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At least 649 records · Page 36

LANDO: Developing Autonomous Payload Offloading Capabilities for Lunar Surface Operations

Introduction: The Lightweight Surface Manipulation System (LSMS) AutoNomy capabilities Development for surface Operations and construction (LANDO) project is an Early Career Initiative selected for funding by NASA Space Technology Mission Directorate. LANDO is developing a general-purpose autonomy framework applicable to serial and tension-actuated manipulation agents, that will be validated using an existing prototype of the LSMS-L35 (35-kg wrist lift capacity on the lunar surface [Fig. 1], sized for a Commercial Lunar Pay-load Services (CLPS) mission). The autonomous LSMS-L35 will be used to demonstrate autonomous payload handling capabilities for Lunar and other planetary surfaces, directly addressing STMD capability gaps in autonomous excavation and construction operations, advanced robotics and spacecraft autonomy technologies, and technologies supporting emerging space industries including the In-Space Servicing, Assembly and Manufacturing national strategy. LSMS: The LSMS is a tension actuated robotic agent that is scalable (reach and lifting capacity in different gravity environments), versatile (types of surface operations), and reusable. Compared to serial arms, the LSMS provides significantly higher structural efficiency and mechanical advantage, enabling a greater payload lift capacity at a lower system mass. The LSMS is envisioned to be a crucial part of the excavation and construction portfolio, capable of supporting a variety of activities on the lunar surface. Autonomous payload handling is one of the first activities the LSMS can support that develops capabilities that are extensible to other surface operations. Payload handling is required to: remove payloads from a lander; place payloads on mobile agents for transport from a lander to construction site/assembly point; emplace payloads in their operational configuration, and aggregate components to create an asset. As an example of this critical gap, manifested CLPS missions do not currently have a ubiquitous payload offloading capability; payloads (excluding rovers) are designed to remain on the lander. Why Autonomy? Autonomous robotic systems capable of carrying out excavation and construction operations are a fundamental and critical capability required for realizing the NASA Artemis program vision to “emplace and build the infrastructure, systems, and robotic missions that can enable a sustained lunar surface presence.” While teleoperation is still feasible for lunar surface operations, increased latency at Mars will require validated supervised autonomous technologies capable of operating with minimal human involvement (human-on-the-loop) unless an unexpected event occurs requiring human intervention. Autonomy reduces operator burden, allows operations to continue during uncrewed periods, in-creases the safety of operations by automatically detecting and handling faults, and allows operating in high latency environments. Development Activities: LANDO is extending critical autonomous operations to the manipulation domain and creating an integrated system, based on reusable software modules, that is capable of planning and executing payload handling and autonomous surface operations without requiring hu-man intervention beyond a supervisory role. The priority features under development are 1) autonomously offload payloads from a tilted lander deck without buckling the LSMS; 2) sensing whether a payload is safe to lift and handle; and 3) integrate with Astrobotic’s CLPS lander. The poster presentation will highlight current development activities over the past year on LSMS-L35 prototype hard-ware design, and autonomy software.

in-space assembly↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗

Structural basis for human ZBTB7A action at the fetal globin promoter

Elevated levels of fetal globin protect against β-hemoglobinopathies, such as sickle cell disease and β-thalassemia. Two zinc-finger (ZF) repressors, BCL11A and ZBTB7A/LRF, bind directly to the fetal globin promoter elements positioned at -115 and -200, respectively. Here, we describe X-ray structures of the ZBTB7A DNA-binding domain, consisting of four adjacent ZFs, in complex with the -200 sequence element, which contains two copies of four consecutive C:G base pairs. ZF1 and ZF2 recognize the 5' C:G quadruple, and ZF4 contacts the 3' C:G quadruple. Natural non-coding DNA mutations associated with hereditary persistence of fetal hemoglobin (HPFH) impair ZBTB7A DNA binding, with the most severe disruptions resulting from mutations in the base pairs recognized by ZF1 and ZF2. Our results firmly establish ZBTB7A/LRF as a key molecular regulator of fetal globin expression and inform genome-editing strategies that inhibit repressor binding and boost fetal globin expression to treat hemoglobinopathies.

