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NASA NTRS2005

Miniature Instrumentation for SIPR (Subsurface Ice PRobe)

Ice coring has proved to be a valuable scientific tool for determining climate history on Earth. The goal of the SIPR project is to develop a simple extraterrestrial ice sampling method of comparable value to coring. The SIPR probe works by melting its way through glacial ice, pumping the melt water to the surface for analysis as it descends hundreds of meters. The specific geometry of the probe, along with size and power constraints, requires creative diagnostic instrumentation. A thin, vertically strung heated filament will provide continuous-level monitoring of water in down-hole containers. The filament has an appreciable temperature coefficient to resistance (TCR), so as water cools the wire, its resistance decreases. At a constant electrical current, the voltage across the filament varies linearly with water level.

Ostmo, Karl P.↗

NASA NTRS2006

CFDP Performance over Weather-Dependent Ka-Band Channel

This study presents an analysis of the delay performance of the CCSDS File Delivery Protocol (CFDP) over weather-dependent Ka-band channel. The Ka-band channel condition is determined by the strength of the atmospheric noise temperature, which is weather dependent. Noise temperature data collected from the Deep Space Network (DSN) Madrid site is used to characterize the correlations between good and bad channel states in a two-state Markov model. Specifically, the probability distribution of file delivery latency using the CFDP deferred Negative Acknowledgement (NAK) mode is derived and quantified. Deep space communication scenarios with different file sizes and bit error rates (BERs) are studied and compared. Furthermore, we also examine the sensitivity of our analysis with respect to different data sampling methods. Our analysis shows that while the weather-dependent channel only results in fairly small increases in the average number of CFDP retransmissions required, the maximum number of transmissions required to complete 99 percentile, on the other hand, is significantly larger for the weather-dependent channel due to the significant correlation of poor weather states.

weather↗

NASA NTRS2008

Petrography and Origin of the Unique Achondrite GRA 06128 and 06129: Preliminary Results

GRA 06128 & 06129 are paired achondrites [1], with unique mineral proportions (75% oligoclase), mineral compositions, and oxygen isotope ratios. They appear to represent alkalic igneous rock from a hitherto unsampled differentiated parent body, modified significantly by thermal and shock metamorphism. Samples and Methods: Bulk samples were examined at JSC during splitting for consortium analyses. Microscope and BSE images here are on thick section GRA06128,40. Chemical analyses of minerals were acquired at Johnson Space Center with the Cameca SX100, operated at 15 kV. Feldspar was analyzed with a defocused 5 micron beam @ 5 nA; other minerals were analyzed with a focused beam @ 20 nA. Moessbauer spectra were obtained at ARES, JSC [2]. Intrinsic radioactivity was measured in the low-level counting facility at ARES JSC [3]. An estimated abundance of Al-26 of approx. 70 dpm/kg is within the range determined for eucrites.

Treiman, A. H.↗

NASA NTRS2006

Estimating Random Errors Due to Shot Noise in Backscatter Lidar Observations

In this paper, we discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson-distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root-mean-square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF uncertainties can be reliably calculated from/for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar and tested using data from the Lidar In-space Technology Experiment (LITE). OCIS Codes:

Liu, Zhaoyan↗

NASA NTRS2008

Digital X-ray camera for quality evaluation three-dimensional topographic reconstruction of single crystals of biological macromolecules

The present invention provides a digital topography imaging system for determining the crystalline structure of a biological macromolecule, wherein the system employs a charge coupled device (CCD) camera with antiblooming circuitry to directly convert x-ray signals to electrical signals without the use of phosphor and measures reflection profiles from the x-ray emitting source after x-rays are passed through a sample. Methods for using said system are also provided.

