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At least 253 records · Page 14

A review of crack propagation under unsteady loading

The theories and research current available on crack propagation under unsteady loadings, especially those of acoustic origin, are reviewed. Since the original theories on fatigue failure did not account for random loading conditions, modified theories which provide statistical methods for evaluating the random loading have emerged. The impact of acoustic fatigue in the aerospace industry, basic principles such as fatigue crack initiation and propagation and load interactions, and testing procedures are discussed. Attention is also given to metal and metal alloy structures, fiber-reinforced composites and nonmetallic structures, short crack growth, and the effects of temperature, moisture, and corrosion on structures. Suggestions for future research in this field are presented, namely, studies on the effect of 'snap-through' response and associated crack growth patterns, studies in microcrack and 'small crack'; propagation under unsteady loading conditions, and the development of an accurate analytical model to predict acceleration and retardation effects in fatigue crack growth under random loading conditions.

Bryan, H. H.↗

Simulations of Seasonal and Latitudinal Variations in Leaf Inclination Angle Distribution: Implications for Remote Sensing

The leaf inclination angle distribution (LAD) is an important characteristic of vegetation canopy structure affecting light interception within the canopy. However, LADs are difficult and time consuming to measure. To examine possible global patterns of LAD and their implications in remote sensing, a model was developed to predict leaf angles within canopies. Canopies were simulated using the SAIL radiative transfer model combined with a simple photosynthesis model. This model calculated leaf inclination angles for horizontal layers of leaves within the canopy by choosing the leaf inclination angle that maximized production over a day in each layer. LADs were calculated for five latitude bands for spring and summer solar declinations. Three distinct LAD types emerged: tropical, boreal, and an intermediate temperate distribution. In tropical LAD, the upper layers have a leaf angle around 35 with the lower layers having horizontal inclination angles. While the boreal LAD has vertical leaf inclination angles throughout the canopy. The latitude bands where each LAD type occurred changed with the seasons. The different LADs affected the fraction of absorbed photosynthetically active radiation (fAPAR) and Normalized Difference Vegetation Index (NDVI) with similar relationships between fAPAR and leaf area index (LAI), but different relationships between NDVI and LAI for the different LAD types. These differences resulted in significantly different relationships between NDVI and fAPAR for each LAD type. Since leaf inclination angles affect light interception, variations in LAD also affect the estimation of leaf area based on transmittance of light or lidar returns.

Seasonal↗

Natural Language Understanding and Extraction of Flight Constraints Recorded in Letters of Agreement

This paper presents an automated information extraction and inference technique using natural language processing for extracting flight operational procedures and constraints embedded in heritage air traffic management documents. The extracted flight constraints can be digitized and fit into existing airspace information exchange models such as the Aeronautical Information Exchange Model (AIXM). This approach offers a digitized solution to disseminate airspace operating conditions to diverse air users and stakeholders in the National Airspace System (NAS). Furthermore, the digitized flight procedures can provide operational flexibility for emerging advanced air mobility providers and reduce traffic controller workload while maintaining current safety standards. To demonstrate this process, 1,972 Letters of Agreement (LOAs) have been selected for processing, named entity extraction, constraint identification and extraction. This dataset is derived from a subset of documents related to Air Route Traffic Control Centers (ARTCC) operations. We experimented with various traditional information extraction techniques, state-of-the-art machine learning and deep learning models to perform named entity recognition and pattern recognition on our dataset. We present the results from our experiments and demonstrate 99.0% F-1 score for named entity recognition, and a 96.6% accuracy for our entire workflow up to named entity recognition. We also discuss constraint definitions using generic patterned templates and extensions to this work in applying entity linking to digitally extracting relevant constraints.

Natural Language Processing↗

Natural Language Understanding and Extraction of Flight Constraints Recorded in Letters of Agreement

This paper presents an automated information extraction and inference technique using natural language processing for extracting flight operational procedures and constraints embedded in heritage air traffic management documents. The extracted flight constraints can be digitized and fit into existing airspace information exchange models such as the Aeronautical Information Exchange Model (AIXM). This approach offers a digitized solution to disseminate airspace operating conditions to diverse air users and stakeholders in the National Airspace System (NAS). Furthermore, the digitized flight procedures can provide operational flexibility for emerging advanced air mobility providers and reduce traffic controller workload while maintaining current safety standards. To demonstrate this process, 1,972 Letters of Agreement (LOAs) have been selected for processing, named entity extraction, constraint identification and extraction. This dataset is derived from a subset of documents related to Air Route Traffic Control Centers (ARTCC) operations. We experimented with various traditional information extraction techniques, state-of-the-art machine learning and deep learning models to perform named entity recognition and pattern recognition on our dataset. We present the results from our experiments and demonstrate 99.0% F-1 score for named entity recognition, and a 96.6% accuracy for our entire workflow up to named entity recognition. We also discuss constraint definitions using generic patterned templates and extensions to this work in applying entity linking to digitally extracting relevant constraints.