59 BASIC BIOLOGICAL SCIENCES↗

Planning to Explore: Using a Coordinated Multisource Infrastructure to Overcome Present and Future Space Flight Planning Challenges

Few human endeavors present as much of a planning and scheduling challenge as space flight, particularly manned space flight. Just on the operational side of it, efforts of thousands of people across hundreds of organizations need to be coordinated. Numerous tasks of varying complexity and nature, from scientific to construction, need to be accomplished within limited mission time frames. Resources need to be carefully managed and contingencies worked out, often on a very short notice. From the beginning of the NASA space program, planning has been done by large teams of domain experts working months, sometimes years, to put together a single mission. This approach, while proven very reliable up to now, is becoming increasingly harder to sustain. Elevated levels of NASA space activities, from deployment of the new Crew Exploration Vehicle (CEV) and completion of the International Space Station (ISS), to the planned lunar missions and permanent lunar bases, will put an even greater strain on this largely manual process. While several attempts to automate it have been made in the past, none have fully succeeded. In this paper we describe the current NASA planning methods, outline their advantages and disadvantages, discuss the planning challenges of upcoming missions and propose a distributed planning/scheduling framework (CMMD) aimed at unifying and optimizing the planning effort. CMMD will not attempt to make the process completely automated, but rather serve in a decision support capacity for human managers and planners. It will help manage information gathering, creation of partial and consolidated schedules, inter-team negotiations, contingencies investigation, and rapid re-planning when the situation demands it. The fist area of CMMD application will be planning for Extravehicular Activities (EVA) and associated logistics. Other potential applications, not only in the space flight domain, and future research efforts will be discussed as well.

Balaban, Edward↗

A Qualitative Review of Selected Infrared Flow Visualization Processing Techniques: Contrast Enhancement and Frequency Domain Analysis

The deployment and integration of high-sensitivity infrared cameras in a transonic wind tunnel test environment has resulted in a unique capability to image aerodynamic phenomena in real-time. Multi-camera infrared flow visualization data systems are now routinely utilized at the NASA Ames Unitary Plan Wind Tunnel. The small flow-induced temperature gradients on the surface of the wind tunnel test article coupled with the high bit-depth of the infrared camera sensor makes the processing of the image data critically important. An image processing routine must enhance features of interest with minimal artifacts. Additionally, the production wind tunnel test environment demands that these processed images are made available in a real-time, automatic fashion. Therefore, any image processing routine must be computationally economical and enhance the image data with minimal input from a human operator. The following seeks to qualitatively explore selected image processing techniques by assessing their effectiveness to resolve flow features on a wind tunnel test article. A multi-scale contrast enhancement technique is introduced as well as a new implementation of a multi-scale, non-interpolated adaptive histogram equalization. Finally, a novel method is introduced that demonstrates the ability to resolve flow features imaged on bare-steel test articles possessing low emissivity. This method merges frequency domain analysis with contrast enhancement and has the potential to extend the application of infrared flow-visualization within the wind tunnel test environment.

Infrared Imaging↗

Mesoscale structural gradients in human tooth enamel

The outstanding mechanical and chemical properties of dental enamel emerge from its complex hierarchical architecture. An accurate, detailed multiscale model of the structure and composition of enamel is important for understanding lesion formation in tooth decay (dental caries), enamel development (amelogenesis) and associated pathologies (e.g., amelogenesis imperfecta or molar hypomineralization), and minimally invasive dentistry. Although features at length scales smaller than 100 nm (individual crystallites) and greater than 50 µm (multiple rods) are well understood, competing field of view and sampling considerations have hindered exploration of mesoscale features, i.e., at the level of single enamel rods and the interrod enamel (1 to 10 µm). Here, we combine synchrotron X-ray diffraction at submicrometer resolution, analysis of crystallite orientation distribution, and unsupervised machine learning to show that crystallographic parameters differ between rod head and rod tail/interrod enamel. This variation strongly suggests that crystallites in different microarchitectural domains also differ in their composition. Thus, we use a dilute linear model to predict the concentrations of minority ions in hydroxylapatite (Mg 2+ and CO 3 2- /Na + ) that plausibly explain the observed lattice parameter variations. While differences within samples are highly significant and of similar magnitude, absolute values and the sign of the effect for some crystallographic parameters show interindividual variation that warrants further investigation. In conclusion, by revealing additional complexity at the rod/interrod level of human enamel and leaving open the possibility of modulation across larger length scales, these results inform future investigations into mechanisms governing amelogenesis and introduce another feature to consider when modeling the mechanical and chemical performance of enamel.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Review of Well Integrity Based on Field Experience at Carbon Utilization and Storage Sites

