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PLANETARY DEFENSE: FINDINGS AND RECOMMENDATIONS FROM THE NATIONAL ACADEMIES PLANETARY SCIENCE AND ASTROBIOLOGY DECADAL SURVEY 2023 - 2032

The National Academies of Sciences, Engineering, and Medicine was chartered by the NASA Science Mission Directorate (SMD), with support from the National Science Foundation, to conduct a new decadal survey to develop a comprehensive science and mission strategy for planetary science (1). The survey was tasked to determine the current state of knowledge and to identify the most important scientific questions to be addressed in astrobiology and planetary science during the upcoming decade of 2023 - 2032. For the first time, the decadal survey also included and addressed the topic of planetary defense, now recognized as a key element of NASA’s planetary science activities under the direction of NASA’s SMD Planetary Defense Coordination Office. The topic of planetary defense was included in the decadal survey as a dedicated chapter, divided into five sections based on the framework from the U.S. National NEO Preparedness Strategy and Action Plan (2). These sections discussed: NEO Detection, Tracking, and Characterization NEO Modelling, Prediction, and Integration NEO Deflection and Disruption Missions International Cooperation on NEO Preparation NEO Impact Emergency Procedures and Action Protocols Content of these sections included identifying the activities, ground- and space-based assets, facilities, resources, technologies, and missions that should be considered to enable NEO preparedness over the next decade. Supporting inputs to this chapter involved contributions from submitted white papers authored by many members of the NEO science and planetary defense communities. In addition, a planetary defense rapid mission architecture study commissioned by the decadal survey small bodies panel and led by the Jet Propulsion Laboratory examined several different types of in-situ characterization and mitigation demonstration missions. All of this input contributed to the formulation of 42 findings and 11 recommendations that suggest a path forward for increasing our understanding of the NEO population and their associated physical characteristics, modelling the impact probabilities and hazard potential of these objects, and implementing plans to develop and test NEO impact mitigation capabilities. Including planetary defense in the decadal survey has helped sharpen the focus on this international issue and provided key inputs for stakeholders and decision makers to consider when developing future planetary defense-related activities. Such information is vital for developing a long-term integrated planetary defense capability able to protect humanity in the decades to come.

NEO Detection and Characterization↗

Overview of the Turbine Based Combined Cycle Discipline

The NASA Fundamental Aeronautics Hypersonics project is focused on technologies for combined cycle, airbreathing propulsions systems to enable reusable launch systems for access to space. Turbine Based Combined Cycle (TBCC) propulsion systems offer specific impulse (Isp) improvements over rocket-based propulsion systems in the subsonic takeoff and return mission segments and offer improved safety. The potential to realize more aircraft-like operations with expanded launch site capability and reduced system maintenance are additional benefits. The most critical TBCC enabling technologies as identified in the National Aeronautics Institute (NAI) study were: 1) mode transition from the low speed propulsion system to the high speed propulsion system, 2) high Mach turbine engine development, 3) transonic aero-propulsion performance, 4) low-Mach-number dual-mode scramjet operation, 5) innovative 3-D flowpath concepts and 6) innovative turbine based combined cycle integration. To address several of these key TBCC challenges, NASA s Hypersonics project (TBCC Discipline) initiated an experimental mode transition task that includes an analytic research endeavor to assess the state-of-the-art of propulsion system performance and design codes. This initiative includes inlet fluid and turbine performance codes and engineering-level algorithms. This effort has been focused on the Combined Cycle Engine Large-Scale Inlet Mode Transition Experiment (CCE LIMX) which is a fully integrated TBCC propulsion system with flow path sizing consistent with previous NASA and DoD proposed Hypersonic experimental flight test plans. This experiment is being tested in the NASA-GRC 10 x 10 Supersonic Wind Tunnel (SWT) Facility. The goal of this activity is to address key hypersonic combined-cycle-engine issues: (1) dual integrated inlet operability and performance issues unstart constraints, distortion constraints, bleed requirements, controls, and operability margins, (2) mode-transition constraints imposed by the turbine and the ramjet/scramjet flow paths (imposed variable geometry requirements), (3) turbine engine transients (and associated time scales) during transition, (4) high-altitude turbine engine re-light, and (5) the operating constraints of a Mach 3-7 combustor (specific to the TBCC). The model will be tested in several test phases to develop a unique TBCC database to assess and validate design and analysis tools and address operability, integration, and interaction issues for this class of advanced propulsion systems. The test article and all support equipment is complete and available at the facility. The test article installation and facility build-up in preparation for the inlet performance and operability characterization is near completion and testing is planned to commence in FY11.

