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All sources NASA NTRS DOE OSTI

DOE OSTI2021

Filtration Performance of Layering Masks and Face Coverings and the Reusability of Cotton Masks after Repeated Washing and Drying

In this study, filtration efficiency of different respirators, face masks, and a 2-ply cotton handkerchief bandana was compared for particles in the size range of 60 nm-4 um under a "perfect fit" condition. The filtration efficiency at the most penetrating particle size of 0.3 um on average ranged from 83-99% for N95 and KN95 respirators, 42-88% for surgical masks, 16-23% for cloth masks, and 9% for bandana. We also investigated the effects of using double surgical masks or layering a cloth mask over various surgical masks in terms of their filtration characteristics. In most of these combinations, the filtration efficiency improved by ~25% for particles 0.3-1 um in diameter without any substantial change in the filter quality factor when compared to the highest of the individual mask results. To investigate the reusability of cotton cloth masks, 2-layer cotton fabric sample coupons were machine washed and dried for 52 cycles leading to an increase in inhalation resistance (~20 Pa) without affecting size-resolved filtration efficiency. Scanning electron microscopy revealed that washing and drying led to the gradual deconstruction of cotton fibers at the scale of several micrometers to hundreds of nanometers in the form of delamination of the fiber wall and fibrillation of the nanofiber constituents. Results indicate that cloth masks may be layered over surgical masks for additional benefits, and that cloth masks made out of cotton fabric can be washed and reused numerous times without a significant loss in filtration efficiency.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2015

Exoplanet Coronagraph Shaped Pupil Masks and Laboratory Scale Star Shade Masks: Design, Fabrication and Characterization

Star light suppression technologies to find and characterize faint exoplanets include internal coronagraph instruments as well as external star shade occulters. Currently, the NASA WFIRST-AFTA mission study includes an internal coronagraph instrument to find and characterize exoplanets. Various types of masks could be employed to suppress the host star light to about 10 -9 level contrast over a broad spectrum to enable the coronagraph mission objectives. Such masks for high contrast internal coronagraphic imaging require various fabrication technologies to meet a wide range of specifications, including precise shapes, micron scale island features, ultra-low reflectivity regions, uniformity, wave front quality, achromaticity, etc. We present the approaches employed at JPL to produce pupil plane and image plane coronagraph masks by combining electron beam, deep reactive ion etching, and black silicon technologies with illustrative examples of each, highlighting milestone accomplishments from the High Contrast Imaging Testbed (HCIT) at JPL and from the High Contrast Imaging Lab (HCIL) at Princeton University. We also present briefly the technologies applied to fabricate laboratory scale star shade masks.

black silicon↗

NASA NTRS2017

Fabrication of coronagraph masks and laboratory scale star-shade masks: characteristics, defects and performance

NASA WFIRST mission has planned to include a coronagraph instrument to find and characterize exoplanets. Masks are needed to suppress the host star light to better than 10-8 – 10-9 level contrast over a broad bandwidth to enable the coronagraph mission objectives. Such masks for high contrast coronagraphic imaging require various fabrication technologies to meet a wide range of specifications, including precise shapes, micron scale island features, ultra-low reflectivity regions, uniformity, wave front quality, etc. We present the technologies employed at JPL to produce these pupil plane and image plane coronagraph masks, and lab-scale external occulter masks, highlighting accomplishments from the high contrast imaging testbed (HCIT) at JPL and from the high contrast imaging lab (HCIL) at Princeton University. Inherent systematic and random errors in fabrication and their impact on coronagraph performance are discussed with model predictions and measurements.

Casey Wilson, Robert↗

DOE OSTI2022

Exploring the MeV sky with a combined coded mask and Compton telescope: the Galactic Explorer with a Coded aperture mask Compton telescope (GECCO)