Maintaining well integrity is critical to the success of geologic carbon storage (GCS) and carbon dioxide enhanced oil recovery (CO 2 -EOR) operations. Wells that experience leakage because of integrity issues can potentially become a risk to the environment or human health if they release previously captured CO 2 back into the atmosphere or into freshwater aquifers. There are many GCS and CO 2 -EOR sites in operation around the world. However, well integrity experiences at these sites are not widely documented in the public domain. This study details findings from a survey of well integrity experiences elicited from operators of GCS and CO 2 -EOR sites. The goal of the survey was to obtain information about site characteristics and operator experiences with well integrity, monitoring methods, and risk assessment of legacy wells. Literature relevant to the survey questions was also reviewed and summarized to provide context for survey responses and identify areas where field experiences with well integrity do and do not align with the current state of research. We highlight the current state-of-practice, identify research needs, and provide context for future interactions between researchers, operators, and regulators on issues related to well integrity.

54 ENVIRONMENTAL SCIENCES↗

NF-κB and neutrophil extracellular traps cooperate to promote breast cancer progression and metastasis

Highlights: • Cancer cells–derived factors, such as IL-8 and G-CSF, induce NETs formation via PAD4 and NF-κB. • NETs increase the interaction of NEMO with IKKα/β and enhance NF-κB activation. • Blockade of NETs using PAD4 inhibitor decreases NF-κB and tumor metastasis. • Selective inhibition of NF-κB reduces NETs formation and tumor growth and metastasis. Aberrant NF-κB activation and neutrophil extracellular traps (NETs) are associated with breast cancer progression. How NF-κB and NETs modulate each other in breast cancer development remains unclear. Here, we found that NETs induced by phorbol 12-myristate 13-acetate promote breast cancer cell progression. In turn, cancer cells–derived factors, such as IL-8 and granulocyte colony-stimulating factor, stimulate neutrophils to form NETs. Mechanistically, NETs increased the interaction of NF-κB essential modifier (NEMO) with IκB kinase (IKK)α/β and enhanced NF-κB activation. We then employed a cell-permeable peptide corresponding to the NEMO-binding domain (NBD) of IKKα/β, termed NBD peptide, which disrupts NETs-mediated NEMO interaction with IKKα/β and abolished NF-κB activation in vitro. NBD peptide also reduced IL-8 level and NETs formation, and suppressed primary tumor growth and/or lung metastasis in human breast cancer mouse xenograft models and mouse spontaneous breast cancer model. Blockade of NET formation using a peptidylarginine deiminase 4 (PAD4) pharmacologic inhibitor decreased NF-κB activation and tumor metastasis. Collectively, these data suggest that NF-κB associates with NETs to form a positive loop facilitating breast tumor progression and metastasis, and that selective inhibition of NF-κB and PAD4-dependent NETs provides an effective therapeutic approach for treating breast cancer.

60 APPLIED LIFE SCIENCES↗

Distilling nanoscale heterogeneity of amorphous silicon using tip-enhanced Raman spectroscopy (TERS) via multiresolution manifold learning

Abstract Accurately identifying the local structural heterogeneity of complex, disordered amorphous materials such as amorphous silicon is crucial for accelerating technology development. However, short-range atomic ordering quantification and nanoscale spatial resolution over a large area on a-Si have remained major challenges and practically unexplored. We resolve phonon vibrational modes of a-Si at a lateral resolution of <60 nm by tip-enhanced Raman spectroscopy. To project the high dimensional TERS imaging to a two-dimensional manifold space and categorize amorphous silicon structure, we developed a multiresolution manifold learning algorithm. It allows for quantifying average Si-Si distortion angle and the strain free energy at nanoscale without a human-specified physical threshold. The multiresolution feature of the multiresolution manifold learning allows for distilling local defects of ultra-low abundance (< 0.3%), presenting a new Raman mode at finer resolution grids. This work promises a general paradigm of resolving nanoscale structural heterogeneity and updating domain knowledge for highly disordered materials.