Borgstahl, Gloria↗

NASA NTRS2006

CFDP Performance over Weather-dependent Ka-band Channel

deep space communications↗

NASA NTRS2013

Transmission Electron Microscopy of Itokawa Regolith Grains

Introduction: In a remarkable engineering achievement, the JAXA space agency successfully recovered the Hayabusa space-craft in June 2010, following a non-optimal encounter and sur-face sampling mission to asteroid 25143 Itokawa. These are the first direct samples ever obtained and returned from the surface of an asteroid. The Hayabusa samples thus present a special op-portunity to directly investigate the evolution of asteroidal sur-faces, from the development of the regolith to the study of the effects of space weathering. Here we report on our preliminary TEM measurements on two Itokawa samples. Methods: We were allocated particles RA-QD02-0125 and RA-QD02-0211. Both particles were embedded in low viscosity epoxy and thin sections were prepared using ultramicrotomy. High resolution images and electron diffraction data were ob-tained using a JEOL 2500SE 200 kV field-emission scanning-transmission electron microscope. Quantitative maps and anal-yses were obtained using a Thermo thin-window energy-dispersive x-ray (EDX) spectrometer. Results: Both particles are olivine-rich (Fo70) with μm-sized inclusions of FeS and have microstructurally complex rims. Par-ticle RA-QD02-0125 is rounded and has numerous sub-μm grains attached to its surface including FeS, albite, olivine, and rare melt droplets. Solar flare tracks have not been observed, but the particle is surrounded by a continuous ~50 nm thick, stuctur-ally disordered rim that is compositionally similar to the core of the grain. One of the surface adhering grains is pyrrhotite show-ing a S-depleted rim (~8-10 nm thick) with nanophase Fe metal grains (<5 nm) decorating the outermost surface. The pyrrhotite displays a complex superstructure in its core that is absent in the S-depleted rim. Particle RA-QD02-0211 contains solar flare particle tracks (~2x109 cm-2) and shows a structurally disordered rim ~100 nm thick. The track density corresponds to a surface exposure of ~103-104 years based on the track production rate of [1]. The dis-ordered rim is nanocrystalline with minor amorphous material between crystalline domains. Quantitative element maps show the outermost ~10 nm of the disordered rim is Si-rich. Discussion and Conclusions: Both particles record the ef-fects of space weathering processes on Itokawa. Noguchi et al. [2] proposed that the disordered rims they observed on Itokawa particles largely result from solar wind radiation damage and we arrive at a similar conclusion for the two particles we analyzed. The microstructure of the S-depleted layer on the pyrrhotite grain in RA-QD02-0125 is similar to that observed in troilite irradiated with ~1018 4 kV He+ [3, 4]. Prolonged irradiation has also been shown to disorder pyrrhotite such that the superstructure reflec-tions are lost [5].

Keller, Lindsay P.↗

NASA NTRS2015

Risk of Crew Adverse Health Event Due to Altered Immune Response

Determining the effect of space travel on the human immune system has proven to be extremely challenging. Limited opportunities for in-flight studies, varying mission durations, technical and logistical obstacles, small subject numbers, and a broad range of potential assays have contributed to this problem. Additionally, the inherent complexity of the immune system, with its vast array of cell populations, sub-populations, diverse regulatory molecules, and broad interactions with other physiological systems, makes determining precise variables to measure very difficult. There is also the challenge of determining the clinical significance of any observed immune alterations. Will such a change lead to disease, or is it a transient subclinical observation related to short-term stress? The effect of this problem may be observed by scanning publications associated with immunity and spaceflight, which began to appear during the 1970s. Although individually they are each valid studies, the comprehensive literature to date suffers from widely varying sampling methods and assay techniques, low subject counts, and sometimes a disparate focus on narrow aspects of immunity. The most clinically relevant data are derived from in-flight human studies, which have demonstrated altered cell-mediated immunity and reactivation of latent herpes viruses. Much more data are available from post-flight testing of humans, with clear evidence of altered cytokine production patterns, altered leukocyte distribution, continued latent viral reactivation, and evidence of dramatically altered virus-specific immunity. It is unknown if post-flight assessments relate to the in-flight condition or are a response to landing stress and readaptation. In-flight culture of cells has clearly demonstrated that immune cells are gravity-sensitive and display altered functional characteristics. It is unknown if these data are related to in vivo immune cell function or are an artifact of microgravity culture. Ground analog testing of humans and animals, as well as microgravity-analog cell culture, has demonstrated utility. However, in all cases, it is not known with certainty if these data would reflect similar testing during space travel. Given their ready availability, ground analogs may be extremely useful for assay development and the evaluation of potential countermeasures. In general, the evidence base suffers from widely disparate studies on small numbers of subjects that do not directly correlate well with each other or spaceflight itself. Also lacking are investigations of the effect of gender on adaption to spaceflight. This results in significant knowledge 'gaps' that must be filled by future studies to completely determine any clinical risk related to immunity for human exploration-class space missions. These gaps include a significant lack of in-flight data, particularly during long-duration space missions. The International Space Station represents an excellent science platform with which to address this knowledge gap. Other knowledge gaps include lack of a single validated ground analog for the phenomenon and a lack of flight-compatible laboratory equipment capable of monitoring astronauts (for either clinical or research purposes). However, enough significant data exist, as described in this manuscript, to warrant addressing this phenomenon during the utilization phase of the ISS. A recent Space Shuttle investigation has confirmed the 31 in-flight nature of immune dysregulation, demonstrating that it is not merely a post-flight phenomenon. Several current studies are ongoing onboard the ISS that should thoroughly characterize the phenomenon. NASA recognizes that if spaceflight-associated immune dysregulation persists during exploration flights in conjunction with other dangers, such as high-energy radiation, the result may be a significant clinical risk. This emphasizes the need for a continued integrated comprehensive approach to determining the effect of prolonged spaceflight, separated from transient launch and landing stresses, on human immunity. After such studies, the phenomenon will be understood, and, hopefully, a monitoring strategy will have been developed that could be used to monitor the effectiveness of countermeasure