Natural Language Processing↗

Hierarchical Mixture of Experts for Advanced Air Mobility Flight Phase Classification

Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) operations will have numerous vehicles and aircraft flying in the airspace, which poses safety and security concerns. Commercial airlines utilize Air Traffic Management (ATM) and Air Traffic Control (ATC) for real-time monitoring, surveillance, traffic coordination, and rerouting to maintain safe and efficient flight patterns. Transferring ATM and ATC architectures to AAM/UAM will be challenging to implement since AAM/UAM aircraft fly at lower altitudes, have more static and dynamic obstacles, operate in highly dense environments, and have several more aircraft to monitor for a given volume of the national airspace (NAS). Aircraft typically have the following flight phases: takeoff, climb, cruise, descent, and landing. Classifying these flight phases provides insight into ensuring safe operations, providing situational awareness of the NAS, and monitoring flights in emergencies. Automatic flight phase classification will enhance the efficiencies of ATM/ATC-like architectures for AAM/UAM, especially since numerous aircraft will be flying in highly dense urban environments. Typical flight phase classification methods are all-or-nothing, which will not capture or accurately classify the transitions between flight phases. Utilizing hierarchical mixture of experts (HME) provides a flight phase classification solution that includes transitions between the flight phases by assigning weights based on ground-based distributed sensor readings from cameras and radar. Adding the transitions between flight phases increases the fidelity of flight phase classification and provides deeper insight into flight phase classification by leveraging distributed sensing concepts. Simulation results and post-processed flight test results demonstrate the utility of HME for automatic and robust flight phase classification for real-time AAM operations.

distributed sensing↗

Evolution in vitro: analysis of a lineage of ribozymes

Background: Catalytic RNAs, or ribozymes, possessing both a genotype and a phenotype, are ideal molecules for evolution experiments in vitro. A large, heterogeneous pool of RNAs can be subjected to multiple rounds of selection, amplification and mutation, leading to the development of variants that have some desired phenotype. Such experiments allow the investigator to correlate specific genetic changes with quantifiable alterations of the catalytic properties of the RNA. In addition, patterns of evolutionary change can be discerned through a detailed examination of the genotypic composition of the evolving RNA population. Results: Beginning with a pool of 10(13) variants of the Tetrahymena ribozyme, we carried out in vitro evolution experiments that led to the generation of ribozymes with the ability to cleave an RNA substrate in the presence of Ca2+ ions, an activity that does not exist for the wild-type molecule. Over the course of 12 generations, a seven-error variant emerged that has substantial Ca(2+)-dependent RNA-cleavage activity. Advantageous mutations increased in frequency in the population according to three distinct dynamics--logarithmic, linear and transient. Through a comparative analysis of 31 individual variants, we infer how certain mutations influence the catalytic properties of the ribozyme. Conclusions: In vitro evolution experiments make it possible to elucidate important aspects of both evolutionary biology and structural biochemistry on a reasonable short time scale.