The sky at MeV energies is currently poorly explored. Here we present an innovative mission concept that builds upon the heritage of past and current missions improving the sensitivity and, very importantly, the angular resolution. This consists in combining a Compton telescope and a coded-mask telescope. We delineate the motivation for such a concept and we define the scientific goals for such a mission. The Galactic Explorer with a Coded Aperture Mask Compton Telescope (GECCO) is a novel concept for a next-generation telescope covering hard X-ray and soft gamma-ray energies. The potential and importance of this approach that bridges the observational gap in the MeV energy range are presented. With the unprecedented angular resolution of the coded mask telescope combined with the sensitive Compton telescope, a mission such as GECCO can disentangle the discrete sources from the truly diffuse emission. Individual Galactic and extragalactic sources are detected. This also allows to understand the gamma-ray Galactic center excess and the Fermi Bubbles, and to trace the low-energy cosmic rays, and their propagation in the Galaxy. Nuclear and annihilation lines are spatially and spectrally resolved from the continuum emission and from sources, addressing the role of low-energy cosmic rays in star formation and galaxy evolution, the origin of the 511 keV positron line, fundamental physics, and the chemical enrichment in the Galaxy. Such an instrument also detects explosive transient gamma-ray sources, which, in turn, enables identifying and studying the astrophysical objects that produce gravitational waves and neutrinos in a multi-messenger context. By looking at a poorly explored energy band it also allows discoveries of new astrophysical phenomena.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2022

Cloud Mask Intercomparison eXercise (CMIX): An evaluation of cloud masking algorithms for Landsat 8 and Sentinel-2

Cloud cover is a major limiting factor in exploiting time-series data acquired by optical spaceborne remote sensing sensors. Multiple methods have been developed to address the problem of cloud detection in satellite imagery and a number of cloud masking algorithms have been developed for optical sensors but very few studies have carried out quantitative intercomparison of state-of-the-art methods in this domain. This paper summarizes results of the first Cloud Masking Intercomparison eXercise (CMIX) conducted within the Committee Earth Observation Satellites (CEOS) Working Group on Calibration & Validation (WGCV). CEOS is the forum for space agency coordination and cooperation on Earth observations, with activities organized under working groups. CMIX, as one such activity, is an international collaborative effort aimed at intercomparing cloud detection algorithms for moderate-spatial resolution (10–30 m) spaceborne optical sensors. The focus of CMIX is on open and free imagery acquired by the Landsat 8 (NASA/USGS) and Sentinel-2 (ESA) missions. Ten algorithms developed by nine teams from fourteen different organizations representing universities, research centers and industry, as well as space agencies (CNES, ESA, DLR, and NASA), are evaluated within the CMIX. Those algorithms vary in their approach and concepts utilized which were based on various spectral properties, spatial and temporal features, as well as machine learning methods. Algorithm outputs are evaluated against existing reference cloud mask datasets. Those datasets vary in sampling methods, geographical distribution, sample unit (points, polygons, full image labels), and generation approaches (experts, machine learning, sky images). Overall, the performance of algorithms varied depending on the reference dataset, which can be attributed to differences in how the reference datasets were produced. The algorithms were in good agreement for thick cloud detection, which were opaque and had lower uncertainties in their identification, in contrast to thin/semi-transparent clouds detection. Not only did CMIX allow identification of strengths and weaknesses of existing algorithms and potential areas of improvements, but also the problems associated with the existing reference datasets. The paper concludes with recommendations on generating new reference datasets, metrics, and an analysis framework to be further exploited and additional input datasets to be considered by future CMIX activities.

Sergii Skakun↗

NASA NTRS2022

Exploring the MeV Sky With A Combined Coded Mask and Compton Telescope: the Galactic Explorer With A Coded Aperture Mask Compton Telescope (GECCO)

Elena Orlando↗

DOE OSTI2021

DeepGhostBusters: Using Mask R-CNN to Detect and Mask Ghosting and Scattered-Light Artifacts from Optical Survey Images

Wide-field astronomical surveys are often affected by the presence of undesirable reflections (often known as "ghosting artifacts" or "ghosts") and scattered-light artifacts. The identification and mitigation of these artifacts is important for rigorous astronomical analyses of faint and low-surface-brightness systems. However, the identification of ghosts and scattered-light artifacts is challenging due to a) the complex morphology of these features and b) the large data volume of current and near-future surveys. In this work, we use images from the Dark Energy Survey (DES) to train, validate, and test a deep neural network (Mask R-CNN) to detect and localize ghosts and scattered-light artifacts. We find that the ability of the Mask R-CNN model to identify affected regions is superior to that of conventional algorithms and traditional convolutional neural networks methods. We propose that a multi-step pipeline combining Mask R-CNN segmentation with a classical CNN classifier provides a powerful technique for the automated detection of ghosting and scattered-light artifacts in current and near-future surveys.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1964

Note on binaural masking-level differences as a function of the interaural correlation of the masking noise.