Crucian, Brian↗

NASA NTRS2016

Near-Infrared Monitoring of Volatiles in Frozen Lunar Simulants While Drilling

In Situ Resource Utilization (ISRU) focuses on using local resources for mission consumables. The approach can reduce mission cost and risk. Lunar polar volatiles, e.g. water ice, have been detected via remote sensing measurements and represent a potential resource for both humans and propellant. The exact nature of the horizontal and depth distribution of the ice remains to be documented in situ. NASA's Resource Prospector mission (RP) is intended to investigate the polar volatiles using a rover, drill, and the RESOLVE science package. RP component level hardware is undergoing testing in relevant lunar conditions (cryovacuum). In March 2015 a series of drilling tests were undertaken using the Honeybee Robotics RP Drill, Near-Infrared Volatile Spectrometer System (NIRVSS), and sample capture mechanisms (SCM) inside a 'dirty' thermal vacuum chamber at the NASA Glenn Research Center. The goal of these tests was to investigate the ability of NIRVSS to monitor volatiles during drilling activities and assess delivery of soil sample transfer to the SCMs in order to elucidate the concept of operations associated with this regolith sampling method.

Neutron Spectrometer System↗

NASA NTRS2016

Wind Information Uplink to Aircraft Performing Interval Management Operations

Interval Management (IM) is an ADS-B-enabled suite of applications that use ground and flight deck capabilities and procedures designed to support the relative spacing of aircraft (Barmore et al., 2004, Murdoch et al. 2009, Barmore 2009, Swieringa et al. 2011; Weitz et al. 2012). Relative spacing refers to managing the position of one aircraft to a time or distance relative to another aircraft, as opposed to a static reference point such as a point over the ground or clock time. This results in improved inter-aircraft spacing precision and is expected to allow aircraft to be spaced closer to the applicable separation standard than current operations. Consequently, if the reduced spacing is used in scheduling, IM can reduce the time interval between the first and last aircraft in an overall arrival flow, resulting in increased throughput. Because IM relies on speed changes to achieve precise spacing, it can reduce costly, low-altitude, vectoring, which increases both efficiency and throughput in capacity-constrained airspace without negatively impacting controller workload and task complexity. This is expected to increase overall system efficiency. The Flight Deck Interval Management (FIM) equipment provides speeds to the flight crew that will deliver them to the achieve-by point at the controller-specified time, i.e., assigned spacing goal, after the target aircraft crosses the achieve-by point (Figure 1.1). Since the IM and target aircraft may not be on the same arrival procedure, the FIM equipment predicts the estimated times of arrival (ETA) for both the IM and target aircraft to the achieve-by point. This involves generating an approximate four-dimensional trajectory for each aircraft. The accuracy of the wind data used to generate those trajectories is critical to the success of the IM operation. There are two main forms of uncertainty in the wind information used by the FIM equipment. The first is the accuracy of the forecast modeling done by the weather provider. This is generally a global environmental prediction obtained from a weather model such as the Rapid Refresh (RAP) from the National Centers for Environmental Prediction (NCEP). The weather forecast data will have errors relative to the actual, or truth, winds that the aircraft will encounter. The second source of uncertainty is that only a small subset of the forecast data can be uplinked to the aircraft for use by the FIM equipment. This results in loss of additional information. The Federal Aviation Administration (FAA) and RTCA are currently developing standards for the communication of wind and atmospheric data to the aircraft for use in NextGen operations. This study examines the impact of various wind forecast sampling methods on IM performance metrics to inform the standards development.

