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At least 217 records · Page 12

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗

Quantifying the Correlation Between Eye-Movement and Perceptual Responses to Moving Plaids

To determine the extent to which the pursuit eye-movement and perceptual systems share a common neural motion-processing pathway, we simultaneously measure the psychophysical and eye-movement responses to drifting plaids in a direction-discrimination task. Correlation between the noise in the eye movements and percepts would suggest a shared neural substrate. Three observers were asked to track a plaid (Type I 90 deg; TF = 4 Hz, SF = 0.6 c/d; direction = -2, 0, or 2 deg), and to respond whether the motion was to the right or left of vertical. The eye-movement direction is computed from the initial 300 ms of saccade-free tracking (near open-loop). On each trial, we use the eye-movement direction to predict the perceptual response. We then compute the probability of successfully predicting the observer's response. We also use SOC analysis as an alternate measure of the correlation. We compare the data from both these analyses to the predictions of two models in which the eye movements and the percept are driven by either a common noisy signal (correlated model) or by two separate noisy signals (uncorrelated model). We also allow for the fact that our measured eye movements are degraded by eye-tracker noise. This noise causes our measured correlation to be lower than the actual biological correlation. The correlations in our data are higher than those predicted by the uncorrelated model, and are similar to the predictions of the correlated model. The proportion of perceptual responses correctly predicted by the eye movements were 0.66, 0.60, 0.73 for the -2, 0, 2 deg stimuli respectively (correlated model 0.65, 0.60, 0.70; uncorrelated model 0.58, 0.51, 0.60).The SOC proportions were 0.71, 0.64, 0.72 (correlated model 0.66, 0.64, 0.69; uncorrelated model 0.5, 0.5, 0.5). These results show that the oculomotor and perceptual system share a performance-limiting noise source and provide strong evidence that a common neural mechanism (perhaps MT or MST) drives both perception and smooth eye movements.

Beutter, Brent R.↗

Physical and biological studies with protons and HZE particles in a NASA supported research center in radiation health

NASA has established and supports a specialized center for research and training (NSCORT) to specifically address the potential deleterious effects of HZE particles on human health. The NSCORT in radiation health is a joint effort between Lawrence Berkeley National Laboratory (LBNL) and Colorado State University (CSU). The overall scope of research encompasses a broad range of subjects from microdosimetric studies to cellular and tissue responses to initial damage produced by highly energetic protons and heavy charged particles of the type found in galactic cosmic rays (GCR) spectrum. The objectives of the microdosimetry studies are to determine the response of Tissue Equivalent Proportional Counter (TEPC) to cosmic rays using ground based accelerators. This includes evaluation of energy loss due to the escape of high-energy delta rays and increased energy deposition due to the enhanced delta ray production in the wall of the detector. In this report major results are presented for 56Fe at 1000, 740, 600 and 400 MeV/nucleon. An assessment of DNA repair and early development of related chromosomal changes is extremely important to our overall understanding of enhanced biological effectiveness of high LET particle radiation. Results are presented with respect to the fidelity of the rejoining of double strand breaks and the implications of misrejoining. The relationship between molecular and cytogenetic measurements is presented by studying damage processing in highly heterochromatic supernumerary (correction of sypernumerary) X chromosomes and the active X-chromosome. One of the important consequences of cell's inability to handle DNA damage can be evaluated through mutation studies. Part of our goal is the assessment of potential radioprotectors to reduce the mutation yield following HZE exposures, and some promising results are presented on one compound. A second goal is the integration of DNA repair and mutation studies. Results are presented on a direct comparison of initial double strand breaks induction, the time course and fidelity of double strand break rejoining, cell killing and mutation induction in the same human model system. In order to understand the carcinogenic potential of protons and HZE particles, the role of damaged microenvironment in this process must be understood. In this project it has been postulated that radiation affects the microenvironment, which then modifies cell interactions in a manner conducive to neoplastic progression. Both TGF-beta and FGF-2 are important components of microenvironment. A recent result on the assessment of the role of FGF-2 and its cross-talk with TGF-beta as a function of radiation quality is presented. Theoretical modeling has so far played a central role in analyzing and integrating experimental data on repair and mutation studies and predicting new phenomena. The integrated NSCORT program also provides a broad training experience for students and postdoctoral fellows in space radiation health.

