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Real time monitoring of COVID-19 intervention effectiveness through contact tracing data

Communities worldwide have used vaccines and facemasks to mitigate the COVID-19 pandemic. When an individual opts to vaccinate or wear a mask, they may lower their own risk of becoming infected as well as the risk that they pose to others while infected. The first benefit–reducing susceptibility–has been established across multiple studies, while the second–reducing infectivity–is less well understood. Using a new statistical method, we estimate the efficacy of vaccines and facemasks at reducing both types of risks from contact tracing data collected in an urban setting. We find that vaccination reduced the risk of onward transmission by 40.7% [95% CI 25.8–53.2%] during the Delta wave and 31.0% [95% CI 19.4–40.9%] during the Omicron wave and that mask wearing reduced the risk of infection by 64.2% [95% CI 5.8–77.3%] during the Omicron wave. By harnessing commonly-collected contact tracing data, the approach can broadly provide timely and actionable estimates of intervention efficacy against a rapidly evolving pathogen.

60 APPLIED LIFE SCIENCES↗

Characterization of a 2016-2017 Human Seasonal H3 Influenza A Virus Spillover Now Endemic to U.S. Swine

In 2017, the Iowa State University Veterinary Diagnostic Laboratory detected a reverse-zoonotic transmission of a human seasonal H3 influenza A virus into swine (IAV-S) in Oklahoma. Pairwise comparison between the recently characterized human seasonal H3 IAV-S (H3.2010.2) hemagglutinin (HA) sequences detected in swine and the most similar 2016–2017 human seasonal H3 revealed 99.9% nucleotide identity. To elucidate the origin of H3.2010.2 IAV-S, 45 HA and 27 neuraminidase (NA) sequences from 2017 to 2020 as well as 11 whole-genome sequences (WGS) were genetically characterized. Time to most recent common human ancestor was estimated between August and September 2016. The N2 NA was of human origin in all but one strain from diagnostic submissions with NA sequences, and the internal gene segments from WGS consisted of matrix genes originating from the 2009 pandemic H1N1 and another 5 internal genes of triple reassortant swine origin (TTTTPT). Pigs experimentally infected with H3.2010.2 demonstrated efficient nasal shedding and replication in the lungs, mild pneumonia, and minimal microscopic lung lesions and transmitted the virus to indirect contact swine. Antigenically, H3.2010.2 viruses were closer to a human seasonal vaccine strain, A/Hong Kong/4801/2014, than to the H3.2010.1 human seasonal H3 viruses detected in swine in 2012. This was the second sustained transmission of a human seasonal IAV into swine from the 2010 decade after H3.2010.1. Monitoring the spillover and detection of novel IAV from humans to swine may help vaccine antigen selection and could impact pandemic preparedness.

59 BASIC BIOLOGICAL SCIENCES↗

A Hands-On Curriculum for Training in HPC Cluster Deployment and Management

This paper presents the design, methodology, and outcomes of the High-Performance Computing Technologies (HPCT) course, a hands-on training program focused on the system-side of HPC cluster deployment and administration. Delivered as part of the Master in High Performance Computing (MHPC) program, the course introduces students to key concepts in cluster configuration, including networking, software stack provisioning, job scheduling, and monitoring. Initially taught in person, the course was transitioned to an online format during the COVID-19 pandemic. This shift led to the development of openly available instructional material and a flipped-classroom approach that continues to support both in-person and hybrid delivery. All course materials are publicly available at www.hpc.temple.edu/mhpc/hpc-technology/index.html. By documenting the structure, infrastructure, and evolution of HPCT, this paper offers a model for accessible HPC system training that supports workforce development in computational science.

