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NASA NTRSDate not supplied

Robust Path-following Controller for Multirotor Vehicles in Uncertain Wind Conditions

This paper presents simulations of L1 adaptive controller on a multirotor vehicle for compensation of convective winds. There are increasing efforts to utilize unmanned vehicles for fighting wildfires, but such vehicles need to be able to compensate for convective updrafts and other uncertainties (e.g., wind shear and turbulence) caused by the wildfire. Other application domains, such as urban air mobility, also must account for convective or uncertain winds present in urban microclimates. Geometric controllers have great tracking performance properties in environments without uncertainties, but the tracking performance degrades when wind disturbances and external loads are present in the environment. Introducing L1 adaptive control into the controller architecture compensates for these wind disturbances and reduces the tracking error caused by such disturbances. The controller architecture is implemented on a small quadrotor. The simulations demonstrate the advantages of the L1 adaptive augmentation for a sample figure-eight trajectory while encountering unknown variable wind conditions with an external load.

John L Bullock↗

NASA NTRSDate not supplied

Robust Path-following Controller for Multirotor Vehicles in Uncertain Wind Conditions

John Bullock↗

NASA NTRS2014

Organic Contamination Baseline Study in NASA Johnson Space Center Astromaterials Curation Laboratories

Future robotic and human spaceflight missions to the Moon, Mars, asteroids, and comets will require curating astromaterial samples with minimal inorganic and organic contamination to preserve the scientific integrity of each sample. 21st century sample return missions will focus on strict protocols for reducing organic contamination that have not been seen since the Apollo manned lunar landing program. To properly curate these materials, the Astromaterials Acquisition and Curation Office under the Astromaterial Research and Exploration Science Directorate at NASA Johnson Space Center houses and protects all extraterrestrial materials brought back to Earth that are controlled by the United States government. During fiscal year 2012, we conducted a year-long project to compile historical documentation and laboratory tests involving organic investigations at these facilities. In addition, we developed a plan to determine the current state of organic cleanliness in curation laboratories housing astromaterials. This was accomplished by focusing on current procedures and protocols for cleaning, sample handling, and storage. While the intention of this report is to give a comprehensive overview of the current state of organic cleanliness in JSC curation laboratories, it also provides a baseline for determining whether our cleaning procedures and sample handling protocols need to be adapted and/or augmented to meet the new requirements for future human spaceflight and robotic sample return missions.

Calaway, Michael J.↗

NASA NTRS2008

Systems and methods for self-synchronized digital sampling

Systems and methods for self-synchronized data sampling are provided. In one embodiment, a system for capturing synchronous data samples is provided. The system includes an analog to digital converter adapted to capture signals from one or more sensors and convert the signals into a stream of digital data samples at a sampling frequency determined by a sampling control signal; and a synchronizer coupled to the analog to digital converter and adapted to receive a rotational frequency signal from a rotating machine, wherein the synchronizer is further adapted to generate the sampling control signal, and wherein the sampling control signal is based on the rotational frequency signal.

Samson, Jr., John R.↗

DOE OSTI2026

Adaptive optical correction for in vivo two-photon fluorescence microscopy with neural fields

Adaptive optics restore ideal imaging performance in complex samples by measuring and correcting optical aberrations but often require custom-built microscopes with carefully aligned wavefront sensing/shaping devices and can be susceptible to sample motion. Here we describe NeAT, a computational framework using neural fields for adaptive optics two-photon fluorescence microscopy. NeAT estimates wavefront aberration and recovers sample structure from a 3D image stack without requiring external datasets for training. Incorporating motion correction in learning and correcting conjugation errors commonly found in commercial microscopes, NeAT is designed for deployment in biological laboratories for in vivo imaging. We validate NeAT’s performance using a custom-built microscope with a wavefront sensor under varying signal-to-noise ratios, aberration and motion conditions. With a commercial microscope, we demonstrate real-time aberration correction for in vivo morphological and functional imaging in the living mouse brain, with NeAT improving the signal and accuracy of glutamate and calcium imaging of synapses and neurons.