Thomas, Scott R.↗

The Future of Arctic Fires: Leveraging Ongoing Activities, New Efforts, and International Cooperation

Fires in the Arctic region are gaining more attention and driving increased concern from the public, the scientific community, and policymakers. An increasing number of scientific projects, collaboration efforts, media coverage, and policy assessments have been and are being implemented and published regarding this emerging and important wildland fire phenomenon. In short, this increased activity comes from the recognition of increasing fire risk and activity close to, within, and impacting the Arctic. There is a need to integrate these numerous and expanding local, national, and international efforts to avoid redundant and overlapping efforts and to focus resources more efficiently. As a response, this report suggests short and long-term goals to respond to the growing fire risk and fire danger in the Arctic. All efforts call for more integrated international collaboration and greater recognition of the importance for Arctic communities to be collaborators and leaders.

Future↗

Logistics planning for phased programs.

It is pointed out that the proper and early integration of logistics planning into the phased program planning process will drastically reduce these logistics costs. Phased project planning is a phased approach to the planning, approval, and conduct of major research and development activity. A progressive build-up of knowledge of all aspects of the program is provided. Elements of logistics are discussed together with aspects of integrated logistics support, logistics program planning, and logistics activities for phased programs. Continuing logistics support can only be assured if there is a comprehensive sequential listing of all logistics activities tied to the program schedule and a real-time inventory of assets.

Cook, W. H.↗

Near-Real-Time Forecast of Satellite-Based Soil Moisture Using Long Short-Term Memory with an Adaptive Data Integration Kernel

Nowcasts, or near-real-time (NRT) forecasts, of soil moisture based on the Soil Moisture Active and Passive (SMAP) mission could provide substantial value for a range of applications including hazards monitoring and agricultural planning. To provide such a NRT forecast with high fidelity, we enhanced a time series deep learning architecture, long short-term memory (LSTM), with a novel data integration (DI) kernel to assimilate the most recent SMAP observations as soon as they become available. The kernel is adaptive in that it can accommodate irregular observational schedules. Testing over the CONUS, this NRT forecast product showcases predictions with unprecedented accuracy when evaluated against subsequent SMAP retrievals. It showed smaller error than NRT forecasts reported in the literature, especially at longer forecast latency. The comparative advantage was due to LSTM’s structural improvements, as well as its ability to utilize more input variables and more training data. The DI-LSTM was compared to the original LSTM model that runs without data integration, referred to as the projection model here. We found that the DI procedure removed the autocorrelated effects of forcing errors and errors due to processes not represented in the inputs, for example, irrigation and floodplain/lake inundation, as well as mismatches due to unseen forcing conditions. The effects of this purely data-driven DI kernel are discussed for the first time in the geosciences. Furthermore, this work presents an upper-bound estimate for the random component of the SMAP retrieval error.

54 ENVIRONMENTAL SCIENCES↗

Tailoring Binder Molecular Weight to Enhance Slurry-Cast NMC Cathodes for Sulfide Solid-State Batteries

We demonstrate for the first time the critical influence of binder molecular weight on the performance of slurry-cast lithium nickel manganese cobalt oxide (NMC) cathodes in sulfide-based all-solid-state batteries (SSBs). SSBs are increasingly recognized as a safer and potentially more efficient alternative to traditional Li-ion batteries, owing to the superior ionic conductivities and inherent safety features of sulfide solid electrolytes. However, the integration of high-voltage NMC cathodes with sheet-type sulfide solid electrolytes presents significant fabrication challenges. Our findings reveal that higher molecular weight binders not only enhance the discharge capacity and cycle life of these cathodes but also ensure robust adhesion and structural integrity. By optimizing binder molecular weights, we effectively shield the active materials from degradation and mechanical stress, significantly boosting the functionality and longevity of SSBs. These results underscore the paramount importance of binder properties in advancing the practical application of high-performance all-solid-state batteries.