Posada Correa, Fernando [ORNL] (ORCID:000000022565↗

COVID-19 pandemic reveals persistent disparities in nitrogen dioxide pollution

We leverage the unparalleled changes in human activity during COVID-19 and the unmatched capabilities of the TROPOspheric Monitoring Instrument to understand how lockdowns impact ambient nitrogen dioxide (NO 2 ) pollution disparities in the United States. The least White communities experienced the largest NO 2 reductions during lockdowns; however, disparities between the least and most White communities are so large that the least White communities still faced higher NO 2 levels during lockdowns than the most White communities experienced prior to lockdowns, despite a ~50% reduction in passenger vehicle traffic. Similar findings hold for ethnic, income, and educational attainment population subgroups. Future strategies to reduce NO 2 disparities will need to target emissions from heavy-duty vehicles.

TROPOMI↗

Spatial Variation of Fine Particulate Matter Levels in Nairobi Before and During the COVID-19 Curfew: Implications for Environmental Justice

The temporary decrease of fine particulate matter (PM(sub 2.5)) concentrations in many parts of the world due to the COVID-19 lockdown spurred discussions on urban air pollution and health. However there has been little focus on sub-Saharan Africa, as few African cities have air quality monitors and if they do, these data are often not publicly available. Spatial differentials of changes in PM(sub 2.5) concentrations as a result of COVID also remain largely unstudied. To address this gap, we use a serendipitous mobile air quality monitoring deployment of eight Sensirion SPS 30 sensors on motorbikes in the city of Nairobi starting on 16 March 2020, before a COVID-19 curfew was imposed on 25 March and continuing until 5 May 2020. We developed a random-forest model to estimate PM(sub 2.5) surfaces for the entire city of Nairobi before and during the COVID-19 curfew. The highest PM(sub 2.5) concentrations during both periods were observed in the poor neighborhoods of Kariobangi, Mathare, Umoja, and Dandora, located to the east of the city center. Changes in PM(sub 2.5) were heterogeneous over space. PM(sub 2.5) concentrations increased during the curfew in rapidly urbanizing, the lower-middle-class neighborhoods of Kahawa, Kasarani, and Ruaraka, likely because residents switched from LPG to biomass fuels due to loss of income. Our results indicate that COVID-19 and policies to address it may have exacerbated existing air pollution inequalities in the city of Nairobi. The quantitative results are preliminary, due to sampling limitations and measurement uncertainties, as the available data came exclusively from low-cost sensors. This research serves to highlight that spatial data that is essential for understanding structural inequalities reflected in uneven air pollution burdens and differential impacts of events like the COVID pandemic. With the help of carefully deployed low cost sensors with improved spatial sampling and at least one reference-quality monitor for calibration, we can collect data that is critical for developing targeted interventions that address environmental injustice in the African context.

Environmental justice↗

TDCOSMO - XVII. New time delays in 22 lensed quasars from optical monitoring with the ESO-VST 2.6m and MPG 2.2m telescopes

We present new time delays, the main ingredient of time delay cosmography, for 22 lensed quasars resulting from high-cadence r-band monitoring on the 2.6 m ESO VLT Survey Telescope and Max-Planck-Gesellschaft 2.2 m telescope. Each lensed quasar was typically monitored for one to four seasons, often shared between the two telescopes to mitigate the interruptions forced by the COVID-19 pandemic. The sample of targets consists of 19 quadruply and 3 doubly imaged quasars, which received a total of 1918 hours of on-sky time split into 21 581 wide-field frames, each 320 seconds long. In a given field, the 5-σ depth of the combined exposures typically reaches the 27th magnitude, while that of single visits is 24.5 mag – similar to the expected depth of the upcoming Vera-Rubin LSST. The fluxes of the different lensed images of the targets were reliably de-blended, providing not only light curves with photometric precision down to the photon noise limit, but also high-resolution models of the targets whose features and astrometry were systematically confirmed in Hubble Space Telescope imaging. This was made possible thanks to a new photometric pipeline, lightcurver, and the forward modelling method STARRED. Finally, the time delays between pairs of curves and their uncertainties were estimated, taking into account the degeneracy due to microlensing, and for the first time the full covariance matrices of the delay pairs are provided. Of note, this survey, with 13 square degrees, has applications beyond that of time delays, such as the study of the structure function of the multiple high-redshift quasars present in the footprint at a new high in terms of both depth and frequency. The reduced images will be available through the European Southern Observatory Science Portal.Key words: methods: data analysis / surveys / distance scale