NASA Discipline Radiation Health↗

Auxins and tropisms

Differential growth of plants in response to the changes in the light and gravity vectors requires a complex signal transduction cascade. Although many of the details of the mechanisms by which these differential growth responses are induced are as yet unknown, auxin has been implicated in both gravitropism and phototropism. Specifically, the redistribution of auxin across gravity or light-stimulated tissues has been detected and shown to be required for this process. The approaches by which auxin has been implicated in tropisms include isolation of mutants altered in auxin transport or response with altered gravitropic or phototropic response, identification of auxin gradients with radiolabeled auxin and auxin-inducible gene reporter systems, and by use of inhibitors of auxin transport that block gravitropism and phototropism. Proteins that transport auxin have been identified and the mechanisms which determine auxin transport polarity have been explored. In addition, recent evidence that reversible protein phosphorylation controls this process is summarized. Finally, the data in support of several hypotheses for mechanisms by which auxin transport could be differentially regulated during gravitropism are examined. Although many details of the mechanisms by which plants respond to gravity and light are not yet clear, numerous recent studies demonstrate the role of auxin in these processes.

NASA Discipline Plant Biology↗

Modeled Microgravity Inhibits Apoptosis in Peripheral Blood Lymphocytes

Impairment of the immunity in astronauts and cosmonauts even in short term flights is a recognized risk. Long term orbital space missions and anticipated interplanetary flights increase the concern for more pronounced effects on the immune system with potential clinical consequences. Impairment of the immunity in space may be due tonumerous physiological changes caused by space-related factors, which in turn affect the immune system, or alternatively, it may be due to direct effects of different factors encountered in space on lymphoid cells and their interactions. Indeed, in modeled microgravity (MMG) experiments on Earth we and others showed that microgravity directly affects multiple lymphocyte functions. It interferes with expression of cell surface molecules, causes inhibition of lymphocyte locomotion, suppresses polyclopal and antigen-specific lymphocyte activation, selectively inhibits protein kinase C (PKC) isoforms. Some of these effects were also confirmed in cell culture experiments in real space conditions during Spacelab, Biokosmos and Shuttle Missions. The results of these studies, taken together, strongly indicated that microgravity interferes with fundamental biological processes associated with functional and structural changes in cell surface membranes, cell surface molecules and in their interaction. Based on the data and on their interpretation, we hypothesized that microgravity in addition to observed functional changes affects programmed cell death (PCD) in lymphocyte populations and that this mechanism could contribute to the impairment of the immunity.

Risin, Diana↗

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, the re-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA’s Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related ‘omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata ‘omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data re-use, resulting in 38 additional publications derived from the original 67 publication over the past four years. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA “Open Science Data Repositories (OSDR)” and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Fluorescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to “big data” from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology. Several other talks will cover these topics in this conference.

life sciences↗

Thiols in Hydrothermal Solution: Standard Partial Molal Properties and Their Role in the Organic Geochemistry of Hydrothermal Environments

Modern seafloor hydrothermal systems are locations where great varieties of geochemistry occur due to the enormous disequilibrium between vent fluids and seawater. The disequilibrium geochemistry has been hypothesized to include reactions to synthesize organic compounds. Despite the incomplete understanding of the carbon budget in hydrothermal systems, the organic geochemistry of these sites has received little attention. Experimental simulations of these environments, however, indicate that organic compounds may have difficulty forming in a purely aqueous environment. On the other hand, thiols, thioesters and disulfides have been implicated as reaction intermediates between CO or CO2 in experiments of carbon reduction in hydrothermal environments, as well as in a variety of biological processes and other abiotic reactions. The reduction of CO2 to thesis, for example, is observed using the FeS-H2S/FeS2 couple to provide the reducing power. We have used recent advances in theoretical geochemistry to estimate the standard partial moral thermodynamic properties and parameters for the revised Helgeson-Kirkham-Flowers equation of state for aqueous straight-chain alkyl thesis. With these data and parameters we have evaluated the role that organic sulfur compounds may play as reaction intermediates during organic compound synthesis. We conclude that organic sulfur compounds may hold the key to the organic chemistry leading to the origin of life in hydrothermal settings. These results may also explain the presence of sulfur in a number of biomolecules present in ancient thermophilic microorganisms.