Ahmad, Nashat N.↗

NASA NTRS2010

Failure Bounding And Sensitivity Analysis Applied To Monte Carlo Entry, Descent, And Landing Simulations

In the study of entry, descent, and landing, Monte Carlo sampling methods are often employed to study the uncertainty in the designed trajectory. The large number of uncertain inputs and outputs, coupled with complicated non-linear models, can make interpretation of the results difficult. Three methods that provide statistical insights are applied to an entry, descent, and landing simulation. The advantages and disadvantages of each method are discussed in terms of the insights gained versus the computational cost. The first method investigated was failure domain bounding which aims to reduce the computational cost of assessing the failure probability. Next a variance-based sensitivity analysis was studied for the ability to identify which input variable uncertainty has the greatest impact on the uncertainty of an output. Finally, probabilistic sensitivity analysis is used to calculate certain sensitivities at a reduced computational cost. These methods produce valuable information that identifies critical mission parameters and needs for new technology, but generally at a significant computational cost.

Gaebler, John A.↗

NASA NTRS2019

Sensor Analysis, Modeling, and Test for Robust Propulsion System Autonomy

An approach is presented supporting analysis, modeling, and test validation of operational flight instrumentation (OFI) that facilitates critical functions for the Space Launch System (SLS) main propulsion system (MPS). Certain types of OFI sensors were shown to exhibit highly nonlinear and non-gaussian noise characteristics during acceptance testing, motivating the development of advanced modeling and simulation (M&S) capability to support algorithm verification and flight certification. Hardware model and algorithm simulation fidelity was informed by a risk scoring metric; redesign of high-risk algorithms using test-validated sensor models significantly improved their expected performance as evaluated using Monte Carlo acceptance sampling methods. Autonomous functions include closed-loop ullage pressure regulation, pressurant leak detection, and fault isolation for automated safing and crew caution and warning (C&W).

Orr, Jeb S.↗

NASA NTRS2019

Risk Estimation of Threatening Asteroids

When faced with the question of designing an asteroid deflection mission or with the decision of launching it, significant uncertainties are present in the asteroid’s physical properties, and its orbit solution. The success of the deflection mission relies heavily on these aspects. For example, a heavier than expected asteroid will reduce the imparted deflection DV. So will a larger porosity value by reducing the beta factor [1]. Here, we present a new capability that estimates asteroid impact risk under consideration of these uncertainties. The new method samples the uncertainty space along multiple dimensions, performs a predetermined deflection, propagates the deflected samples to the Earth, models the impact damage, and estimates the overall risk outcome. The work builds on the Probabilistic Asteroid Impact Risk (PAIR) assessment tool [2] by including orbital uncertainty and deflection capabilities. We demonstrate this risk estimation approach for threatening asteroids using the example of the fictitious impactor 2019 PDC. Such analysis provides a quantitative basis for the work of decision makers and disaster managers. It may further find application in areas such as mitigation mission planning where projected post-mitigation risk can be compared to premitigation levels as a means of cost-benefit analysis formitigation options.

Rumpf, Clemens↗

NASA NTRS2021

Predicting near-saturated hydraulic conductivity in urban soils

Pedotransfer functions (PTFs) provide point predictions of soil hydraulic properties from more readily measured soil characteristics, yet uncertainties and biases in measurement methods, sampling distributions, and boundary conditions can limit accuracy when estimating near-saturated hydraulic conductivity (K(n)). These limitations may be particularly problematic in understudied urban landscapes that often contain altered hydraulic properties. To better treat deficiencies in PTF performance, we addressed three objectives, which were to: 1) develop PTFs to predict urban K(n), 2) assess bulk density and coarse fragments as explanatory variables; and 3) evaluate the predictive capability of these PTFs by comparing their output to measured hydraulic conductivity values from three other studies of urban soil hydraulics. We used artificial neural networks (ANN) and random forest (RF) approaches to predict urban K(n), with the training dataset including 307 tension infiltrometer tests and other measurements drawn from urban soil assessments in 11 U.S. cities. The PTFs utilized a hierarchy of inputs, starting with percentage sand, silt, clay, and then adding percentage coarse fragments and bulk density. The ANN models performed similar to the RF models, and all models exhibited similar or better predictive performance as models results collected from published articles. The inclusion of bulk density or coarse fragments did not improve accuracy over soil texture alone. Possible reasons for this result include low correlation between K(n) and bulk density and the exclusion of large voids during flow measurements with tension infiltrometers. The models have been made available as an open-source software package to encourage adoption by users working in urban systems.