Kang, Iksung↗

DOE OSTI2025

Footprints of Worldwide Adaptation in Structured Populations of Drosophila melanogaster Through the Expanded DEST 2.0 Genomic Resource

Abstract Large-scale genomic resources can place genetic variation into an ecologically informed context. To advance our understanding of the population genetics of the fruit fly Drosophila melanogaster, we present an expanded release of the community-generated population genomics resource Drosophila Evolution over Space and Time (DEST 2.0; https://dest.bio/). This release includes 530 high-quality pooled libraries from flies collected across six continents over more than a decade (2009 to 2021), most at multiple time points per year; 211 of these libraries are sequenced and shared here for the first time. We used this enhanced resource to elucidate several aspects of the species' demographic history and identify novel signs of adaptation across spatial and temporal dimensions. For example, we showed that the spatial genetic structure of populations is stable over time, but that drift due to seasonal contractions of population size causes populations to diverge over time. We identified signals of adaptation that vary between continents in genomic regions associated with xenobiotic resistance, consistent with independent adaptation to common pesticides. Moreover, by analyzing samples collected during spring and fall across Europe, we provide new evidence for seasonal adaptation related to loci associated with pathogen response. Furthermore, we have also released an updated version of the DEST genome browser. This is a useful tool for studying spatiotemporal patterns of genetic variation in this classic model system.

Biochemistry & Molecular Biology↗

DOE OSTI2025

A Cloud-Tracking Data Set for the CSAPR2 Adaptive Scanning during TRACER

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility (Mather and Voyles 2013) deployed the first ARM Mobile Facility (AMF1; Miller et al. 2016) near LaPorte, Texas to support the Tracking Aerosol Convection Interactions Experiment (TRACER) (Jensen et al. 2025) near Houston, Texas. From October 2021 to September 2022, AMF1 was deployed to 29.67° N, 95.06° W near LaPorte, Texas and the 2nd Generation C-band Scanning ARM Precipitation Radar (CSAPR2) was deployed to a supplementary site at 29.53° N, 95.28° W (Figure 1). During an intensive operational period (IOP) from 1 June to 30 September 2022, the CSAPR2 sampled precipitation echoes in an adaptive scanning mode following the Multisensor Agile Adaptive Scanning (MAAS) framework (Kollias et al. 2020). MAAS helped optimize the CSAPR2 scan strategy to perform frequent plan position indicator (PPI) and range height indicator (RHI) scans (Lamer et al. 2023). Details of the CSAPR2 scanning, data processing, and calibration procedures used by the principal investigator (PI), and the PI data files are described by Oue et al. (2023). Details of the CSAPR2 operational performance, ARM data processing and correction procedures, and data quality masks are described by Feng et al. (2024a).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Testing Classical Properties from Quantum Data

Many properties of Boolean functions can be tested far more efficiently than the function itself can be learned. However, this dramatic advantage often disappears when testers are limited to random samples of ƒ instead of adaptively chosen queries to f. In this work we investigate the quantum version of this restriction: quantum algorithms that test properties of a Boolean function f solely from copies of either the function state |ƒ⟩ ∝ ∑ x |x, ƒ(x)⟩ or the phase state |(-1) ƒ ⟩ ∝ ∑ x (-1) ƒ(x) |x⟩. For monotonicity, symmetry, and triangle-freeness, we show passive quantum testers are unboundedly or super-polynomially better than their classical passive testing counterparts. They are competitive with classic query -based testers in each case. Our new testers use techniques beyond quantum Fourier sampling, and it turns out this is necessary: we show a certain class of bent functions can be tested from 𝒪(1) function states but has a sample complexity lower bound of 2 Ω(n) for any tester relying exclusively on Fourier and classical samples. Our passive quantum testers are competitive with classical query -based testers, but this isn't universal: we exhibit a testing problem that can be solved from 𝒪(1) classical queries but requires Ω(2 n/2 ) function state copies. The Forrelation problem provides a separation of the same magnitude in the opposite direction, so we conclude that quantum data and classical queries are "maximally incomparable" resources for testing. We also begin the study of lower bounds for testing from quantum data. For quantum monotonicity testing, we prove that the ensembles of [Goldreich et al., 2000; Black, 2024], which give exponential lower bounds for classical sample-based testing, do not yield any nontrivial lower bounds for testing from quantum data. New insights specific to quantum data will be required for proving copy complexity lower bounds for testing in this model.

