Hypothesis Generation Strategies for Adaptive Problem Solving
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Hypothesis Genereation Adaptive problem solving re↗
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The permuted generator hypothesis for the origin of a genetic code
Protocells had no known means of ensuring that their randomly collected proteins would be duplicated. A possible, albeit inexact, mechanism for protein synthesis in a primitive t-RNA is presented, whereby an oligonucleotide (12 units) in a circular configuration is able to align a generator site with amino acid discriminator sites. In this way, unique anticodons could be specified for each site and replication could occur.
Folsome, C.↗
An expert system for monitoring dynamic aspects of RCS
An expert system (ARC) based on the MIMIC(2) framework is being developed for assistance in monitoring the Space Shuttle reaction control system (RCS) and in training RCS mission controllers. ARC has four components: a hypothesis generator, a model-constructor, a model-simulator and a matcher. The hypothesis generator examines current readings of sensors to generate a set of hypotheses. The model constructor generates models from these hypotheses. The simulator predicts future behaviors of the system. The matcher validates hypotheses by testing the predicted states against real data. The hypothesis generator postulates faults using model-based reasoning (MBR), learned rules from real data, and expert-defined rules. The simulator uses a qualitative QSIM model of the RCS which can handle both nominal modes as well as a variety of fault models. This allows the simulator to simulate the system even when one or more components have degraded. Finally, the matcher is responsible for comparing readings against predictions and calculating confidence in a particular hypothesis.
Kulkarni, Deepak↗
LSKnowledge: Nexus for Transformative Scientific Discoveries and Enhanced Information Retrieval in NASA Life Sciences Portal
We stand at the brink of an extraordinary transformation in the field of AI, driven by the convergence of generative AI and semantic technologies (e.g., knowledge graphs). This fusion holds immense potential and could redefine the future of scientific exploration, particularly in the realm of life sciences research. In this context, we shed light on the pivotal roles that Large Language Models (LLMs) and semantic technologies will play in advancing research, unearthing and comprehending life sciences information through innovative approaches, and empowering researchers to extract insights from NASA's extensive Life Sciences Data Archive. Within the NASA Life Sciences Portal (NLSP), the integration of LLMs and semantic technologies unlocks several advanced capabilities. First and foremost, it equips scientists with sophisticated tools to manage the ever-expanding wealth of scientific literature and data. Furthermore, it facilitates the creation of knowledge graphs that visually represent intricate relationships among biological entities, enabling comprehensive systems-level analysis. Additionally, the fusion of generative AI (including LLMs) and semantic technology can significantly benefit NASA's life sciences research by enhancing information retrieval and hypothesis generation. These tools enhance natural language understanding, facilitating knowledge discovery within NLSP. The overarching vision is to establish a cohesive knowledge ecosystem within NLSP, harnessing the power of LLMs and semantic technologies to synthesize and cross-reference data from diverse missions, disciplines, and research domains. This holistic approach ultimately deepens our understanding of how space environments impact life sciences data. To advance this initiative, we have launched LSKnowledge, aimed at enhancing the information retrieval capabilities of NLSP. In the short term, our primary goal is to develop a robust semantic search system. This system will empower HRP (Human Research Program) researchers to navigate NLSP data repositories more efficiently and precisely, catalyzing the process of hypothesis formation and scientific breakthroughs. To achieve this, we have employed pre-trained LLMs as part of a semantic search tool that can rank and highlight the most relevant records for user queries. To assess the tool's performance, we have curated a set of approximately 200 queries from subject matter experts (SMEs) and manually ranked the top records retrieved by both the current search system and the new semantic search, using SME judgments as the gold standard for relevancy. Herein, we present the results of our comparative analysis and illustrate how these findings have informed the fine-tuning of the system for enhanced performance. In the long term, our objectives include 1) retrieving publicly available information and integrating it with NLSP data to provide more precise answers to user queries, and 2) incorporating non-textual information from the NLSP database into our approach. In conclusion, the fusion of LLMs and semantic technologies within NLSP represents a pioneering stride towards reshaping the landscape of scientific discovery. This synergy not only equips researchers with powerful tools to navigate the burgeoning sea of information but also facilitates a deeper understanding of complex biological relationships, all while accelerating hypothesis generation and knowledge discovery. Through our initiative, LSKnowledge, we are committed to continually refining and expanding these capabilities, with the aim of not only enhancing information retrieval but also integrating diverse data sources to provide more precise insights. In the grand vision, NLSP strives to become the cornerstone of a comprehensive knowledge ecosystem, unraveling the enigmatic intricacies of life sciences phenomena in the context of space environments.