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development of Large Scale Extrusion Deposition for Structural Applications

Large Scale Extrusion Deposition (LSED) is an evolving additive manufacturing (AM) technology that research, such as that taking place at Oak Ridge National Laboratory (ORNL) and companies like Local Motors, are continuing to utilize and develop new applications. A major LSED application of interest has been molds and tooling as it allows for much shorter production time and lower cost. However, interest has been expanding into using LSED for more structural applications due to more frequent use of high performing polymer composites as feedstock. The use of LSED for structural applications is of particular interest to Local Motors as it is currently being used to create commercially viable, energy efficient electric vehicles. LSED offers a unique opportunity when compared to traditional manufacturing methods as it can significantly reduce the number of components necessary, while decreasing embodied energy and carbon emissions. Even with these benefits however, it is important that LSED is properly understood from a structural aspect as this field has not been as heavily researched as tooling. To ensure a high level of safety and repeatability is an essential responsibility of a manufacturer whose products are structural in nature. As such it is important to understand the materials and LSED process to make structural objects that the manufacturer can be confident in. The main goals of this project were to: develop and investigate materials that are of interest for structural LSED applications, further develop and understand the current machines used in LSED and develop simulations tools of LSED and the mechanical properties of the created structure. Material development focused on composite materials that have high mechanical properties and are stable in a variety of environments. The materials were tested to determine their as printed mechanical and thermal properties as these are necessary for simulations. Once the materials were investigated thoroughly, it allowed for simulations to be performed to compare to experimental data with simulations. Materials were also vetted to determine candidates for multi-material printing. The machine development focused around the areas of process monitoring, non-destructive evaluation, and quality control. Finally, the goal of the simulations was to develop a realistic model of printed structures, including in-process simulation and dynamic simulation. The routes to get to some of these goals and the depth in which they were investigated changed throughout the project due to personnel changes and the COVID-19 pandemic. This project resulted in many valuable results such as the development of an nondestructive evaluation (NDE) technique for interlayer defects, proof of simulation for warpage in simple parts, the development and utilization of a profilometer to monitor a print for defects or inconsistencies, thorough investigation of a material used commercially for structural LSED applications and valuable experimental data on the applicability and advantages of multi-material crush structures versus their neat counterparts by creation and testing of samples.

36 MATERIALS SCIENCE↗

BioSecure Digital Twin: Manufacturing Innovation and Cybersecurity Resilience

U.S. national security, prosperity, economy, and well-being require secure, flexible, and resilient Biopharmaceutical Manufacturing. The COVID-19 pandemic reaffirmed that the biomedical production value-chain is vulnerable to disruption and has been under attack from sophisticated nation-state adversaries. Current cyber defenses are inadequate, and the integrity of critical production systems and processes are inherently vulnerable to cyber-attacks, human error, and supply chain disruptions. The following chapter explores how a BioSecure Digital Twin will improve U.S. manufacturing resilience and preparedness to respond to these hazards by significantly improving monitoring, integrity, security, and agility of our manufacturing infrastructure and systems. The BioSecure Digital Twin combines a scalable manufacturing framework with a robust platform for monitoring and control to increase U.S. biopharma manufacturing resilience. Then, the chapter discusses some of the inherent vulnerabilities and challenges at the nexus of health and advanced manufacturing. Next, the chapter highlights that as the Pandemic evolves, we need agility and resilience to overcome significant obstacles. This section highlights an innovative application of Cyber Informed Engineering to developing and deploying a BioSecure Digital Twin to improve the resilience and security of the biopharma industrial supply chain and production processes. Finally, the chapter concludes with a process framework to complement the Digital Twin platform, called the Biopharma (Observe, Orient, Decide, Act) OODA Loop Framework (BOLF), a four-step approach to decision-making outputs from the Digital Twin. The BOLF will help end users leverage twin technology by distilling the available information, focusing the data on context, and rapidly making the best decision while remaining cognizant of changes that can be made as more data becomes available.