Boolean Functions↗

NASA NTRSDate not supplied

Assessing the Relationships Between Sensorimotor Biomarkers and Post-Landing Functional Task Performance

Spaceflight drives adaptive changes in healthy individuals appropriate for sensorimotor function in a microgravity environment. These changes are maladaptive for return to earth's gravity. The inter-individual variability of sensorimotor decrements is striking, although poorly understood. The goal of this study was to identify a set of behavioral, neuroimaging and genetic measures that can be used to predict early post-flight performance on a set of sensorimotor tasks. Astronauts were recruited who previously participated in sensorimotor field tests and/or posturography soon after long-duration spaceflight. Behavioral tests included assessments of sensory dependency and adaptability. Visual dependency involved treadmill walking while viewing a moving virtual visual scene. Vestibular perceptual thresholds were measured while seated during lateral translations. Proprioception dependency was measured during one-legged stance on a horizontal air-bearing surface. Ground assessment of adaptability was performed (1) during treadmill walking with a virtual linear hallway and a moving walking surface, and (2) during multiple trials of navigating an obstacle course while wearing reversing prisms (adaptive Functional Mobility Test, aFMT). The neuroimaging tests characterized individual differences in regional brain volumes (using Structural MRI) and white matter microstructure (using Diffusion Tensor Imaging) to serve as potential predictors of adaptive capacity. The genetic tests utilized saliva samples to examine variations in four genes chosen because of their ability to differentiate sensorimotor adaptation ability in a normative population, including Catechol-O-methyltransferase (COMT), Dopamine Receptor D2 (DRD2), Brain-derived neurotrophic factor (BDNF) and the α2-adrenergic receptor. Thirty ISS crewmembers were recruited, including 12 first-time fliers, 6F, and mission durations lasting 185.5 ± 45.5 days, mean ± std. We utilized a combination of three post-flight functional task outcomes: tandem walk, recovery from fall and dynamic posturography. There was considerable variability among all post-flight performance outcomes. Based on an ordinal scale survey, 72% indicated their ability to perform functional tasks were more impacted postflight relative to inflight with 50% indicating they needed to restrict movements for a longer period postflight relative to inflight. While there is a strong association within tests obtained at different R+0 timepoints, by R+24 hr performance on one post-flight test does not necessarily correlate with performance on other post-flight tests. Preliminary statistical analysis indicates combining biomarkers will increase predictive power and this will be explored with future analyses. Our preliminary findings underscore the importance of a comprehensive post-flight test battery including different types of tasks with varying sensory feedback. Understanding the relationships between these sensorimotor biomarkers and post-flight functional task performance improve both our understanding of the individual variability and our strategy to optimize sensorimotor countermeasures.

biomarkers↗

NASA NTRS2020

Preparing for Mars 2020 and Future Space Missions: Technology Advancements Driving Contamination Control Requirements and Cleanroom Protocols

Future space exploration missions will force contamination control requirements to become more strict to support increasingly sensitive instrumentation and search for life missions. Driving issues for these extremely clean requirements include increased instrument sensitivity, return sample science, and protecting ambitious mission science objectives. Preparing to meet these requirements mandates that contamination control provide new guidelines and more involved support for the cleanrooms during flight hardware assembly, including establishing better methods for setting cleanroom personnel limits to reduce particle fall out in cleanrooms. Limited literature exists for universal methods of determining cleanroom personnel limits, and what does exist includes mostly theory and assumptions on determining the limit. In this work, published method will be assessed against particle fall out data collected from the ISO 5 cleanrooms of the Mars 2020 Perseverance Rover assembly. Additional evaluations will assess contamination control required cleanroom protocols and the overall success of meeting strict cleanliness requirements of the Adaptive Caching Assembly (ACA) and sample tubes to safeguard future scientific endeavors.