Life Sciences↗
The atmospheric electric global circuit
The hypothesis that world thunderstorm activity represents the generator for the atmospheric electric current flow in the earth atmosphere between ground and the ionosphere is based on a close correlation between the magnitude and the diurnal variation of the supply current (thunderstorm generator current) and the load current (fair weather air-earth current density integrated over the earth surface). The advantages of using lightning survey satellites to furnish a base for accepting or rejecting the thunderstorm generator hypothesis are discussed.
Kasemir, H. W.↗
Shape matching utilizing indexed hypotheses generation and testing
An indexing mechanism is developed as part of an overall scheme called SMITH (shape matching utilizing indexed hypothesis generation and testing) for two-dimensional model-based object recognition. The approach is based on a dynamic programming implementation of attributed string matching, is computationally efficient, and works effectively for both nonoccluded and occluded shapes. Another advantage of this technique is that models may be inserted or deleted with relatively little cost.
Mehrotra, Rajiv↗
Mitochondria Dysfunction Central in Driving Health Risks Associated with Spaceflight
Background: Determining the biological impact of spaceflight through novel approaches is essential to reduce the health risks to astronauts for long-term space missions. The current established health risks due to spaceflight are only reflecting known symptomatic and physiologic responses and do not reflect early onset of other potential diseases. There are many unknown variables which still need to be identified to fully understand the health impacts due to the environmental factors in space. Materials and Methods: One method to uncover potential novel biological mechanisms responsible for health risks in astronauts is by utilizing NASA’s GeneLab platform (genelab.nasa.gov). GeneLab is public repository that hosts multiple omics datasets generated from space biology experiments that include experiments flown in space, simulated cosmic radiation experiments, and simulated microgravity experiments. This presentation will provide an example of analysis and novel hypothesis generation that is being produced with GeneLab datasets. A comprehensive multi-omics approach was implemented correlating transcriptomics, proteomics, metabolomics, and methylation analysis. Results: We found that cells have stronger overall biological response than the tissues to spaceflight, with mitochondrial activity and innate immunity pathways being heavily impacted. NASA Twin Study results are consistent with a specific alteration in mitochondrial ATP production. Our results indicate that the space environment can directly induce mitochondrial damage, with mitochondrial dysfunctions being a cause for chronic inflammation and both being involved in the development of metabolic disorders that cause changes in lipid metabolism. We also found biological changes occurring during spaceflight with cell cycle, circadian rhythm and olfactory activity pathways can also influence and be influenced by alterations on mitochondrial activity
Afshin Beheshti↗
Ice Crystal Icing Physics Study using a NACA 0012 Airfoil at the National Research Council of Canada's Research Altitude Test Facility
This paper presents results from a study of the fundamental physics of ice-crystal ice accretion using a NACA 0012 airfoil at the National Research Council of Canada (NRC) Research Altitude Test Facility in August 2017. These tests were a continuation of work which began in 2010 as part of a joint collaboration between NASA and NRC. The research seeks to generate icing conditions representative of those that occur inside a jet engine when ingesting ice crystals. In this test, an airfoil was exposed to mixed-phase icing conditions and the resulting ice accretions were recorded and analyzed. This paper details the specific objectives, procedures, and measurements which included the aero-thermal and cloud measurements. The objectives were built upon observations and hypothesis generated from several previous test campaigns regarding mixed-phase ice-crystal icing. The specific objectives included (A) ice accretions under different wet-bulb temperatures, (B) investigations of steady-state ice shapes previously reported in the literature, (C) total water content variations in search of a threshold for accretion, and (D) probe characterization related to measuring melt fraction which is important to characterize the mixed-phase condition. The resulting ice accretions and conditions leading to such accretions are intended to help extend NASA’s predictive ice-accretion codes to include conditions occurring in engine ice-crystal icing.