Non-NASA Center↗

An Approach for Defining IASMS Services, Functions, and Capabilities

Assuring safety in the NAS with the inclusion of new entrants, such as Advanced Air Mobility (AAM), will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using autonomous vehicles. The focus of the In-time Aviation Safety Management System (IASMS) is to overcome AAM’s safety assurance challenges. The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs) designed to manage operational risks, identify unknown risks, and inform system designs. This paper describes an approach for defining SFCs based on technology trends in research, assessment of known and unknown risks in voluntary safety reports, and causal and contributing factors in aviation accidents and incidents. This approach would identify potential SFCs that further expand the Monitor, Assess, and Mitigate (M-A-M) functionality that represents the enabling framework of the IASMS. Safety implications that will result from integration of AAM in the transformation of the National Airspace System (NAS) were addressed in National Academies committees reports on AAM and IASMS. Development of a ConOps for IASMS was a top recommendation and can be represented as a reframing of safety assurance that builds on real-time alerting such as the Traffic Alert and Collision Avoidance System, and adds the more encompassing in-time temporal parameter in recognition of the different timelines for collecting and assessing safety data for risk mitigations. For example, mining for safety trends from data sources such as the Aviation Safety Information Analysis and Sharing system occurs over a longer time period. Research on AAM operations poses that SFCs can be designed to monitor the safety margin appropriate for AAM including with regards to the distance between current flight parameters and nominal ideal conditions. These in-time comparisons will become more complex as the density of operations increases at least in certain areas and can include planned and actual 4D trajectory, and in-time comparisons having implications on conflict modeling and prediction including expected and actual departure time, fix/waypoint crossing times, and arrival time. These comparisons would be integrated as part of SFCs that redefine and inform new safety margin. An increased safety margin improves management of operational risks while reducing the potential for anomalies. An increased safety margin also has implications for operator confidence in the certainty of its operations and trust in automation. Technology trends in research could be used to refine existing SFCs and define needs for additional SFCs that provide safety improvements to the design and operation of vehicles, airspace design, and operator performance requirements. NASA is developing innovative approaches to safeguard against major accidents and incidents that have occurred in the NAS and those anticipated with the inclusion of envisioned AAM operations. The innovations use operational performance data to monitor, detect, and predict flight variations exceeding safe nominal patterns, such as would be caused by navigational error, severe weather complications, or hijacking of UAS controls. These innovative approaches have high potential to prevent accidents and incidents in the new AAM era. It is anticipated that elements of the innovations will evolve into SFCs for the IASMS. Voluntary safety reports can be monitored to identify anomalies related to design or operational performance risks. Reports could be periodically monitored and assessed for specific topics. Reports might serve as weak signals or precursors indicative of emergent risk such as when combined with other safety information. The architecture could include SFCs that are based on voluntary safety reports recognizing the periodic temporal nature of data analysis. As previously mentioned, aviation accidents with their causal and contributing precursors can inform the need for SFCs in the IASMS. Accidents and incidents at San Francisco International Airport such as Asiana 214 and Air Canada 759 illustrate how combinations of different factors lead to increased risk. These types of precursors and different factors have implications on the types of SFCs that could be needed to monitor and manage different sources and types of design and operational risk. Continuing to assure the safety of AAM as designs and operations gain in complexity can be accompanied by defining SFCs that also increase in complexity. These SFCs can leverage information from findings and recommendations synthesized across on-going research, voluntary safety reports, and accident and incident reports. These SFCs can serve to refine accuracy of algorithms and resolve limitations with current practices. The IASMS architecture represents the framework for the SFCs and their critical role in safety assurance.

In-Time Aviation Safety Management System↗

Flows around sunspots and pores

Observations are reported yielding high-resolution white-light data regarding the flow pattern of penumbral material and granules around sunspots and pores. The data are culled from optical observations near the limit of the telescope modulation transfer function, and correlation tracking is employed to track the motions of penumbral features and granules. Dark fibrils and bright grains in the sunspots' inner penumbra regions move toward the umbra, and the opposite occurs in the outer penumbra. Before pore formation and during the pores existence granular flows are found to converge on the features. The paper also details the evolution of an emerging flux region, and two types of photospheric dark alignments are described in the region of new flux emergence.

Wang, Haimin↗

The Effect of Regional Climate Variability on Outbreak of Bartonellosis Epidemics in Peru

Bartonellosis is a vector-borne, highly fatal, emerging infectious disease, which has been known in the Peruvian Andes since the early 1600s and has continued to be a problem in many mountain valleys in Peru and other Andean South American countries. The causative bacterium, Bartonella bacilliformis (Bb), is believed to be transmitted to humans by bites of the sand fly Lutzomyia verrucarum. According to available medical records, the transmission of infection often occurs in river valleys of the Andes Mountains at an altitude between 800 and 3500 meters above sea level. It shows a seasonal pattern, which usually begins to rise in December, peaks in February and March, and is at its lowest from July until November. The epidemics of bartonellosis also vary interannually, occurring every four to eight years, and appear to be associated with the El Nino cycle. In response to the National Oceanic and Atmospheric Administration (NOAA) announcement on climate variability and human health, which was constructed to stimulate integrated multidisciplinary research in the area of climate variability and health interactions, we have conducted a study to investigate the relationship between the El Nino induced regional climate variation and the outbreak of bartonellosis epidemics in Peru. Two test sites, Caraz and Cusco, were selected for this study. According to reports, Caraz has a long-standing history of endemic transmission and Cusco, which is located about five degrees poleward of Caraz, had no recorded epidemics until the most recent 1997/1998 El Nino event. The goal of this study is to clarify the relative importance of climatic risk factors for each area that could be predicted in advance, thus allowing implementation of cost-effective control measures, which would reduce disease morbidity and mortality.