Schulte, Mitchell D.↗

NASA GeneLab Concept of Operations

NASA's GeneLab aims to greatly increase the number of scientists that are using data from space biology investigations on board ISS, emphasizing a systems biology approach to the science. When completed, GeneLab will provide the integrated software and hardware infrastructure, analytical tools and reference datasets for an assortment of model organisms. GeneLab will also provide an environment for scientists to collaborate thereby increasing the possibility for data to be reused for future experimentation. To maximize the value of data from life science experiments performed in space and to make the most advantageous use of the remaining ISS research window, GeneLab will apply an open access approach to conducting spaceflight experiments by generating, and sharing the datasets derived from these biological studies in space.Onboard the ISS, a wide variety of model organisms will be studied and returned to Earth for analysis. Laboratories on the ground will analyze these samples and provide genomic, transcriptomic, metabolomic and proteomic data. Upon receipt, NASA will conduct data quality control tasks and format raw data returned from the omics centers into standardized, annotated information sets that can be readily searched and linked to spaceflight metadata. Once prepared, the biological datasets, as well as any analysis completed, will be made public through the GeneLab Space Bioinformatics System webb as edportal. These efforts will support a collaborative research environment for spaceflight studies that will closely resemble environments created by the Department of Energy (DOE), National Center for Biotechnology Information (NCBI), and other institutions in additional areas of study, such as cancer and environmental biology. The results will allow for comparative analyses that will help scientists around the world take a major leap forward in understanding the effect of microgravity, radiation, and other aspects of the space environment on model organisms. These efforts will speed the process of scientific sharing, iteration, and discovery.

Space Life Science↗

Artificial Intelligence Based Control Power Optimization on Tailless Aircraft

Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling large arrays of control devices on innovative air vehicles. Artificial neutral networks are inspired by biological nervous systems and neurocomputing has successfully been applied to a variety of complex optimization problems. This project investigates the potential of applying neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts to minimize control power, hinge moments, and actuator forces, while keeping system weights within acceptable limits. The main objective of this project is to develop a proof-of-concept process suitable to demonstrate the potential of using neurocomputing for optimizing actuation power for aircraft featuring multiple independently actuated control surfaces. A Nastran aeroservoelastic finite element model is used to generate a learning database of hinge moment and actuation power characteristics for an array of flight conditions and control surface deflections. An artificial neural network incorporating a genetic algorithm then uses this training data to perform control allocation optimization for the investigated aircraft configuration. The phase I project showed that optimization results for the sum of required hinge moments are improved by more than 12% over the best Nastran solution by using the neural network optimization process.

Gern, Frank↗

Focused Metabolite Profiling for Dissecting Cellular and Molecular Processes of Living Organisms in Space Environments

Regulatory control in biological systems is exerted at all levels within the central dogma of biology. Metabolites are the end products of all cellular regulatory processes and reflect the ultimate outcome of potential changes suggested by genomics and proteomics caused by an environmental stimulus or genetic modification. Following on the heels of genomics, transcriptomics, and proteomics, metabolomics has become an inevitable part of complete-system biology because none of the lower "-omics" alone provide direct information about how changes in mRNA or protein are coupled to changes in biological function. The challenges are much greater than those encountered in genomics because of the greater number of metabolites and the greater diversity of their chemical structures and properties. To meet these challenges, much developmental work is needed, including (1) methodologies for unbiased extraction of metabolites and subsequent quantification, (2) algorithms for systematic identification of metabolites, (3) expertise and competency in handling a large amount of information (data set), and (4) integration of metabolomics with other "omics" and data mining (implication of the information). This article reviews the project accomplishments.