99 GENERAL AND MISCELLANEOUS↗

Mining and Validating Social Media Data for COVID-19–Related Human Behaviors Between January and July 2020: Infodemiology Study

Background: Health authorities can minimize the impact of an emergent infectious disease outbreak through effective and timely risk communication, which can build trust and adherence to subsequent behavioral messaging. Monitoring the psychological impacts of an outbreak, as well as public adherence to such messaging, is also important for minimizing long-term effects of an outbreak. Objective: We used social media data from Twitter to identify human behaviors relevant to COVID-19 transmission, as well as the perceived impacts of COVID-19 on individuals, as a first step toward real-time monitoring of public perceptions to inform public health communications. Methods: We developed a coding schema for 6 categories and 11 subcategories, which included both a wide number of behaviors as well codes focused on the impacts of the pandemic (eg, economic and mental health impacts). We used this to develop training data and develop supervised learning classifiers for classes with sufficient labels. Classifiers that performed adequately were applied to our remaining corpus, and temporal and geospatial trends were assessed. We compared the classified patterns to ground truth mobility data and actual COVID-19 confirmed cases to assess the signal achieved here. Results: We applied our labeling schema to approximately 7200 tweets. The worst-performing classifiers had F1 scores of only 0.18 to 0.28 when trying to identify tweets about monitoring symptoms and testing. Classifiers about social distancing, however, were much stronger, with F1 scores of 0.64 to 0.66. We applied the social distancing classifiers to over 228 million tweets. We showed temporal patterns consistent with real-world events, and we showed correlations of up to –0.5 between social distancing signals on Twitter and ground truth mobility throughout the United States. Conclusions: Behaviors discussed on Twitter are exceptionally varied. Twitter can provide useful information for parameterizing models that incorporate human behavior, as well as for informing public health communication strategies by describing awareness of and compliance with suggested behaviors.

60 APPLIED LIFE SCIENCES↗

SARS-CoV-2 Monitoring in Wastewater Reveals Novel Variants and Biomarkers of Infection

Wastewater-based epidemiology (WBE) is a popular tool for the early indication of community spread of infectious diseases. WBE emerged as an effective tool during the COVID-19 pandemic and has provided meaningful information to minimize the spread of infection. Here, we present a combination of analyses using the correlation of viral gene copies with clinical cases, sequencing of wastewater-derived RNA for the viral mutants, and correlative analyses of the viral gene copies with the bacterial biomarkers. Our study provides a unique platform for potentially using the WBE-derived results to predict the spread of COVID-19 and the emergence of new variants of concern. Further, we observed a strong correlation between the presence of SARS-CoV-2 and changes in the microbial community of wastewater, particularly the significant changes in bacterial genera belonging to the families of Lachnospiraceae and Actinomycetaceae . Our study shows that microbial biomarkers could be utilized as prediction tools for future infectious disease surveillance and outbreak responses. Overall, our comprehensive analyses of viral spread, variants, and novel bacterial biomarkers will add significantly to the growing body of literature on WBE and COVID-19.

59 BASIC BIOLOGICAL SCIENCES↗

Ultra Long-Lived, Self-Surveying Autonomous Air Quality Sensing - Executive Summary

We set out to evolve ultra-low power air quality sensing technologies developed at JSC to add a highly accurate positioning sensor based on SBIR technology to give a self-surveying air quality monitoring platform with years-long lifetime on a small, disposable coin cell battery. Using Radio Frequency Identification (RFID) technology for data transport, the system can take advantage of RFID-based inventory management systems in place on lunar exploration assets to provide this capability with extremely small SWAP impacts. Years-long operational lifetimes enable flexible, autonomous environmental monitoring during lengthy intervals between and unprecedented situational awareness during crewed missions. Software integration of the localization system into the JSC RFID sensing platform was advanced, but the COVID-19 pandemic complicated and slowed maturation of the localization system SBIR product, and center closure indefinitely deferred a final hardware integration and system demonstration. In the meantime, progress was made to mature the air-quality sensing platform for flight, including hardware, software, antenna, and mechanical improvements. The underlying RFID sensing capability was also adapted to a drawer motion sensing system, which is currently (FY21) being taken toward an ISS flight demonstration as part of the RFID Enhanced Autonomous Logistics Management (REALM)-3 experiment.

