 3'' as the result of an out-of-focus effect, which helps avoid saturation by decreasing the peak surface brightness of the trail. For 48,000 LEOsats of apparent magnitude 4.5, about 1% of pixels in LSST nautical twilight images would need to be masked.

79 ASTRONOMY AND ASTROPHYSICS↗