25 ENERGY STORAGE↗

Functional Relevance of CASP16 Nucleic Acid Predictions as Evaluated by Structure Providers

ABSTRACT Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, experimental model building, and many other applications. Such algorithms to predict essential functional and structural features remain out of reach for biomolecular complexes containing nucleic acids. Here, we report a quantitative and qualitative evaluation of nucleic acid structures for the CASP16 blind prediction challenge by 12 of the experimental groups who provided nucleic acid targets. Blind predictions accurately model secondary structure and some aspects of tertiary structure, including reasonable global folds for some complex RNAs; however, predictions often lack accuracy in the regions of highest functional importance. All models have inaccuracies in non‐canonical regions where, for example, the nucleic‐acid backbone bends, deviating from an A‐form helix geometry, or a base forms a non‐standard hydrogen bond (not a Watson‐Crick base pair). These bends and non‐canonical interactions are integral to forming functionally important regions such as RNA enzymatic active sites. Additionally, the modeling of conserved and functional interfaces between nucleic acids and ligands, proteins, or other nucleic acids remains poor. For some targets, the experimental structures may not represent the only structure the biomolecular complex occupies in solution or in its functional life cycle, posing a future challenge for the community.

Biochemistry & Molecular Biology↗

PANNA: Properties from Artificial Neural Network Architectures

We report prediction of material properties from first principles is often a computationally expensive task. Recently, artificial neural networks and other machine learning approaches have been successfully employed to obtain accurate models at a low computational cost by leveraging existing example data. Here, we present a software package “Properties from Artificial Neural Network Architectures” (PANNA) that provides a comprehensive toolkit for creating neural network models for atomistic systems following the Behler–Parrinello topology. Besides the core routines for neural network training, it includes data parser, descriptor builder for Behler–Parrinello class of symmetry functions and force-field generator suitable for integration within molecular dynamics packages. PANNA offers a variety of activation and cost functions, regularization methods, as well as the possibility of using fully-connected networks with custom size for each atomic species. PANNA benefits from the optimization and hardware-flexibility of the underlying TensorFlow engine which allows it to be used on multiple CPU/GPU/TPU systems, making it possible to develop and optimize neural network models based on large datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The European wood pellets for heating market - Price developments, trade and market efficiency

Competitive international markets imply adjustments towards competitive spatial equilibrium in which excess from one market is transferred to another and prices are equilibrated except for remaining differences that can be assigned to transfer costs. The European market for wood pellets used in small-scale heating systems has been expanding significantly over the past decade. Small scale pellet heating is arguably a mature technology, but whether the market is mature is another question. In this paper we analyse recent data on trade flows and price developments between Italy, Austria, Germany and France to understand the developments of wood pellet market efficiency and to draw conclusions about market function. The objective of this study is to establish a framework to test the European residential wood pellet market for competitive spatial equilibrium using modern trade theory. We find mainly inefficiently integrated markets with remaining positive marginal profits and detectable arbitrageurs’ activity. Based on a thorough discussion of these findings and the underlying data we outline possible methodology advancements and list policy recommendations to secure access and affordability of this renewable heating commodity in the long run.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Projected network performance for multiple isotopes using next-generation xenon monitoring systems

Since about 2000 (Bowyer et al., 1998), radioxenon monitoring systems have been under development and testing for the verification of the Comprehensive Nuclear Test-Ban Treaty (CTBT). Operation of the systems since then has resulted in development of a next-generation of systems that are nearly ready for operational deployment. By 2010, the need to screen out civilian sources was well known (Auer et al., 2010; Saey, 2009), and isotopic ratio approaches were soon considered (Kalinowski et al., 2014) to identify specific sources. New generation systems are expected to improve the ability to verify the absence of nuclear tests by using isotopic ratios when multiple isotopes are detected. In this work, thousands of releases were simulated to compute the global detection probability of 131m Xe, 133m Xe, 133 Xe, and 135 Xe at 39 noble gas systems in the International Monitoring System (IMS) for both current and next-generation systems. Three release scenarios are defined at 1 h, 1 d, and 10 d past a 1 kt TNT equivalent 235U explosion event. Multiple cases using from one part in a million to the complete release of the xenon isotopic activity are evaluated for each scenario. Coverage maps and global integrals comparing current and next-generation monitoring systems are presented showing that next-generation noble gas systems will create measurable improvements in the IMS. The global detection probability for 133 Xe is shown to be strong in all scenarios, but only modestly improved by next-generation equipment. However, the detection probability for 131m Xe and 133m Xe increased to about 50% in different scenarios, providing a second detectable isotope for many events. As anticipated from shorter sampling intervals, the expected number of detecting samples roughly doubled and the expected number of detecting stations rose by approximately 50% for all release scenarios. Thus, it might be anticipated that future events would consist of multiple 133 Xe detections and one or more second isotope detections. In conclusion, signals of this nature should increase detection confidence, tighten release location estimates, improve rejection of civilian signals, and lessen the impacts from individual systems being offline for maintenance or repair reasons.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