Raymond Summers Wagner↗

2021 Annual Site Environmental Report

This report provides the U.S. Department of Energy (DOE) and the public with information on the level of radioactive and non-radioactive pollutants (if any) that are added to the environment as a result of Princeton Plasma Physics Laboratory’s (PPPL) operations. The results of PPPL’s 2021 environmental surveillance and monitoring program are presented and discussed. The report also summarizes environmental initiatives, assessments, and community involvement programs that were undertaken in 2021. PPPL’s on-site operations were significantly curtailed in 2021 due to the global coronavirus pandemic. PPPL has engaged in fusion energy research since 1951. The Laboratory’s mission is to develop the scientific knowledge and advanced engineering to enable fusion to power the U.S. and the world, and to developing the understanding of plasmas from the nano- to the astrophysical scale. PPPL’s primary experiment, the National Spherical Torus Experiment-Upgrade (NSTX-U) is a collaboration among national laboratories, universities, and national and international research institutions and is a major element in the US Fusion Energy Sciences Program. Its design tests the physics principles of spherical torus (ST) plasmas, playing an important role in the development of smaller, more economical fusion reactors. Due to previous operational issues, NSTX-U did not operate in 2021. PPPL is engaged in a project to replace key NSTX-U components and systems to enable operation of this international fusion user facility. In 2021, PPPL’s radiological environmental monitoring program measured tritium in the air at the NSTX-U Stack and at onsite sampling stations. Using highly sensitive air monitors, PPPL is capable of detecting small changes in the ambient levels of tritium. The operation of an in-stack monitor located on D-site is used to demonstrate compliance with the National Emission Standard for Hazardous Air Pollutants (NESHAPs) regulations. Also included in PPPL’s radiological environmental monitoring program, are water monitoring – ground, surface, and waste waters. PPPL’s radiological monitoring program characterized the background levels of tritium in the environment and those data are presented in this report. Ground water monitoring continued under New Jersey Department of Environmental Protection’s (NJDEP) Site Remediation Program regulations. PPPL monitored for non-radiological contaminants, mainly volatile organic compounds (components of common degreasing solvents). In 2021, PPPL complied with permit limits for surface and sanitary discharges. PPPL was honored with awards for EPEAT-certified electronics purchasing and use of peracetic acid as an alternative water treatment chemical in its non-potable process water systems an NJDEP recycling award.