36 MATERIALS SCIENCE↗

Advanced Software Development Workstation Project

The Advanced Software Development Workstation Project, funded by Johnson Space Center, is investigating knowledge-based techniques for software reuse in NASA software development projects. Two prototypes have been demonstrated and a third is now in development. The approach is to build a foundation that provides passive reuse support, add a layer that uses domain-independent programming knowledge, add a layer that supports the acquisition of domain-specific programming knowledge to provide active support, and enhance maintainability and modifiability through an object-oriented approach. The development of new application software would use specification-by-reformulation, based on a cognitive theory of retrieval from very long-term memory in humans, and using an Ada code library and an object base. Current tasks include enhancements to the knowledge representation of Ada packages and abstract data types, extensions to support Ada package instantiation knowledge acquisition, integration with Ada compilers and relational databases, enhancements to the graphical user interface, and demonstration of the system with a NASA contractor-developed trajectory simulation package. Future work will focus on investigating issues involving scale-up and integration.

Lee, Daniel↗

Perceived orientation in physical and virtual environments: changes in perceived orientation as a function of idiothetic information available

Two experiments examined perceived spatial orientation in a small environment as a function of experiencing that environment under three conditions: real-world, desktop-display (DD), and head-mounted display (HMD). Across the three conditions, participants acquired two targets located on a perimeter surrounding them, and attempted to remember the relative locations of the targets. Subsequently, participants were tested on how accurately and consistently they could point in the remembered direction of a previously seen target. Results showed that participants were significantly more consistent in the real-world and HMD conditions than in the DD condition. Further, it is shown that the advantages observed in the HMD and real-world conditions were not simply due to nonspatial response strategies. These results suggest that the additional idiothetic information afforded in the real-world and HMD conditions is useful for orientation purposes in our presented task domain. Our results are relevant to interface design issues concerning tasks that require spatial search, navigation, and visualization.

NASA Center ARC↗

Application of Human-Autonomy Teaming to an Advanced Ground Station for Reduced Crew Operations

Within human factors there is burgeoning interest in the "human-autonomy teaming" (HAT) concept as a way to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous systems as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as "plays." It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations, healthcare and medicine, autonomous vehicles, photography, and aviation. The current paper presents one such effort to apply HAT. It details the design of a HAT agent, developed by Human Automation Teaming Solutions, Inc., to facilitate teamwork between the automation and the human operator of an advanced ground dispatch station. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO); consequently, we have named the agent R-HATS. Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by R-HATS, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, R-HATS determines what tasks need to be completed and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. R-HATS has been designed to both support end users and researchers in RCO and HAT. Additionally, R-HATS and its underlying architecture were developed with generalizability in mind as a modular software applicable outside of RCO/aviation domains. This paper will also discuss future further development and testing of RHATS.

automation↗

TRPV4-Rho GTPase complex structures reveal mechanisms of gating and disease

Crosstalk between ion channels and small GTPases is critical during homeostasis and disease, but little is known about the structural underpinnings of these interactions. TRPV4 is a polymodal, calcium-permeable cation channel that has emerged as a potential therapeutic target in multiple conditions. Gain-of-function mutations also cause hereditary neuromuscular disease. Here, we present cryo-EM structures of human TRPV4 in complex with RhoA in the ligand-free, antagonist-bound closed, and agonist-bound open states. These structures reveal the mechanism of ligand-dependent TRPV4 gating. Channel activation is associated with rigid-body rotation of the intracellular ankyrin repeat domain, but state-dependent interaction with membrane-anchored RhoA constrains this movement. Notably, many residues at the TRPV4-RhoA interface are mutated in disease and perturbing this interface by introducing mutations into either TRPV4 or RhoA increases TRPV4 channel activity. Together, these results suggest that RhoA serves as an auxiliary subunit for TRPV4, regulating TRPV4-mediated calcium homeostasis and disruption of TRPV4-RhoA interactions can lead to TRPV4-related neuromuscular disease. These insights will help facilitate TRPV4 therapeutics development.

59 BASIC BIOLOGICAL SCIENCES↗

Screening the complex biological behavior of late lanthanides through genome-wide interactions

Abstract Despite their similar physicochemical properties, recent studies have demonstrated that lanthanides can display different biological behaviors. Hence, the lanthanide series can be divided into three parts, namely early, mid, and late lanthanides, based on their interactions with biological systems. In particular, the late lanthanides demonstrate distinct, but poorly understood biological activity. In the current study, we employed genome-wide functional screening to help understand biological effects of exposure to Yb(III) and Lu(III), which were selected as representatives of the late lanthanides. As a model organism, we used Saccharomyces cerevisiae, since it shares many biological functions with humans. Analysis of the functional screening results indicated toxicity of late lanthanides is consistent with disruption of vesicle-mediated transport, and further supported a role for calcium transport processes and mitophagy in mitigating toxicity. Unexpectedly, our analysis suggested that late lanthanides target proteins with SH3 domains, which may underlie the observed toxicity. This study provides fundamental insights into the unique biological chemistry of late lanthanides, which may help devise new avenues toward the development of decorporation strategies and bio-inspired separation processes.