INTS6 promotes colorectal cancer progression by activating of AKT and ERK signaling

Highlights: • INTS6 is upregulated in colorectal cancer and correlated with poor prognosis. • INTS6 promotes the growth of colorectal cancer cells in vitro and in vivo. • INTS6 affects the cell cycle distribution of colorectal cancer cells. • INTS6 activates the AKT and ERK signaling in colorectal cancer. INTS6 (integrator complex subunit 6) has been reported as a tumor suppressor in many cancers. However, the expression and biological function of INTS6 in colorectal cancer (CRC) has not been investigated yet. In this study, we found that INTS6 expression was significantly increased in CRC tissues when compared with normal tissues and was associated with poor prognosis. Downregulation of INTS6 induced G1/S-phase cell cycle arrest, and markedly suppressed the growth of CRC cells and the derived tumors, while overexpression of INTS6 showed opposite effect. Mechanism study revealed that INTS6 increased the levels of phosphorylated AKT (p-AKT) and ERK (p-ERK), and the growth-promoting effect of INTS6 was inhibited by AKT and ERK inhibitors. Besides, INTS6 also affected the expression of two targets of PI3K/AKT and MAPK signaling, c-Myc and CDK2, which contributed to cell cycle alteration. Altogether, the present study has revealed the oncogenic role of INTS6 in CRC, providing a novel therapeutic target for this malignant cancer.

60 APPLIED LIFE SCIENCES↗

Industrial Adoption of Carbon Nanotubes

Over the past 30 years, carbon nanotubes have emerged as one of the most exciting classes of nanomaterials due to their unique physicochemical properties. While challenges in nanotube synthesis and processing initially hindered their adoption, many of these barriers have since been addressed by research and manufacturing advances, resulting in substantial industrial application of nanotubes across multiple sectors. However, much of this progress is not known in the academic community. This perspective discusses the current landscape and outlook of industrial integration of carbon nanotubes and key factors mediating widespread integration across all major material-related areas of human activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrochemically Initiated Depolymerization of Poly(Methyl Methacrylate)

Efficient depolymerization of polymers with all-carbon backbones under mild conditions would be valuable in chemically recycling commodity plastics. Poly(methyl methacrylate) (PMMA) is a commodity thermoplastic that is currently depolymerized under temperatures in excess of 400 °C. Herein, we lower the temperatures needed to achieve depolymerization of PMMA by performing radical generation and depropagation with orthogonal stimuli. This first demonstration of electrochemically initiated PMMA depolymerization relies on reduction of phthalimide esters that, upon subsequent decarboxylation, generate polymer-centered radicals. These radicals then spontaneously unzip the polymer back to its monomeric constituents at temperatures as low as 105 °C. We studied the mechanism and efficiency of this transformation as a function of phthalimide ester placement, incorporation density, and polymer molecular weight. We found that chain-end activation is effective for modest molecular weights but suffers diminished efficiency at higher degrees of polymerization. In contrast, pendent-group activation is more effective for depolymerizing higher molecular weight species. Integrating higher molar amounts of phthalimide ester pendants leads to more effective depolymerization, with >95% depolymerization in copolymers with 5 mol% phthalimide ester incorporation. We leveraged this understanding to create a custom electro-distillation apparatus that allowed us to simultaneously electrochemically depolymerize PMMA and directly distill methyl methacrylate in >22% yield, which could ultimately be repolymerized. These findings establish electrochemistry as a versatile and orthogonal stimulus for vinyl polymer depolymerization and provide a foundation for closed-loop electrochemical recycling of widely used plastics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Illumination of Thunderclouds by Lightning: 4. Volumetric Thunderstorm Imagery