Jinshi Jian↗

NASA NTRSDate not supplied

The Stop-and-Go Mechanism: Towards an Integrated Approach to Model Seismicity, Outgassing, Deformation, and Thermal Unrest at Active Volcanoes

Connecting the geophysical and geochemical signals recorded at and above the surface of volcanoes with source mechanisms is fundamental to understand transitions from quiescence to eruption, and to integrate the behavior of volcanoes with their regional seismotectonic and hydrological context. Some of these signals include shallow volcanic tremor, a long-lasting (minutes-to-years) ground vibration detected in volcanic areas during unrest; volcanic outgassing, which shows intriguing periodicities over multiple scales, as revealed by space-borne instruments and by ground-based, high-frequency (~1 Hz), sampling methods; inflation and deflation of volcanic edifices, commonly associated with subsurface volume changes; and large-scale (from a few to tens of km2), low-temperature, thermal anomalies, a newly-discovered signal that has been observed to emerge on volcanic flanks from months-to-years prior to gas- and magma-driven eruptions. Traditionally, these geophysical and geochemical signals have been modelled independently, which limits our interpretation of subsurface processes and thus our assessment of unrest. In this work, we show through lumped-parameter models, numerical simulations, and preliminary laboratory experiments that many of the signals recorded around volcanoes can be integrated into a common “stop-and-go” mechanism. In particular, we found that they can arise spontaneously when taking into account the feedbacks between the temporary accumulation of gas and/or magma in the crust (“stop”), and the diffusive transfer of gas and heat towards the surface (“go”). For example, we find that the “stop-and-go” mechanism can explain: (i) the emergence of monochromatic, broadband, and harmonic tremor; (ii) the periodic components commonly observed in volcanic outgassing time series; (iii) the link between large-scale thermal anomalies and shallow hydrothermal systems; (iv) the reported time lags between large-scale thermal anomalies and deformation; and (v) the breathing of potentially destructive volcanic calderas. The “stop-and-go” mechanism provides a consistent and realistic framework to link multiple geophysical and geochemical signals with the processes leading to volcanic unrest and eruption.

volcanoes↗

NASA NTRSDate not supplied

Testing and validation of the microbial environment of the NASA rodent spaceflight habitat water delivery system.

Sterilized, deionized water within a closed, self-sufficient system has been used in NASA spaceflight rodent studies for several decades. Within the specialized spaceflight rodent habitat, water is delivered through a compression spring-loaded bag system to maintain positive pressure. Refill of the drinking water occurs every 30 days by direct transfer of potable water from aboard the International Space Station (ISS). This enables long term use without a weekly water change out, which meets spaceflight requirements, but contrasts with the general guidelines for the sanitation of water delivery systems. Even though the water is iodinated to minimize microbial growth, rodents are fed a special diet of high moisture nutrient-rich food bars based on the AIN-93 diet that may contribute to microbial growth in this water system. We designed a ground study to assess the quality of drinking water that is given to rodents throughout a mission. We conducted the ground test using 20 female C57BL/6J mice housed in this specialized habitat to mimic the timeline of a 90-day mission as well as the environmental conditions (temperature, humidity, and pCO2) within the ISS. We used a novel sampling method to test water at 2-week intervals for the 90-days, and also after each 30-day refill of the water delivery system. Mice in standard vivarium cages with water bottles were also included for comparison to the habitat. The results showed that overall microbial load remained close to zero for the duration, while total organic compound concentrations increased from 1370g/L to 10650g/L over the course of 90 days but remained below the level of concern. Inorganic ions and pH were also found to be at acceptable levels. Overall, we conclude that this system is effective in delivering clean, potable water to rodents for the 90-day duration of current missions to the ISS.

water↗

NASA NTRSDate not supplied

Enumeration and Fluorescence In Situ Hybridization of Microbial Bioburden on Cleanroom Surfaces