Icing↗
On three dimensional object recognition and pose-determination: An abstraction based approach
A method of computing reliable Gaussian and mean curvature sign-map descriptors from the polynomial approximation of surfaces was demonstrated. Such descriptors which are invariant under perspective variation are suitable for hypothesis generation. A means for determining the pose of constructed geometric forms whose algebraic surface descriptors are nonlinear in terms of their orienting parameters was developed. This was done by means of linear functions which are capable of approximating nonlinear forms and determining their parameters. It was shown that biquadratic surfaces are suitable companion linear forms for cylindrical approximation and parameter estimation. The estimates provided the initial parametric approximations necessary for a nonlinear regression stage to fine tune the estimates by fitting the actual nonlinear form to the data. A hypothesis-based split-merge algorithm for extraction and pose determination of cylinders and planes which merge smoothly into other surfaces was developed. It was shown that all split-merge algorithms are hypothesis-based. A finite-state algorithm for the extraction of the boundaries of run-length regions was developed. The computation takes advantage of the run list topology and boundary direction constraints implicit in the run-length encoding.
Quek, Kok How Francis↗
Rocket engine diagnostics using neural networks
Two problems in applying neural networks to fault detection and identification are (1) the complexity of the sensor data to fault mapping and (2) the lack of sufficient training data. Here, methods are derived and tested in an architecture which addresses these two problems. First, the sensor data to fault mapping is decomposed into three simpler mappings which perform sensor data compression, hypothesis generation, and sensor fusion. Efficient training is performed for each mapping separately. Second, the neural network which performs sensor fusion is structured to detect new unknown faults for which training examples were not presented. These methods were tested on a task of fault detection and identification in the Space Shuttle Main Engine (SSME). Results indicate that the decomposed neural network architecture can be trained efficiently, can identify faults for which it has been trained, and can detect the occurrence of faults for which it has not been trained.
Whitehead, Bruce A.↗
Learning and diagnosing faults using neural networks
Neural networks have been employed for learning fault behavior from rocket engine simulator parameters and for diagnosing faults on the basis of the learned behavior. Two problems in applying neural networks to learning and diagnosing faults are (1) the complexity of the sensor data to fault mapping to be modeled by the neural network, which implies difficult and lengthy training procedures; and (2) the lack of sufficient training data to adequately represent the very large number of different types of faults which might occur. Methods are derived and tested in an architecture which addresses these two problems. First, the sensor data to fault mapping is decomposed into three simpler mappings which perform sensor data compression, hypothesis generation, and sensor fusion. Efficient training is performed for each mapping separately. Secondly, the neural network which performs sensor fusion is structured to detect new unknown faults for which training examples were not presented during training. These methods were tested on a task of fault diagnosis by employing rocket engine simulator data. Results indicate that the decomposed neural network architecture can be trained efficiently, can identify faults for which it has been trained, and can detect the occurrence of faults for which it has not been trained.