Model for interpreting data, describing binaural masked threshold dependence on proportion of noise in masking signals

CROSS CORRELATION↗

DOE OSTI2019

Performance of the Gemini Planet Imager Non-redundant Mask and Spectroscopy of Two Close-separation Binaries: HR 2690 and HD 142527

The Gemini Planet Imager (GPI) contains a 10-hole non-redundant mask (NRM), enabling interferometric resolution in complement to its coronagraphic capabilities. The NRM operates both in spectroscopic (integral field spectrograph, henceforth IFS) and polarimetric configurations. NRM observations were taken between 2013 and 2016 to characterize its performance. Most observations were taken in spectroscopic mode, with the goal of obtaining precise astrometry and spectroscopy of faint companions to bright stars. We find a clear correlation between residual wavefront error measured by the adaptive optic system and the contrast sensitivity by comparing phase errors in observations of the same source, taken on different dates. We find a typical 5σ contrast sensitivity of (2–3) × 10 –3 at $~λ/D$. We explore the accuracy of spectral extraction of secondary components of binary systems by recovering the signal from a simulated source injected into several data sets. We outline data reduction procedures unique to GPI's IFS and describe a newly public data pipeline used for the presented analyses. We demonstrate recovery of astrometry and spectroscopy of two known companions to HR 2690 and HD 142527. NRM+polarimetry observations achieve differential visibility precision of σ ~ 0.4% in the best case. We discuss its limitations on Gemini-S/GPI for resolving inner regions of protoplanetary disks and prospects for future upgrades. We summarize lessons learned in observing with NRM in spectroscopic and polarimetric modes.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Using Mask R-CNN to detect and mask ghosting and scattered-light artifacts in astronomical images

Wide-field astronomical surveys are often affected by the presence of undesirable reflections (often known as “ghosting artifacts” or “ghosts”) and scattered-light artifacts. The identification and mitigation of these artifacts is important for rigorous astronomical analyses of faint and low-surface-brightness systems. In this work, we use images from the Dark Energy Survey (DES) to train, validate, and test a deep neural network (Mask R-CNN) to detect and localize ghosts and scattered- light artifacts. We find that the ability of the Mask R-CNN model to identify affected regions is superior to that of conventional algorithms that model the physical processes that lead to such artifacts, thus providing a powerful technique for the automated detection of ghosting and scattered-light artifacts in current and near-future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

A New Mask for An Old Suspect: Testing the Sensitivity of the Galactic Center Excess to the Point Source Mask

The Fermi-LAT collaboration has recently released a new point source catalog, referred to as 4FGL. For the first time, we perform a template fit using information from this new catalog and find that the Galactic center excess is still present. On the other hand, we find that a wavelet-based search for point sources is highly sensitive to the use of the 4FGL catalog: no excess of bright regions on small angular scales is apparent when we mask out 4FGL point sources. We postulate that the 4FGL catalog contains the large majority of bright point sources that have previously been suggested to account for the excess in gamma rays detected at the Galactic center in Fermi-LAT data. Furthermore, after identifying which bright sources have no known counterpart, we place constraints on the luminosity function necessary for point sources to explain the smooth emission seen in the template fit.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Multiscale Effects Masked the Impact of the COVID-19 Pandemic on Electricity Demand in the United States

Shelter-in-place orders and business closures related to COVID-19 changed the hourly profile of electricity demand and created an unprecedented source of uncertainty for the grid. The potential for continued shifts in electricity profiles has implications for electricity sector investment and operating decisions that maintain reserve margins and provide grid reliability. This study reveals that understanding this uncertainty requires an understanding of the underlying drivers at the customer-class scale. This paper utilizes three datasets to compare the impacts of COVID-19 on electricity consumption across a range of spatiotemporal and customer scales. At the utility/customer-class scale, COVID-19-induced shutdowns in the spring of 2020 shifted weekday residential load profiles to resemble weekend profiles from previous years. Total commercial loads declined, but the commercial diurnal load profile was unchanged. With only total loads available at the balancing authority scale, the apparent impact of COVID-19 was smaller during the summer due in part to phased re-opening and spatial variability in re-opening, but there were still clear variations once total loads were broken down zonally. Monthly data at the state scale showed an increase in state-level residential electricity sales, a decrease in commercial sales, and a small net decrease in total sales in most states from April-August 2020. Analyses that focus on total load or a single scale may miss important changes that become apparent when the load is broken down regionally or by customer class.