54 ENVIRONMENTAL SCIENCES↗

2022 Annual Site Environment Report, Princeton Plasma Physics Laboratory

This report provides the U.S. Department of Energy (DOE) and the public with information on the level of radioactive and non-radioactive pollutants (if any) that are added to the environment as a result of Princeton Plasma Physics Laboratory’s (PPPL) operations. This report fulfills the annual public reporting requirements of DOE Order 231.1B. The results of PPPL’s 2022 environmental surveillance and monitoring program are presented and discussed. The report also summarizes environmental initiatives, assessments, and community involvement programs that were undertaken in 2022. PPPL’s on-site operations started to be restored in 2022, following curtailments in 2020 and 2021 for the global coronavirus (COVID-19) pandemic. PPPL has engaged in fusion energy research since 1951 and at its current locations since 1958. The Laboratory’s mission is to develop the scientific knowledge and advanced engineering to enable fusion to power the U.S. and the world, and to develop the understanding of plasmas from the nano- to the astrophysical scale. PPPL’s primary experiment, the National Spherical Torus Experiment-Upgrade (NSTX-U) is a collaboration among national laboratories, universities, and national and international research institutions and is a major element in the US Fusion Energy Sciences Program. Its design tests the physics principles of spherical torus (ST) plasmas, playing an important role in the development of smaller, more economical fusion reactors. Due to previous operational issues, NSTX-U did not operate in 2022. PPPL is engaged in a project to replace key NSTX-U components and systems to enable the operation of this international magnetic fusion user facility. In 2022, PPPL’s radiological environmental monitoring program measured tritium in the air at onsite sampling stations. Using highly sensitive air monitors, PPPL is capable of detecting small changes in the ambient levels of tritium. The operation of monitors located on D-site is used to demonstrate compliance with the National Emission Standard for Hazardous Air Pollutants (NESHAPs) regulations. Also included in PPPL’s radiological environmental monitoring program, are water monitoring – ground, surface, and waste waters. PPPL’s radiological monitoring program characterized the background levels of tritium in the environment and those data are presented in this report. Ground water monitoring continued under New Jersey Department of Environmental Protection’s (NJDEP) Site Remediation Program regulations. PPPL monitored for non-radiological contaminants, mainly volatile organic compounds (components of common degreasing solvents). In 2022, PPPL complied with permit limits for surface water and sanitary wastewater discharges. PPPL was honored with an award for EPEAT-certified electronics purchasing from the Global Electronics Council.

54 ENVIRONMENTAL SCIENCES↗

Has NO(2) in Metropolitan Areas Returned to Pre-COVID-19 Levels as Measured by OMI Satellite Data?

Nitrogen oxides (NOx = NO + NO2) are primarily emitted through the combustion of fossil fuels, such as automobiles and power plants. NOx can contribute to chemical reactions that produce ozone and fine particulate matter (PM2.5) pollution. Using tropospheric vertical column density (TVCD) NO2 data from satellite hyperspectral instruments, such as the Ozone Monitoring Instrument (OMI) on board NASA’s EOS Aura satellite, one can monitor changes in NO2 pollution during “black-swan” events, such as mobility restrictions during COVID-19 lockdowns. Our OMI team has created the Global Nitrogen Dioxide Monitoring Home Page (https://so2.gsfc.nasa.gov/no2/no2_index.html ) where we display NO2 TVCD time series, animated maps, and COVID-specific NO2 anomalies comparing to a pre-COVID five-year average for 317 cities and regions around the world. During the pandemic as a result of the widespread lockdowns, many areas saw low NO2 anomalies superimposed on the natural weather related NO2 changes, such as seasonal NO2 cycle. Has NO2 levels returned to pre-Covid-19 levels in large metropolitan areas? We analyze NO2 time series from March through September for the years 2020-2023 using as a reference the average NO2 from 2015-2019 for those months. We will present data from selected cities that represent all countries.

Keith D Evans↗

PMEL Passive Acoustics Research: Quantifying the Ocean Soundscape from Whales to Wave Energy

Passive acoustic monitoring of the global ocean has increased dramatically over the last decade, providing insights into seasonal sea ice and wind/wave variability, biodiversity, geophysical hazards, and anthropogenic noise impacts. All of these phenomena are sentinels of marine ecosystem health and ocean climate change. Recognizing the utility of underwater sound, the Pacific Marine Environmental Laboratory (PMEL) formed a passive acoustic research program with the goal of quantifying deep-ocean and coastal soundscapes in support of NOAA’s mission to conserve and manage marine ecosystems. PMEL Acoustics Program researchers have built a stable of novel ocean technologies, including autonomous stationary hydrophones, mobile platforms, and near-real-time surface buoys with satellite communication capability. These passive acoustic monitoring systems have been deployed in every major ocean basin on Earth, enabling significant advancements in understanding of natural and anthropogenic sounds. This progress includes evaluation of human-made sound levels across US waters, observations of ship noise fluctuations during the COVID-19 pandemic, and evaluation of noise levels from offshore wave-energy devices. Progress in natural sound research includes assessment of seasonal variability in the presence of endangered cetacean species due to population recovery and/or changing ocean temperatures as well as early detection of the collapse of an Antarctic ice shelf.