Whitehead, Bruce A.↗
The Intelligent Data Understanding Element of NASA's Intelligent Systems Program
Within the NASA Intelligent Systems Program, the Intelligent Data Understanding (IDU) element develops techniques for transforming data into scientific understanding. Automating such tools is critical for space science, space-based earth science, and planetary exploration with onboard scientific data analysis. Intelligent data understanding (IDU) is about extracting meaning from large, diverse science and engineering databases, via autonomous techniques that transform very large datasets into understanding. The earth science community in particular needs new tools for analyzing multi-formatted and geographically distributed datasets and for identifying cause-effect relationships in the complex data. Research within the IDU program element seeks to automate data analysis tasks so that humans can focus on creative hypothesis generation and knowledge synthesis. It may also enable NASA space missions in which autonomous agents must generate knowledge and take actions, and missions where limited bandwidth permits transmission of only the most interesting scientific observations, summaries, and conclusions. Twenty-seven research projects are-currently funded.
Coughlan, Joseph C.↗
Using OpenTarget to Generate Potential Countermeasures for Long-Term Space Exposure from Data Available on GeneLab
GeneLab as a general tool for the scientific community; Utilizing GeneLab datasets to generate hypothesis and determining potential biological targets against health risks due to long-term space missions; How can OpenTarget be used to discover novel drugs to test as countermeasures that can be utilized by astronauts.
GeneLab↗
ThermoBase: A Database of the Phylogeny and Physiology of Thermophilic and Hyperthermophilic Organisms
Thermophiles and hyperthermophiles are those organisms which grow at high temperature (> 40°C). The unusual properties of these organisms have received interest in multiple fields of biological research, and have found applications in biotechnology, especially in industrial processes. However, there are few listings of thermophilic and hyperthermophilic organisms and their relevant environmental and physiological data. Such repositories can be used to standardize definitions of thermophile and hyperthermophile limits and tolerances and would mitigate the need for extracting organism data from diverse literature sources across multiple, sometimes loosely related, research fields. Therefore, we have developed ThermoBase, a web-based and freely available database which currently houses comprehensive descriptions for 1238 thermophilic or hyperthermophilic organisms. ThermoBase reports taxonomic, metabolic, environmental, experimental, and physiological information in addition to literature resources. This includes parameters such as coupling ions for chemiosmosis, optimal pH and range, optimal temperature and range, optimal pressure, and optimal salinity. The database interface allows for search features and sorting of parameters. As such, it is the goal of ThermoBase to facilitate and expedite hypothesis generation, literature research, and understanding relating to thermophiles and hyperthermophiles within the scientific community in an accessible and centralized repository. ThermoBase is freely available online at the Astrobiology Habitable Environments Database (AHED; https://ahed.nasa.gov), at the Database Center for Life Science (TogoDB; http://togodb.org/db/thermobase), and in the S1 File.
Thermophiles↗
Hypothesis: Trans‐splicing Generates Evolutionary Novelty in the Photosynthetic Amoeba Paulinella
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Arwa Gabr↗
Perpendicular blade vortex interaction and its implications for helicopter noise prediction: Wave-number frequency spectra in a trailing vortex for BWI noise prediction
Perpendicular blade vortex interactions are a common occurrence in helicopter rotor flows. Under certain conditions they produce a substantial proportion of the acoustic noise. However, the mechanism of noise generation is not well understood. Specifically, turbulence associated with the trailing vortices shed from the blade tips appears insufficient to account for the noise generated. The hypothesis that the first perpendicular interaction experienced by a trailing vortex alters its turbulence structure in such a way as to increase the acoustic noise generated by subsequent interactions is examined. To investigate this hypothesis a two-part investigation was carried out. In the first part, experiments were performed to examine the behavior of a streamwise vortex as it passed over and downstream of a spanwise blade in incompressible flow. Blade vortex separations between +/- one eighth chord were studied for at a chord Reynolds number of 200,000. Three-component velocity and turbulence measurements were made in the flow from 4 chord lengths upstream to 15 chordlengths downstream of the blade using miniature 4-sensor hot wire probes. These measurements show that the interaction of the vortex with the blade and its wake causes the vortex core to loose circulation and diffuse much more rapidly than it otherwise would. Core radius increases and peak tangential velocity decreases with distance downstream of the blade. True turbulence levels within the core are much larger downstream than upstream of the blade. The net result is a much larger and more intense region of turbulent flow than that presented by the original vortex and thus, by implication, a greater potential for generating acoustic noise. In the second part, the turbulence measurements described above were used to derive the necessary inputs to a Blade Wake Interaction (BWI) noise prediction scheme. This resulted in significantly improved agreement between measurements and calculations of the BWI noise spectrum especially for the spectral peak at low frequencies, which previously was poorly predicted.