Source record↗

Artificial Immune System for Recognizing Patterns

A method of recognizing or classifying patterns is based on an artificial immune system (AIS), which includes an algorithm and a computational model of nonlinear dynamics inspired by the behavior of a biological immune system. The method has been proposed as the theoretical basis of the computational portion of a star-tracking system aboard a spacecraft. In that system, a newly acquired star image would be treated as an antigen that would be matched by an appropriate antibody (an entry in a star catalog). The method would enable rapid convergence, would afford robustness in the face of noise in the star sensors, would enable recognition of star images acquired in any sensor or spacecraft orientation, and would not make an excessive demand on the computational resources of a typical spacecraft. Going beyond the star-tracking application, the AIS-based pattern-recognition method is potentially applicable to pattern- recognition and -classification processes for diverse purposes -- for example, reconnaissance, detecting intruders, and mining data.

Huntsberger, Terrance↗

Hyperspectral Imaging and Related Field Methods: Building the Science

The proposal requested funds for the computing power to bring hyperspectral image processing into undergraduate and graduate remote sensing courses. This upgrade made it possible to handle more students in these oversubscribed courses and to enhance CSES' summer short course entitled "Hyperspectral Imaging and Data Analysis" provided for government, industry, university and military. Funds were also requested to build field measurement capabilities through the purchase of spectroradiometers, canopy radiation sensors and a differential GPS system. These instruments provided systematic and complete sets of field data for the analysis of hyperspectral data with the appropriate radiometric and wavelength calibration as well as atmospheric data needed for application of radiative transfer models. The proposed field equipment made it possible to team-teach a new field methods course, unique in the country, that took advantage of the expertise of the investigators rostered in three different departments, Geology, Geography and Biology.

Goetz, Alexander F. H.↗

The Breadboard Project - A functioning CELSS plant growth system

The primary objective of the Breadboard Project for the next 3-4 years is to develop, integrate and operate a Controlled Ecological Life Support System (CELSS) at a one-person scale. The focus of this project over the past two years has been the development of the plant growth facility, the first module of the CELSS. The other major modules, food preparation, biomass processing, and resource recovery, have been researched at the laboratory scale during the past two years and facilities are currently under construction to scale-up these modules to an operational state. This paper will outline the design requirements for the Biomass Production Chamber (BPC), the plant growth facility for the project, and the control and monitoring subsystems which operate the chamber and will present results from both engineering and biological tests of the facility. Three production evaluations of wheat, conducted in the BPC during the past year, will be described and the data generated from these tests discussed.

Knott, W. M.↗

The impact crater as a habitat: effects of impact processing of target materials

Impact structures are a rare habitat on Earth. However, where they do occur they can potentially have an important influence on the local ecology. Some of the types of habitat created in the immediate post-impact environment are not specific to the impact phenomenon, such as hydrothermal systems and crater lakes that can be found, for instance, in post-volcanic environments, albeit with different thermal characteristics than those associated with impact. However, some of the habitats created are specifically linked to processes of impact processing. Two examples of how impact processing of target materials has created novel habitats that improve the opportunities for colonization are found in the Haughton impact structure in the Canadian High Arctic. Impact-shocked rocks have become a habitat for endolithic microorganisms, and large, impact-shattered blocks of rock are used as resting sites by avifauna. However, some materials produced by an impact, such as melt sheet rocks, can make craters more biologically depauperate than the area surrounding them. Although there are no recent craters with which to study immediate post-impact colonization, these data yield insights into generalized mechanisms of how impact processing can influence post-impact succession. Because impact events are one of a number of processes that can bring localized destruction to ecosystems, understanding the manner in which impact structures are recolonized is of ecological interest. Impact craters are a universal phenomenon on solid planetary surfaces, and so they are of potential biological relevance on other planetary surfaces, particularly Mars.