Introduction: Microorganisms are everywhere on Earth, even in the cleanest of places. Spacecraft assembly cleanrooms can harbor low levels of living and dead microbial cells (e.g., [1,2]), and cleanroom bioburden can also include organic molecules from industrial sources and in situ biomass. Life detection missions require careful attention to avoid contaminants that can be easily convoluted with analytical targets. We are evaluating epifluorescent microscopy and fluorescence in situ hybridization (FISH) as methods to complement organic contamination detection techniques. Epifluorescent cell counting offers an accurate and cost-effective way to quantify low levels of surface biomass. FISH could allow for the identification of residual organisms, and can be targeted to detect active populations of specific organisms such as bacteria known to resist cleaning procedures. This effort is part of a larger study that is concentrated on characterizing the surface and airborne molecular organic contamination background in Johnson Space Center (JSC) Astromaterials curation laboratories and Goddard Space Flight Center (GSFC) spacecraft assembly rooms, and understanding contaminants in the context of cleaning procedures and residual bioburden. Methods: Samples were collected by swabbing surfaces in ISO 5 and ISO 7 equivalent cleanrooms at JSC. Swabs for FISH were fixed in 4% paraformaldehyde (PFA) for 3 hours and then stored in 1:1 ethanol:PBS, while swabs for cell counting were stored in 4% PFA until analysis to avoid any cell loss during centrifugation that could impact quantification of very low biomass samples. Cell counting was performed with SYBR Gold as in [3], but adapted for very low biomass. FISH was performed as in [4], using DAPI as a counterstain for all DNA-containing cells. Negative controls included wells with no probe applied, to test for natural fluorescence, as well as the nonsense probe NONEUB (reverse complement of EUB338) to evaluate non-specific probe binding. Results and Discussion: Cleanroom surfaces had 102-103 cells cm-2. The extremely low biomass of these samples was challenging for enumeration, and required careful and routine use of “field” and laboratory blanks. FISH was performed with the general archaeal and bacterial probes ARCH915 and EUB338 (EUBMIX, [4]), probe GAMBET ([4]), and PSE227, which targets the genus Pseudomonas [5]). The latter two probes were selected because Pseudomonas spp. and other Gammaproteobacteria have not been isolated from cleanroom surfaces but do appear frequently in rRNA gene libraries from these surfaces. While some active bacteria were identified (Fig. 1c), most cells detectable by DAPI did not have a strong or any fluorescent signal (e.g., Fig. 1d), indicating that the vast majority of cells are dead or inactive. This suggests that cleaning protocols are effective at inactivating microbial contaminants, but that dead or inactive cells can remain on surfaces. Cells were often clumped in a weakly autofluorescent matrix, possibly biofilm material (Fig. 1c,d). We also observed other particulate material that was collected by the swabs, including apparent textile fibers (Fig. 1b). Our results are consistent with other studies that show that the bioburden present in clean rooms includes active, dormant, and dead cells. We will discuss how FISH and epifluorescent cell counting could be applied in planetary protection protocols, including the advantages and disadvantages of FISH and cell counting for routine use, as well as different possible applications for more specialized FISH procedures. References: [1] Moissl-Eichinger et al. (2015) Sci Rep, 5, 9156 [2] Hendrickson et al. (2021) Microbiome, 9, 238 [3] Jones et al. (2017) Appl Environ Microbiol, 83, e00909-17 [4] Jones et al. (2015) Appl Environ Microbiol, 81, 1242-1250. [5] Watt et al. (2006) Environ Microbiol, 8, 871-884

C J Huff↗

NASA NTRSDate not supplied

Uncertainty Quantification using Deep Ensembles for Decision Making in Cyber-Physical-Human Systems

In this paper and its companion, Differential Equation Approximation Using Gradient-Boosted Quantile Regression, Robison et al., we examine an approach to quantifying model uncertainty with the aim of increasing the trustworthiness of computational models in human-machine interactions. In Differential Equation Approximation Using Gradient-Boosted Quantile Regression, we focus on gradient-boosted decision trees, while in this one, we give more details about deep ensembles. Uncertainty quantification is crucial for building trustworthy autonomous decision-making agents in human-machine teams. There are two types of uncertainties: aleatoric and epistemic. The former is related to the inherent stochasticity (noise) of the process, whereas the latter is associated with the lack of knowledge or representation capability of models, such as neural networks. By lack of knowledge, we mean the model’s inability to accurately predict outputs for all possible inputs. The aleatory uncertainty can be estimated fairly easily with, for example, filters, whereas epistemic uncertainty is challenging to compute. This paper uses deep ensembles to quantify both aleatory and epistemic uncertainty. It can act as an uncertainty-aware surrogate transition model for decision-making frameworks. "Uncertainty-aware" means that the surrogate transition model should make predictions along with confidence in those predictions. In the context of decision-making, the transition models are ordinary differential equations (ODEs). Since ODEs can be simulated to make one-step or multi-step predictions, a good surrogate model for them should perform reasonably well in both modes. In a multi-step approach, the trajectory sampling method TS∞ was used to propagate uncertainty over multiple steps. The cartpole dynamical system was selected to demonstrate the ability of deep ensembles as good surrogate transition models for decision-making frameworks. The deep ensembles modeled the dynamics of cartpole ODEs and made uncertainty-aware predictions in single-step and multi-step transition modes.

CPH systems↗