Zhou, Jia-Yu↗

Spiral waves are stable in discrete element models of two-dimensional homogeneous excitable media

The spontaneous breakup of a single spiral wave of excitation into a turbulent wave pattern has been observed in both discrete element models and continuous reaction-diffusion models of spatially homogeneous 2D excitable media. These results have attracted considerable interest, since spiral breakup is thought to be an important mechanism of transition from the heart rhythm disturbance ventricular tachycardia to the fatal arrhythmia ventricular fibrillation. It is not known whether this process can occur in the absence of disease-induced spatial heterogeneity of the electrical properties of the ventricular tissue. Candidate mechanisms for spiral breakup in uniform 2D media have emerged, but the physical validity of the mechanisms and their applicability to myocardium require further scrutiny. In this letter, we examine the computer simulation results obtained in two discrete element models and show that the instability of each spiral is an artifact resulting from an unphysical dependence of wave speed on wave front curvature in the medium. We conclude that spiral breakup does not occur in these two models at the specified parameter values and that great care must be exercised in the representation of a continuous excitable medium via discrete elements.

NASA Discipline Cardiopulmonary↗

Ten Years of Land Cover Change on the California Coast Detected using Landsat Satellite Image Analysis

Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.

Land Cover Change↗

Comparative assessment of the polypeptide profiles from lateral and primary roots of Phaseolus vulgaris L

In Phaseolus vulgaris, primary roots show gravitational sensitivity soon after emerging from the seed. In contrast, lateral roots are agravitropic during early development, and become gravitropic after several cm growth. Primary and lateral root tissues were examined by polyacrylamide gel electrophoresis, coupled with western blotting techniques, to compare proteins which may contribute to the acquisition of gravitational sensitivity. Root tips and zones of cell elongation were compared for each root type, using immunological probes for calmodulin, alpha-actin, alpha-tubulin, and proteins of the plastid envelope. Lateral roots contained qualitatively less calmodulin, and showed a slightly different pattern of actin-related epitope proteins, than did primary root tissues, suggesting that polypeptide differences may contribute to the gravitational sensitivity which these root types express.

Non-NASA Center↗

Hierarchical Mixture of Experts for Advanced Air Mobility Flight Phase Classification

Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) operations will have numerous vehicles and aircraft flying in the airspace, which poses safety and security concerns. Commercial airlines utilize Air Traffic Management (ATM) and Air Traffic Control (ATC) for real-time monitoring, surveillance, traffic coordination, and rerouting to maintain safe and efficient flight patterns. Transferring ATM and ATC architectures to AAM/UAM will be difficult to implement since AAM/UAM aircraft fly at lower altitudes, have more static and dynamic obstacles, operate in highly dense environments, and have several more aircraft to monitor for a given volume of the national airspace (NAS). Automatic flight phase classification will enhance efficiencies of ATM/ATC-like architectures for AAM/UAM. Classifying the main flight phases (takeoff, climb, cruise, descent, and landing) provides insight to ensure safe operations, provide situational awareness of the NAS, and monitor flights in case there are any emergencies. Typical flight phase classification methods are all-or-nothing, which will not capture or accurately classify the transitions between flight phases. Utilizing hierarchical mixture of experts (HME) provides a flight phase classification solution that includes transitions between the flight phases by assigning weights based on ground-based distributed sensor readings from cameras and radar. Adding the transitions between flight phases increases the fidelity of flight phase classification and provides deeper insight for flight phase classification by leveraging distributed sensing concepts.