COVID-19, electricity demand, multiscale, Commonwe↗

DOE OSTI2022

DeepGhostBusters: Using Mask R-CNN to detect and mask ghosting and scattered-light artifacts from optical survey images

Not Available

Tanoglidis, D.↗

DOE OSTI2021

Evaluating Automated Face Identity-Masking Methods with Human Perception and a Deep Convolutional Neural Network

Face de-identification (or “masking”) algorithms have been developed in response to the prevalent use of video recordings in public places. Here, we evaluated the success of face identity masking for human perceivers and a deep convolutional neural network (DCNN). Eight de-identification algorithms were applied to videos of drivers’ faces, while they actively operated a motor vehicle. These masks were pre-selected to be applicable to low-quality video and to maintain coarse information about facial actions. Humans studied high-resolution images to learn driver identities and were tested on their recognition of active drivers in low-resolution videos. Faces in the videos were either unmasked or were masked by one of the eight algorithms. When participants were tested immediately after learning (Experiment 1), all masks reduced identification, with six of eight masks reducing identification to extremely poor performance. In a second experiment, two of the most effective masks were tested after a delay of 7 or 28 days. The delay did not further reduce identification of the masked faces. In all masked conditions, participants maintained stringent decision criteria, with low confidence in recognition, further indicating the effectiveness of the masks. Next, the DCNN performed an identity-matching task between high-resolution images and masked videos—a task analogous to that done by humans. The pattern of accuracy for the DCNN mirrored some, but not all, aspects of human performance, highlighting the need to test the effectiveness of identity masking for both humans and machines. The DCNN was also tested on its ability to match identity between masked and unmasked versions of the same video, based only on the face. DCNN performance for the eight masks offers insight into the nature of the information in faces that is coded in these networks.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2010

Designs and Materials for Better Coronagraph Occulting Masks

New designs, and materials appropriate for such designs, are under investigation in an effort to develop coronagraph occulting masks having broad-band spectral characteristics superior to those currently employed. These designs and materials are applicable to all coronagraphs, both ground-based and spaceborne. This effort also offers potential benefits for the development of other optical masks and filters that are required (1) for precisely tailored spatial transmission profiles, (2) to be characterized by optical-density neutrality and phase neutrality (that is, to be characterized by constant optical density and constant phase over broad wavelength ranges), and/or (3) not to exhibit optical- density-dependent phase shifts. The need for this effort arises for the following reasons: Coronagraph occulting masks are required to impose, on beams of light transmitted through them, extremely precise control of amplitude and phase according to carefully designed transmission profiles. In the original application that gave rise to this effort, the concern has been to develop broad-band occulting masks for NASA s Terrestrial Planet Finder coronagraph. Until now, experimental samples of these masks have been made from high-energy-beam-sensitive (HEBS) glass, which becomes locally dark where irradiated with a high-energy electron beam, the amount of darkening depending on the electron-beam energy and dose. Precise mask profiles have been written on HEBS glass blanks by use of electron beams, and the masks have performed satisfactorily in monochromatic light. However, the optical-density and phase profiles of the HEBS masks vary significantly with wavelength; consequently, the HEBS masks perform unsatisfactorily in broad-band light. The key properties of materials to be used in coronagraph occulting masks are their extinction coefficients, their indices of refraction, and the variations of these parameters with wavelength. The effort thus far has included theoretical predictions of performances of masks that would be made from alternative materials chosen because the wavelength dependences of their extinction coefficients and their indices of refraction are such that that the optical-density and phase profiles of masks made from these materials can be expected to vary much less with wavelength than do those of masks made from HEBS glass. The alternative materials considered thus far include some elemental metals such as Pt and Ni, metal alloys such as Inconel, metal nitrides such as TiN, and dielectrics such as SiO2. A mask as now envisioned would include thin metal and dielectric films having stepped or smoothly varying thicknesses (see figure). The thicknesses would be chosen, taking account of the indices of refraction and extinction coefficients, to obtain an acceptably close approximation of the desired spatial transmittance profile with a flat phase profile