Environment↗

Shape-dependent control of cell growth, differentiation, and apoptosis: switching between attractors in cell regulatory networks

Development of characteristic tissue patterns requires that individual cells be switched locally between different phenotypes or "fates;" while one cell may proliferate, its neighbors may differentiate or die. Recent studies have revealed that local switching between these different gene programs is controlled through interplay between soluble growth factors, insoluble extracellular matrix molecules, and mechanical forces which produce cell shape distortion. Although the precise molecular basis remains unknown, shape-dependent control of cell growth and function appears to be mediated by tension-dependent changes in the actin cytoskeleton. However, the question remains: how can a generalized physical stimulus, such as cell distortion, activate the same set of genes and signaling proteins that are triggered by molecules which bind to specific cell surface receptors. In this article, we use computer simulations based on dynamic Boolean networks to show that the different cell fates that a particular cell can exhibit may represent a preprogrammed set of common end programs or "attractors" which self-organize within the cell's regulatory networks. In this type of dynamic network model of information processing, generalized stimuli (e.g., mechanical forces) and specific molecular cues elicit signals which follow different trajectories, but eventually converge onto one of a small set of common end programs (growth, quiescence, differentiation, apoptosis, etc.). In other words, if cells use this type of information processing system, then control of cell function would involve selection of preexisting (latent) behavioral modes of the cell, rather than instruction by specific binding molecules. Importantly, the results of the computer simulation closely mimic experimental data obtained with living endothelial cells. The major implication of this finding is that current methods used for analysis of cell function that rely on characterization of linear signaling pathways or clusters of genes with common activity profiles may overlook the most critical features of cellular information processing which normally determine how signal specificity is established and maintained in living cells. Copyright 2000 Academic Press.

Review↗

Validation of Multisystem Countermeasures Protocol for Spaceflight during Antarctica Winter-over at Palmer Station (Palmer Countermeasures)

Exploration-class missions beyond the Van Allen belt to the Moon and then Mars will begin soon. Low-Earth orbital spaceflight results in the persistent perturbation of the human immune system, characterized by reductions in T and NK cell function, altered cytokine profiles, and the reactivation of latent herpesviruses. While these alterations have not caused widespread clinical issues, some crewmembers experience immune-related adverse events, including manifestations of symptomatic herpes viral reactivation, allergy, and respiratory distress. Because future deep-space exploration missions will be of unprecedented duration, it is reasonable to hypothesize that the immune perturbations observed aboard International Space Station (ISS) will intensify during longer missions in deep space, thereby placing crewmembers at elevated clinical risk. Thus, it is imperative to preserve the immune vigilance of astronauts by developing a countermeasure strategy. Of all the Earth analogs studied to date, an Antarctica winter-over (AWO) mission most closely reproduces the spaceflight experience: prolonged deployment, extreme environment, circadian misalignment, isolation, station lifestyle, and personal risk. The US maintains three primary stations in Antarctica: South Pole Station, McMurdo, and Palmer. Previous studies suggest that stations located near the interior of Antarctica (South Pole, McMurdo) have confounding effects on the immune system due to persistent hypobaric hypoxia. Thus, it was hypothesized that winter-over at a coastal station (Palmer) would be more akin to spaceflight due to its normoxic but still extreme environment. Therefore, AWO at Palmer Station was chosen as the platform for testing and validating the effectiveness of a NASA multi-system countermeasures protocol designed for deep space missions. The array of countermeasure protocols and monitoring methods deployed for each AWO will consist of diet modifications, nutritional supplementation, prescribed aerobic and resistive exercise, and a protocol of stress relieving virtual reality exercises. A multitude of biological sample types, including blood, saliva, and hair will be collected in tandem with the countermeasures in order to examine the combined effectiveness of the countermeasures. Samples and logs from subjects will be transported from Palmer Station to Johnson Space Center for further processing and distribution to co-investigators at the end of each winter-over. Extracted samples will be analyzed by appropriate testing platforms (Multiplex, qPCR, ELISA, etc.) to monitor alterations in leukocyte distribution, T cell and NK function, cytokine profiles, reactivation of latent herpesviruses, and nutritional factors. The data collected will be compared to a control year in which no countermeasures were deployed to evaluate the overall effectiveness of the analog and to validate the candidate immune countermeasure strategy. With the completion of the Antarctica Winter-Over (WO) 2022 control year, samples for 13 subjects have been successfully returned from Antarctica to NASA/JSC for further processing and distribution to Co-Investigators. WO 2023, the first countermeasure year, has also commenced with 11 subject consenting and performing their base line data collections (BDC) held in Chile. Another 5 subjects, who were already stationed at Palmer Station, Antarctica, joined as participates in the investigation. These 5 subjects were consented, but no BDC was able to be collected due to their joining in-mission. Therefore, there will be a total of 16 subjects participating in Antarctica's 2023 Winter-Over.