Chen, Nicole↗

NASA NTRS2015

Wetlab-2 - Quantitative PCR Tools for Spaceflight Studies of Gene Expression Aboard the International Space Station

Wetlab-2 is a research platform for conducting real-time quantitative gene expression analysis aboard the International Space Station. The system enables spaceflight genomic studies involving a wide variety of biospecimen types in the unique microgravity environment of space. Currently, gene expression analyses of space flown biospecimens must be conducted post flight after living cultures or frozen or chemically fixed samples are returned to Earth from the space station. Post-flight analysis is limited for several reasons. First, changes in gene expression can be transient, changing over a timescale of minutes. The delay between sampling on Earth can range from days to months, and RNA may degrade during this period of time, even in fixed or frozen samples. Second, living organisms that return to Earth may quickly re-adapt to terrestrial conditions. Third, forces exerted on samples during reentry and return to Earth may affect results. Lastly, follow up experiments designed in response to post-flight results must wait for a new flight opportunity to be tested.

ISS research platform↗

NASA NTRS1992

Direct Adaptive Control Of An Industrial Robot

Decentralized direct adaptive control scheme for six-jointed industrial robot eliminates part of overall computational burden imposed by centralized controller and degrades performance of robot by reducing sampling rate. Control and controller-adaptation laws based on observed performance of manipulator: no need to model dynamics of robot. Adaptive controllers cope with uncertainties and variations in robot and payload.

Seraji, Homayoun↗

NASA NTRS1987

SMI adaptive antenna arrays for weak interfering signals

The performance of adaptive antenna arrays is studied when a sample matrix inversion (SMI) algorithm is used to control array weights. It is shown that conventional SMI adaptive antennas, like other adaptive antennas, are unable to suppress weak interfering signals (below thermal noise) encountered in broadcasting satellite communication systems. To overcome this problem, the SMI algorithm is modified. In the modified algorithm, the covariance matrix is modified such that the effect of thermal noise on the weights of the adaptive array is reduced. Thus, the weights are dictated by relatively weak coherent signals. It is shown that the modified algorithm provides the desired interference protection. The use of defocused feeds as auxiliary elements of an SMI adaptive array is also discussed.

Gupta, I. J.↗

DOE OSTI2025

Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification

Non-invasive simulations of coronary hemodynamics have improved clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches to distribute total coronary flow amongst the arteries in the coronary tree, which ignores patient variability, the presence of disease, and other clinical factors. Further, uncertainty in the clinical data often remains unaccounted for in the modeling pipeline. We present an end-to-end uncertainty-aware pipeline to (1) personalize coronary flow simulations by incorporating vessel-specific coronary flows as well as cardiac function; and (2) predict clinical and biomechanical quantities of interest with improved precision, while accounting for uncertainty in the clinical data. We assimilate patient-specific measurements of myocardial blood flow from clinical CT myocardial perfusion imaging to estimate branch-specific coronary artery flows. Simulated noise in the clinical data is used to estimate the joint posterior distributions of the model parameters using adaptive Markov Chain Monte Carlo sampling. Additionally, the posterior predictive distribution for the relevant quantities of interest is determined using a new approach combining multi-fidelity Monte Carlo estimation with non-linear, data-driven dimensionality reduction. This leads to improved correlations between high- and low-fidelity model outputs. Our framework accurately recapitulates clinically measured cardiac function as well as branch-specific coronary flows under measurement noise uncertainty. We observe substantial reductions in confidence intervals for estimated quantities of interest compared to single-fidelity Monte Carlo estimation and state-of-the-art multi-fidelity Monte Carlo methods. This holds especially true for quantities of interest that showed limited correlation between the low- and high-fidelity model predictions. In addition, the proposed multi-fidelity Monte Carlo estimators are significantly cheaper to compute than traditional estimators, under a specified confidence level or variance. The proposed pipeline for personalized and uncertainty-aware predictions of coronary hemodynamics is based on routine clinical measurements and recently developed techniques for CT myocardial perfusion imaging. The proposed pipeline offers significant improvements in precision and reduction in computational cost.