Balasubramanian, Kunjithapatham↗

NASA NTRS1997

Calibration of a Spatial-Temporal Discrimination Model from Forward, Simultaneous, and Backward Masking

We have been developing a simplified spatial-temporal discrimination model similar to our simplified spatial model in that masking is assumed to be a function of the local visible contrast energy. The overall spatial-temporal sensitivity of the model is calibrated to predict the detectability of targets on a uniform background. To calibrate the spatial-temporal integration functions that define local visible contrast energy, spatial-temporal masking data are required. Observer thresholds were measured (2IFC) for the detection of a 12 msec target stimulus in the presence of a 700 msec mask. Targets were 1, 3 or 9 c/deg sine wave gratings. Masks were either one of these gratings or two of them combined. The target was presented in 17 temporal positions with respect to the mask, including positions before, during and after the mask. Peak masking was found near mask onset and offset for 1 and 3 c/deg targets, while masking effects were more nearly uniform during the mask for the 9 c/deg target. As in the purely spatial case, the simplified model can not predict all the details of masking as a function of masking component spatial frequencies, but overall the prediction errors are small.

Ahumada, Albert J.↗

DOE OSTI2023

Accurate estimation of angular power spectra for maps with correlated masks

A common procedure when analyzing maps of the cosmic microwave background (CMB) or other cosmological signals is the need to remove ("mask") regions of the maps that are heavily contaminated, e.g., by non-cosmological foreground emission. After applying such a mask, one must account for its effect when inferring statistical properties of interest, such as the angular power spectrum of the field in the original map. A widely used approach to correct for such mask-induced effects was presented by Hivon et al. (2002), now widely known as the "MASTER" formalism. However, it is often the case that the map and mask are correlated in some way, such as point source masks used in CMB analyses, which have nonzero correlation with CMB secondary anisotropy fields and other mm-wave sky signals. In such situations, the MASTER approach gives biased results, as it assumes that the unmasked map and mask have zero correlation. While such effects have been discussed before with regard to specific physical models, here we derive a completely general formalism for any case where the map and mask are correlated. We show that our result ("reMASTERed") reconstructs ensemble-averaged angular power spectra to effectively exact precision, with significant improvements over traditional estimators for cases where the map and mask are correlated. An important consequence of our result is that for maps with correlated masks, it is no longer possible to invert a simple equation to obtain the true power spectrum from the observed (masked) power spectrum. Instead, our result necessitates the use of forward modeling from theory space into the observable domain of the masked power spectrum. We publicly release our software implementation of these results.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Extended use of face masks during the COVID-19 pandemic - Thermal conditioning and spray-on surface disinfection

The current COVID-19 pandemic has resulted in globally constrained supplies for face masks and personal protective equipment (PPE). Production capacity is limited in many countries and the future course of the pandemic will likely continue with shortages for high quality masks and PPE in the foreseeable future. Therefore, expectations are that mask reuse, extended wear and similar approaches will enhance the availability of personal protective measures. Repeated thermal disinfection could be an important option and likely easier implemented in some situations, at least on the small scale, than UV illumination, irradiation or hydrogen peroxide vapor exposure. In this paper, an overview on thermal responses and ongoing filtration performance of multiple face mask types is provided. Most masks have adequate material properties to survive a few cycles (i.e. 30 min disinfection steps) of thermal exposure in the 75°C regime. Some are more easily affected, as seen by the fusing of plastic liner or warping, given that preferred conditioning temperatures are near the softening point for some of the plastics and fibers used in these masks. Hence adequate temperature control is equally important. As guidance, disinfectants sprayed via dilute solutions maintain a surface presence over extended time at 25 and 37°C. Some spray-on alcohol-based solutions containing disinfectants were gently applied to the top surface of masks. Neither moderate thermal aging (less than 24 h at 80 and 95°C) nor gentle application of surface disinfectant sprays resulted in measurable loss of mask filter performance. Subject to bio-medical concurrence (additional checks for virus kill efficiency) and the use of low risk non-toxic disinfectants, such strategies, either individually or combined, by offering additional anti-viral properties or short term refreshing, may complement reuse options of professional masks or the now ubiquitous custom-made face masks with their often unknown filtration effectiveness.

36 MATERIALS SCIENCE↗