distributed sensing↗

System Concepts for the Advanced Post-TRMM Rainfall Profiling Radars

Global rainfall is the primary distributor of latent heat through atmospheric circulation. The recently launched Tropical Rainfall Measuring Mission satellite is dedicated to advance our understanding of tropical precipitation patterns and their implications on global climate and its change. The Precipitation Radar (PR) aboard the satellite is the first radar ever flown in space and has provided. exciting, new data on the 3-D rain structures for a variety of scientific uses. However, due to the limited mission lifetime and the dynamical nature of precipitation, the TRMM PR data acquired cannot address all the issues associated with precipitation, its related processes, and the long-term climate variability. In fact, a number of new post-TRMM mission concepts have emerged in response to the recent NASA's request for new ideas on Earth science missions at the post 2002 era. This paper will discuss the system concepts for two advanced, spaceborne rainfall profiling radars. In the first portion of this paper, we will present a system concept for a second-generation spaceborne precipitation radar for operations at the Low Earth Orbit (LEO). The key PR-2 electronics system will possess the following capabilities: (1) A 13.6/35 GHz dual frequency radar electronics that has Doppler and dual-polarization capabilities. (2) A large but light weight, dual-frequency, wide-swath scanning, deployable antenna. (3) Digital chirp generation and the corresponding on-board pulse compression scheme. This will allow a significant improvement on rain signal detection without using the traditional, high-peak-power transmitters and without sacrificing the range resolution. (4) Radar electronics and algorithm to adaptively scan the antenna so that more time can be spent to observe rain rather than clear air. and (5) Built-in flexibility on the radar parameters and timing control such that the same radar can be used by different future rain missions. This will help to reduce the overall instrument development costs. In the second portion of this paper, we will present a system concept for a geostationary rainfall monitoring radar for operations at the geosynchronous Earth Orbit (GEO). In particular, the science requirements, the observational strategy, the instrument design, and the required technologies will be discussed.

Im, Eastwood↗

Observations of hysteresis in solar cycle variations among seven solar activity indicators

We show that smoothed time series of 7 indices of solar activity exhibit significant solar cycle dependent differences in their relative variations during the past 20 years. In some cases these observed hysteresis patterns start to repeat over more than one solar cycle, giving evidence that this is a normal feature of solar variability. Among the indices we study, we find that the hysteresis effects are approximately simple phase shifts, and we quantify these phase shifts in terms of lag times behind the leading index, the International Sunspot Number. Our measured lag times range from less than one month to greater than four months and can be much larger than lag times estimated from short-term variations of these same activity indices during the emergence and decay of major active regions. We argue that hysteresis represents a real delay in the onset and decline of solar activity and is an important clue in the search for physical processes responsible for changing solar emission at various wavelengths.

Bachmann, Kurt T.↗

The Mars Atmosphere Water Ice Aerosol Climatology by MRO/CRISM: 5 Mars Years of Observations

We use near-infrared spectra returned from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) aboard the Mars Reconnaissance Orbiter (MRO) to provide retrievals of the column-integrated optical depth of water ice aerosols for more than 5 Martian years between Mars Year (MY) 28 at Ls = 112° (27 September 2006) and MY 33 at Ls = 213° (30 August 2016). We have developed a radiative transfer model for this purpose that retrieves aerosol opacity from the water ice aerosol feature near 3.3 μm using CRISM hyperspectral observations for the first time. The resulting retrievals well depict the main features in the water ice aerosol climatology with repeatable patterns every Martian year. The aphelion cloud belt (ACB) is observed between 10°S and 30°N, with peak optical depth around Ls = 90°. Apart from the global dust storm during MY 28, modest interannual variability in the water ice aerosol optical depth is observed in the ACB. The north polar hood is observed at latitudes poleward of 45°N throughout northern spring and summer seasons and reappears in northern winter. The south polar hood is observed in early to mid-southern autumn, reaching latitudes around 60°S, and re-emerging during southern winter between 45°S and 60°S. A lack of water ice aerosols is repeatedly seen in the southern hemisphere throughout southern spring and summer. High optical depth in the ACB is observed over the volcanoes of Olympus Mons, Elysium, and the Tharsis bulge, as well as over Hellas Basin.