Devenport, William J.↗
Latitude-Dependent Effects in the Stellar Wind of Eta Carinae
The Homunculus reflection nebula around eta Carinae provides the rare opportunity to observe the spectrum of a star from more than one direction. In the case of eta Car, the nebula's geometry is known well enough to infer how wind profiles vary with latitude. We present STIS spectra of several positions in the Homunculus, showing directly that eta Car has an aspherical and axisymmetric stellar wind. P Cygni absorption in Balmer lines depends on latitude, with relatively high velocities and strong absorption near the polar axis. Stronger absorption at high latitudes is surprising, and it suggests higher mass flux toward the poles, perhaps resulting from equatorial gravity darkening on a rotating star. Reflected profiles of He I lines are more puzzling, and offer clues to eta Car's wind geometry and ionization structure. During eta Car's high-excitation state in March 2000, the wind had a fast, dense polar wind, with higher ionization at low latitudes. Older STIS data obtained since 1998 reveal that this global stellar-wind geometry changes during eta Car's 5.5 year cycle, and may suggest that this star s spectroscopic events are shell ejections. Whether or not a companion star triggers these outbursts remains ambiguous. The most dramatic changes in the wind occur at low latitudes, while the dense polar wind remains relatively undisturbed during an event. The apparent stability of the polar wind also supports the inferred bipolar geometry. The wind geometry and its variability have critical implications for understanding the 5.5 year cycle and long-term variability, but do not provide a clear alternative to the binary hypothesis for generating eta Car s X-rays.
Smith, Nathan↗
Water in the Cratonic Mantle Lithosphere
The fact that Archean and Proterozoic cratons are underlain by the thickest (>200 km) lithosphere on Earth has always puzzled scientists because the dynamic convection of the surrounding asthenosphere would be expected to delaminate and erode these mantle lithospheric "keels" over time. Although density and temperature of the cratonic lithosphere certainly play a role in its strength and longevity, the role of water has only been recently addressed with data on actual mantle samples. Water in mantle lithologies (primarily peridotites and pyroxenites) is mainly stored in nominally anhydrous minerals (olivine, pyroxene, garnet) where it is incorporated as hydrogen bonded to structural oxygen in lattice defects. The property of hydrolytic weakening of olivine [4] has generated the hypothesis that olivine, the main mineral of the upper mantle, may be dehydrated in cratonic mantle lithospheres, contributing to its strength. This presentation will review the distribution of water concentrations in four cratonic lithospheres. The distribution of water contents in olivine from peridotite xenoliths found in kimberlites is different in each craton (Figure 1). The range of water contents of olivine, pyroxene and garnet at each xenolith location appears linked to local metasomatic events, some of which occurred later then the Archean and Proterozoic when these peridotites initially formed via melting. Although the low olivine water contents (<10 ppm wt H2O) at > 6 GPa at the base of the Kaapvaal cratonic lithosphere may contribute to its strength, and prevent its delamination, the wide range of those from Siberian xenoliths is not compatible with providing a high enough viscosity contrast with the asthenophere. The water content in olivine inclusions from Siberian diamonds, on the other hand, have systematically low water contents (<20 ppm wt H2O). The xenoliths may represent a biased sample of the cratonic lithosphere with an over-abundance of metasomatized peridotites with high water contents. The olivine inclusions, however, may have been protected from metasomatism by their host diamond and record the overall low olivine water content of the cratonic lithosphere. Water may thus still play a role in cratonic keel longevity.
Peslier, A. H.↗