Pallares, Roger M. (ORCID:0000000174238706)↗

N-Glycolylneuraminic Acid Binding of Avian and Equine H7 Influenza A Viruses

Influenza A viruses (IAV) initiate infection by binding to glycans with terminal sialic acids on the cell surface. Hosts of IAV variably express two major forms of sialic acid, N-acetylneuraminic acid (NeuAc) and N-glycolylneuraminic acid (NeuGc). NeuGc is produced in most mammals, including horses and pigs, but is absent in humans, ferrets, and birds. The only known naturally occurring IAV that exclusively bind NeuGc are extinct highly pathogenic equine H7N7 viruses. We determined the crystal structure of a representative equine H7 hemagglutinin (HA) in complex with NeuGc and observed high similarity in the receptor-binding domain with an avian H7 HA. To determine the molecular basis for NeuAc and NeuGc specificity, we performed systematic mutational analyses, based on the structural insights, on two distant avian H7 HAs and an H15 HA. We found that the A135E mutation is key for binding α2,3-linked NeuGc but does not abolish NeuAc binding. The additional mutations S128T, I130V, T189A, and K193R converted the specificity from NeuAc to NeuGc. We investigated the residues at positions 128, 130, 135, 189, and 193 in a phylogenetic analysis of avian and equine H7 HAs. This analysis revealed a clear distinction between equine and avian residues. The highest variability was observed at key position 135, of which only the equine glutamic acid led to NeuGc binding. These results demonstrate that genetically distinct H7 and H15 HAs can be switched from NeuAc to NeuGc binding and vice versa after the introduction of several mutations, providing insights into the adaptation of H7 viruses to NeuGc receptors.

59 BASIC BIOLOGICAL SCIENCES↗

A Methodology for Evaluating Operator Usage of Machine Learning Recommendations for Power Grid Contingency Analysis

This work presents the application of a methodology to measure domain expert trust and workload, elicit feedback, and understand the technological usability and impact when a machine learning assistant is introduced into contingency analysis for real-time power grid simulation. The goal of this framework is to rapidly collect and analyze a broad variety of human factors data in order to accelerate the development and evaluation loop for deploying machine learning applications. We describe our methodology and analysis, and we discuss insights gained from a pilot participant about the current usability state of an early technology readiness level (TRL) artificial neural network (ANN) recommender.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Learning procedures from interactive natural language instructions

Despite its ubiquity in human learning, very little work has been done in artificial intelligence on agents that learn from interactive natural language instructions. In this paper, the problem of learning procedures from interactive, situated instruction is examined in which the student is attempting to perform tasks within the instructional domain, and asks for instruction when it is needed. Presented is Instructo-Soar, a system that behaves and learns in response to interactive natural language instructions. Instructo-Soar learns completely new procedures from sequences of instruction, and also learns how to extend its knowledge of previously known procedures to new situations. These learning tasks require both inductive and analytic learning. Instructo-Soar exhibits a multiple execution learning process in which initial learning has a rote, episodic flavor, and later executions allow the initially learned knowledge to be generalized properly.

Huffman, Scott B.↗

Advancing satellite operations with intelligent graphical monitoring systems

For nearly twenty-five years, spacecraft missions have been operated in essentially the same manner: human operators monitor displays filled with alphanumeric text watching for limit violations or other indicators that signal a problem. The task is performed predominately by humans. Only in recent years have graphical user interfaces and expert systems been accepted within the control center environment to help reduce operator workloads. Unfortunately, the development of these systems is often time consuming and costly. At the NASA Goddard Space Flight Center (GSFC), a new domain specific expert system development tool called the Generic Spacecraft Analyst Assistant (GenSAA) has been developed. Through the use of a highly graphical user interface and point-and-click operation, GenSAA facilitates the rapid, 'programming-free' construction of intelligent graphical monitoring systems to serve as real-time, fault-isolation assistants for spacecraft analysts. Although specifically developed to support real-time satellite monitoring, GenSAA can support the development of intelligent graphical monitoring systems in a variety of space and commercial applications.

Hughes, Peter M.↗