Mars↗

QuakeSim 2.0

QuakeSim 2.0 improves understanding of earthquake processes by providing modeling tools and integrating model applications and various heterogeneous data sources within a Web services environment. QuakeSim is a multisource, synergistic, data-intensive environment for modeling the behavior of earthquake faults individually, and as part of complex interacting systems. Remotely sensed geodetic data products may be explored, compared with faults and landscape features, mined by pattern analysis applications, and integrated with models and pattern analysis applications in a rich Web-based and visualization environment. Integration of heterogeneous data products with pattern informatics tools enables efficient development of models. Federated database components and visualization tools allow rapid exploration of large datasets, while pattern informatics enables identification of subtle, but important, features in large data sets. QuakeSim is valuable for earthquake investigations and modeling in its current state, and also serves as a prototype and nucleus for broader systems under development. The framework provides access to physics-based simulation tools that model the earthquake cycle and related crustal deformation. Spaceborne GPS and Inter ferometric Synthetic Aperture (InSAR) data provide information on near-term crustal deformation, while paleoseismic geologic data provide longerterm information on earthquake fault processes. These data sources are integrated into QuakeSim's QuakeTables database system, and are accessible by users or various model applications. UAVSAR repeat pass interferometry data products are added to the QuakeTables database, and are available through a browseable map interface or Representational State Transfer (REST) interfaces. Model applications can retrieve data from Quake Tables, or from third-party GPS velocity data services; alternatively, users can manually input parameters into the models. Pattern analysis of GPS and seismicity data has proved useful for mid-term forecasting of earthquakes, and for detecting subtle changes in crustal deformation. The GPS time series analysis has also proved useful as a data-quality tool, enabling the discovery of station anomalies and data processing and distribution errors. Improved visualization tools enable more efficient data exploration and understanding. Tools provide flexibility to science users for exploring data in new ways through download links, but also facilitate standard, intuitive, and routine uses for science users and end users such as emergency responders.

Donnellan, Andrea↗

Conditions of the Toll-Like Receptors System of the Human Innate Immunity Cells During the Long-Term Isolation

During long duration missions onboard the International Space Station (ISS), alterations in T cell function and plasma cytokine profiles have been observed. Recent studies involving pattern recognition receptors (PRRs) have established that adaptation of innate immunity to long duration space flight occurs through changes in signal PRRs, Toll-like receptors (TLRs). Despite the fact that fundamental research of PRR molecular biology is far from complete, there are an increasing number of arguments confirming the important role of this system in regulating the initial stages of the adaptive immune response, as well as in the formation of autoimmune and allergic diseases. Long duration isolation is widely used by NASA as an analog for space flight with previous missions including several Antarctic bases, an undersea research station (NEEMO), and other isolation chambers. ‘SIRIUS’ is a multi-compartment pressurized facility at the IMBP in Moscow, Russia, in which subjects will spend 8 months executing tasks similar to those performed by astronauts in space. Prolonged isolation studies like SIRIUS replicate many of the influences expected to occur during long duration spaceflight missions including isolation, stress, confinement, and living in remote conditions. The immune study to be performed on the upcoming SIRIUS mission is being led by Dr. Sergey Ponomarev at the Institute of Biomedical Problems in Moscow, Russia. The NASA JSC Immunology lab will provide analysis of immune cell function, serum cytokines and stress hormones, and salivary cortisol, cytokines, and viruses. This study will be conducted with SIRIUS subjects under the auspices of the parent program. The goal of the study is to evaluate the effect of the 8-month isolation mission on components of human innate immunity at the molecular and cellular level. Successful implementation and completion of this project will provide a unique assortment of new data, significantly expanding the current understanding of the molecular and cellular changes in TLRs during long-term isolation. We hypothesize that mission-like isolation in the Russian NEK facility, consisting of circadian misalignment, isolation, stress, and ‘station lifestyle’, will result in a pattern of immune dysregulation similar to that observed in astronauts onboard ISS. This pattern of alterations can be summarized as phenotypic changes (altered distribution of peripheral cytotoxic, central memory, CD8+ T cell subsets), reductions in T cell function, alterations in plasma cytokine profiles (increased inflammatory and certain chemokines), and reductions in mitogen stimulated cytokine profiles (spans Th1, Th2, Th17). We further hypothesize that these immune changes will correlate with the reactivation of latent herpesviruses (which persists during orbital flight), to be used as measurable adverse clinical manifestation or with other observed symptomology. The SIRIUS-21 mission began in November of 2021 and successfully concluded with the crew emerging in July of 2022. Currently, the logistics of shipping the samples from Russia to the United States is being organized.

Cody L Gutierrez↗