Bayesian parameter estimation↗

DOE OSTI2025

Modeling Sepsis: Establishment and Validation of a 72-Hour Swine Model of Penetrating Abdominal Trauma

Background/Objectives: Fecal peritonitis following penetrating abdominal trauma is a serious condition that often results in sepsis and organ failure. The aim of our study was to develop a novel conscious porcine model of sepsis and organ dysfunction caused by multiple penetrating injuries to the small and large intestines. Methods: Twelve female Yorkshire pigs (average weight 50.6 ± 6.5 kg) were divided into two groups: Penetrating Abdominal Trauma (PAT) (n = 8) and Control (n = 4). All surgical procedures were performed under anesthesia with adequate analgesia. In the PAT group, the small and large intestines were punctured, and feces mixed with saline were introduced into the abdominal cavity to induce peritonitis. The Control group received sham surgery with only saline solution. The animals were observed in a conscious state over a period of 72 h, vital parameters were recorded, and blood samples were taken regularly. We adapted a pig-specific SOFA score and developed pig-specific SIRS criteria and NEWS2 score to assess organ function. The model was validated by independent investigators. Results: The survival rate in the PAT group was 75%, with an average survival time of 58.5 h, while all animals in the Control group survived to euthanasia. Monitoring showed pathophysiological changes, such as tachycardia, leucopenia, and thrombocytopenia, indicative of sepsis and organ dysfunction. Blinded investigators independently confirmed the model’s validity. Conclusions: A new swine model of penetrating abdominal trauma and sepsis has been successfully developed that demonstrates significant physiological and immunologic changes comparable to human sepsis. This new model provides a realistic platform for future research into sepsis, its diagnostics, and the evaluation of therapeutic strategies.

General & Internal Medicine↗

NASA NTRS1972

Kullback-Leibler information function and the sequential selection of experiments to discriminate among several linear models

The error variance of the process prior multivariate normal distributions of the parameters of the models are assumed to be specified, prior probabilities of the models being correct. A rule for termination of sampling is proposed. Upon termination, the model with the largest posterior probability is chosen as correct. If sampling is not terminated, posterior probabilities of the models and posterior distributions of the parameters are computed. An experiment was chosen to maximize the expected Kullback-Leibler information function. Monte Carlo simulation experiments were performed to investigate large and small sample behavior of the sequential adaptive procedure.

Sidik, S. M.↗

NASA NTRS1987

A system for conducting igneous petrology experiments under controlled redox conditions in reduced gravity

The Space Shuttle and the planned Space Station will permit experimentation under conditions of reduced gravitational acceleration offering experimental petrologists the opportunity to study crystal growth, element distribution, and phase chemistry. In particular the confounding effects of macro and micro scale buoyancy-induced convection and crystal settling or flotation can be greatly reduced over those observed in experiments in the terrestrial laboratory. Also, for experiments in which detailed replication of the environment is important, the access to reduced gravity will permit a more complete simulation of processes that may have occurred on asteroids or in free space. A technique that was developed to control, measure, and manipulate oxygen fugacities with small quantities of gas which are recirculated over the sample. This system could be adaptable to reduced gravity space experiments requiring redox control.

Williams, Richard J.↗

NASA NTRS2010

Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems

A voice-command human-machine interface system has been developed for spacesuit extravehicular activity (EVA) missions. A multichannel acoustic signal processing method has been created for distant speech acquisition in noisy and reverberant environments. This technology reduces noise by exploiting differences in the statistical nature of signal (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, the automatic speech recognition (ASR) accuracy can be improved to the level at which crewmembers would find the speech interface useful. The developed speech human/machine interface will enable both crewmember usability and operational efficiency. It can enjoy a fast rate of data/text entry, small overall size, and can be lightweight. In addition, this design will free the hands and eyes of a suited crewmember. The system components and steps include beam forming/multi-channel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, model adaption, ASR HMM (Hidden Markov Model) training, and ASR decoding. A state-of-the-art phoneme recognizer can obtain an accuracy rate of 65 percent when the training and testing data are free of noise. When it is used in spacesuits, the rate drops to about 33 percent. With the developed microphone array speech-processing technologies, the performance is improved and the phoneme recognition accuracy rate rises to 44 percent. The recognizer can be further improved by combining the microphone array and HMM model adaptation techniques and using speech samples collected from inside spacesuits. In addition, arithmetic complexity models for the major HMMbased ASR components were developed. They can help real-time ASR system designers select proper tasks when in the face of constraints in computational resources.

Huang, Yiteng↗