Cody L Gutierrez↗

An efficient approach to ARMA modeling of biological systems with multiple inputs and delays

This paper presents a new approach to AutoRegressive Moving Average (ARMA or ARX) modeling which automatically seeks the best model order to represent investigated linear, time invariant systems using their input/output data. The algorithm seeks the ARMA parameterization which accounts for variability in the output of the system due to input activity and contains the fewest number of parameters required to do so. The unique characteristics of the proposed system identification algorithm are its simplicity and efficiency in handling systems with delays and multiple inputs. We present results of applying the algorithm to simulated data and experimental biological data In addition, a technique for assessing the error associated with the impulse responses calculated from estimated ARMA parameterizations is presented. The mapping from ARMA coefficients to impulse response estimates is nonlinear, which complicates any effort to construct confidence bounds for the obtained impulse responses. Here a method for obtaining a linearization of this mapping is derived, which leads to a simple procedure to approximate the confidence bounds.

Non-NASA Center↗

Characterization of microbial and chemical composition of shuttle wet waste with permanent gas and volatile organic compound analyses

Solid-waste treatment in space for Advanced Life Support, ALS, applications requires that the material can be safely processed and stored in a confined environment. Many solid-wastes are not stable because they are wet (40-90% moisture) and contain levels of soluble organic compounds that can contribute to the growth of undesirable microorganisms with concomitant production of noxious odors. In the absence of integrated Advanced Life Support systems on orbit, permanent gas, trace volatile organic and microbiological analyses were performed on crew refuse returned from the volume F "wet" trash of three consecutive Shuttle missions (STS-105, 109, and 110). These analyses were designed to characterize the short-term biological stability of the material and assess potential crew risks resulting from microbial decay processes during storage. Waste samples were collected post-orbiter landing and sorted into packaging material, food waste, toilet waste, and bulk liquid fractions deposited during flight in the volume F container. Aerobic and anaerobic microbial loads were determined in each fraction by cultivation on R2A and by acridine orange direct count (AODC). Dry and ash weights were performed to determine both water and organic content of the materials. Experiments to determine the aerobic and anaerobic biostability of refuse stored for varying periods of time were performed by on-line monitoring of CO2 and laboratory analysis for production of hydrogen sulfide and methane. Volatile organic compounds and permanent gases were analyzed using EPA Method TO15 by USEPA et al. [EPA Method TO15, The Determination of Volatile Organic Compounds (VOCs) in Ambient Air using SUMMA, Passivated Canister Sampling and Gas Chromatographic Analysis,1999] with gas chromatography/mass spectrometry and by gas chromatography with selective detectors. These baseline measures of waste stream content, labile organics, and microbial load in the volume F Shuttle trash provide data for waste subsystem analysis and atmospheric management within the ALS Project. Published by Elsevier Ltd on behalf of COSPAR.

NASA Center KSC↗