54 ENVIRONMENTAL SCIENCES↗

Hazards of Lunar Surface Exploration: Determining the Immunogenicity/Allergenicity of Lunar Dust

There are multiple Apollo program reports of lunar dust (LD) exposure leading to significant upper respiratory symptoms in select crewmembers. Possible mechanisms include particulate irritation, oxidization and release of noxious gas, or legitimate adaptive immune-mediated response. Although sterile non-protein matter would not be expected to be an allergen, one Apollo flight surgeon reported increasing symptoms upon repeated exposure, with associated eosinophilia indicative of allergy (*Acta Astronautica. 2008 63 (7–10): 980–987). Many ISS crews display a pattern of persistent immune system dysregulation and latent virus reactivation (NPJ Microgravity. 2015 Sep 3; 1:15013; NPJ Microgravity. 2017 Apr 12; 3:11). Some ISS crews manifest atypical respiratory and/or dermatitis symptoms which could have an allergic pathogenesis (J Allergy Clin. Immunol. Pract. 2016 Jul-Aug; 4(4):759-762.e8). It is logical to anticipate crew immune dysregulation would worsen during prolonged deep space missions. Planetary surface hazards will only complicate crew health risks. This study hypothesizes that LD exposure can alter susceptible individuals’ immune responses such that repeated exposure will elicit an IgE mediated allergic response either to the LD itself or concomitant antigen exposure during spaceflight. This will adversely increase clinical and operational impacts for long-duration lunar astronauts and affect countermeasure requirements for surface vehicles. Specific aims for this study are (1) Does in vitro LD exposure result in increased histamine from human peripheral blood basophils? (2) Can LD impact the capacity of CD4+ helper and/or CD19+ B-cell mediated IgE production? To address these questions, a set of in-vitro cell culture experiments will be employed (short and long term) using human peripheral blood mononuclear cells (PBMC) and basophils from both atopic and non-atopic individuals, as well as established human basophil and mast cell lines. Cells will be co-cultured with cellular mitogens, common recall antigens (tetanus, Der p1), nickel (as a possible allergenic component of LD), with or without graded amounts of LD, to study whether LD exposure for varying time intervals will alter the generation of selective immune responses associated with clinical allergic reactions. Measured outputs include supernatant-derived IgE, tryptase, histamine and selected cytokine levels. Cellular activation will be monitored by assessing activation markers via flow cytometry. EM/x-ray analysis will be used to determine cellular interactions with dust particles. The minimal amount of LD (Apollo 14 dust) and controls/simulants have been requested. This study, originally planned as an FY20/21 activity, was delayed due to the COVID pandemic. It is now scheduled to be performed during FY22.

Brian Crucian↗

The Completion of a Geosynchronous Earth Orbit Survey with the Eugene Stansbery-Meter Class Autonomous Telescope

The Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT) is the primary optical sensor used by the NASA Orbital Debris Program Office (ODPO) to statistically characterize the geosynchronous Earth orbit (GEO) debris environment and support future Orbital Debris Engineering Model (ORDEM) releases. The ES-MCAT completed its first optical survey of the GEO region from 2020 to 2022. The primary goal of this survey was to autonomously collect and process GEO data with calculated photometric and astrometric uncertainties. A pointing plan was developed to provide uniform sampling within the region of interest (ROI) while accounting for predicted downtime due to insufficient observing conditions. Detections are autonomously correlated to the Space Surveillance Network (SSN) catalog to determine if objects are correlated targets (CTs) or uncorrelated targets (UCTs), the latter of which are of interest for modeling the GEO orbital debris environment. To assess the size detection sensitivity over time and monitor the general performance of the telescope’s optics and software, the optical throughput of the system and limiting magnitudes are evaluated on a routine basis. While the telescope’s ability to operate autonomously and remotely allowed for the GEO survey to continue throughout the COVID-19 pandemic, travel restrictions hampered routine cleaning of the optics during this time, and the primary mirror degraded enough to require recoating. The mirror was removed in 2022, concluding the first GEO survey. The primary mirror received a new coating designed to be more robust against the harsh environment surrounding the ES-MCAT’s location on Ascension Island, accounting for experience gained during operations over the first GEO survey. In early 2023, the recoated primary mirror was reinstalled, and the second GEO survey was initiated. The primary goal of the second GEO survey is to characterize the evolving GEO debris environment with updated optics, software, and pointing strategies while allowing for the inclusion of non-GEO regimes or those that are outside of the ROI. While the pointing method implemented in the first survey allowed for adequate coverage of the ROI over two years, it has been improved to include pointings that avoid the Moon’s position and the galactic plane to reduce software processing time and maximize the detection capabilities of fainter objects. This method also accounts for the changing weather patterns throughout the year and reduces coverage gaps in the ROI. Provided the success of the first two-year GEO survey using autonomous operations, the ODPO is actively collaborating with the United States Space Force (USSF) to make the ES-MCAT a contributing sensor to the SSN. This paper presents results from the first GEO survey including magnitude distributions and orbital parameters for CTs and UCTs. Details are provided for the automated processing pipeline and the optical system throughput for the previous and current primary mirror coatings. In addition, an updated strategy for the second GEO survey to optimize coverage over the ROI is discussed, as are preliminary results from the ongoing second survey.

Corbin Cruz↗

The Completion of a Geosynchronous Earth Orbit Survey with the Eugene Stansbery-Meter Class Autonomous Telescope

The Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT) is the primary optical sensor used by the NASA Orbital Debris Program Office (ODPO) to statistically characterize the geosynchronous Earth orbit (GEO) debris environment and support future Orbital Debris Engineering Model (ORDEM) releases. The ES-MCAT completed its first optical survey of the GEO region from 2020 to 2022. The primary goal of this survey was to autonomously collect and process GEO data with calculated photometric and astrometric uncertainties. A pointing plan was developed to provide uniform sampling within the region of interest (ROI) while accounting for predicted downtime due to insufficient observing conditions. Detections are autonomously correlated to the Space Surveillance Network (SSN) catalog to determine if objects are correlated targets (CTs) or uncorrelated targets (UCTs), the latter of which are of interest for modeling the GEO orbital debris environment. To assess the size detection sensitivity over time and monitor the general performance of the telescope’s optics and software, the optical throughput of the system and limiting magnitudes are evaluated on a routine basis. While the telescope’s ability to operate autonomously and remotely allowed for the GEO survey to continue throughout the COVID-19 pandemic, travel restrictions hampered routine cleaning of the optics during this time, and the primary mirror degraded enough to require recoating. The mirror was removed in 2022, concluding the first GEO survey. The primary mirror received a new coating designed to be more robust against the harsh environment surrounding the ES-MCAT’s location on Ascension Island, accounting for experience gained during operations over the first GEO survey. In early 2023, the recoated primary mirror was reinstalled, and the second GEO survey was initiated. The primary goal of the second GEO survey is to characterize the evolving GEO debris environment with updated optics, software, and pointing strategies while allowing for the inclusion of non-GEO regimes or those that are outside of the ROI. While the pointing method implemented in the first survey allowed for adequate coverage of the ROI over two years, it has been improved to include pointings that avoid the Moon’s position and the galactic plane to reduce software processing time and maximize the detection capabilities of fainter objects. This method also accounts for the changing weather patterns throughout the year and reduces coverage gaps in the ROI. Provided the success of the first two-year GEO survey using autonomous operations, the ODPO is actively collaborating with the United States Space Force (USSF) to make the ES-MCAT a contributing sensor to the SSN. This paper presents results from the first GEO survey including magnitude distributions and orbital parameters for CTs and UCTs. Details are provided for the automated processing pipeline and the optical system throughput for the previous and current primary mirror coatings. In addition, an updated strategy for the second GEO survey to optimize coverage over the ROI is discussed, as are preliminary results from the ongoing second survey.

Corbin Cruz↗