Optical instruments such as the Geostationary Lightning Mapper (GLM) detect lightning based on transient changes in cloud illumination. The horizontal location of lightning is determined from the coordinates of the pixels on the imaging array illuminated during the flash. However, the vertical position of the lightning pulses (approximated by GLM “groups”) below the cloud top cannot be routinely measured from a single space-based instrument. In our prior work, we have developed a machine learning algorithm that can infer optical source altitude for a given pulse based on how the optical energy is distributed across the group footprint and the local Advanced Baseline Imager Cloud-Top Height (CTH). In this fourth part of our thundercloud illumination study, we leverage these source altitudes to generate volumetric GLM imagery of a Colombia thunderstorm. We find that 3D versions of the current GLM meteorological imagery products (that describe thunderstorm kinematics) and thundercloud imagery products (that depict how the flashes appear from space) provide additional insights into lightning activity in the thunderstorm that are lost in the vertical integration used to generate the current 2D GLM gridded products. This new volumetric imaging capability provides a more comprehensive picture of where lightning occurs in the storm, how its physical characteristics vary across three-dimensional space, and how its optical emissions interact with surrounding the cloud medium.

54 ENVIRONMENTAL SCIENCES↗

NTRC regulates CP12 to activate Calvin–Benson cycle during cold acclimation

NADPH-dependent thioredoxin reductase C (NTRC) is a chloroplast redox regulator in algae and plants. Here, we used site-specific mutation analyses of the thioredoxin domain active site of NTRC in the green alga Chlamydomonas reinhardtii to show that NTRC mediates cold tolerance in a redox-dependent manner. By means of coimmunoprecipitation and mass spectrometry, a redox- and cold-dependent binding of the Calvin–Benson Cycle Protein 12 (CP12) to NTRC was identified. NTRC was subsequently demonstrated to directly reduce CP12 of C. reinhardtii as well as that of the vascular plant Arabidopsis thaliana in vitro. As a scaffold protein, CP12 joins the Calvin–Benson cycle enzymes phosphoribulokinase (PRK) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) to form an autoinhibitory supracomplex. Using size-exclusion chromatography, NTRC from both organisms was shown to control the integrity of this complex in vitro and thereby PRK and GAPDH activities in the cold. Thus, NTRC apparently reduces CP12, hence triggering the dissociation of the PRK/CP12/GAPDH complex in the cold. Like the ntrc::aphVIII mutant, CRISPR-based cp12::emx1 mutants also exhibited a redox-dependent cold phenotype. In addition, CP12 deletion resulted in robust decreases in both PRK and GAPDH protein levels implying a protein protection effect of CP12. Both CP12 functions are critical for preparing a repertoire of enzymes for rapid activation in response to environmental changes. This provides a crucial mechanism for cold acclimation.

54 ENVIRONMENTAL SCIENCES↗

Philympics 2021: Prophage Predictions Perplex Programs

Most bacterial genomes contain integrated bacteriophages—prophages—in various states of decay. Many are active and able to excise from the genome and replicate, while others are cryptic prophages, remnants of their former selves. Over the last two decades, many computational tools have been developed to identify the prophage components of bacterial genomes, and it is a particularly active area for the application of machine learning approaches. However, progress is hindered and comparisons thwarted because there are no manually curated bacterial genomes that can be used to test new prophage prediction algorithms. Here, we present a library of gold-standard bacterial genome annotations that include manually curated prophage annotations, and a computational framework to compare the predictions from different algorithms. We use this suite to compare all extant stand-alone prophage prediction algorithms to identify their strengths and weaknesses. We provide a FAIR dataset for prophage identification, and demonstrate the accuracy, precision, recall, and f 1 score from the analysis of seven different algorithms for the prediction of prophages. We discuss caveats and concerns in this analysis and how those concerns may be mitigated.

Roach, Michael J.↗

Developments and Challenges in the Design of the ITER DRGA

We report the ITER Diagnostic Residual Gas Analyzer (DRGA) will measure the distribution of gas species, i.e., deuterium (D), tritium (T), and impurities, in the divertor exhaust stream and in the plasma periphery, with time resolution relevant to fusion plasma–wall particle dynamics. The uniqueness of the DRGA, over previous implementations of plasma dynamics residual gas analysis, is an integrated approach, combining mass and low-temperature plasma-activated optical spectroscopy, in a differentially pumped analysis station. A further unique feature of the ITER divertor-specific DRGA is an ~8-m separation of the analysis station from the sampled pumping duct, while still maintaining a ~1-s response time for hydrogen isotopic concentrations. ITER DRGA final design activities are strongly benefiting from testing of prototypical DRGA components and methods on present fusion devices, most currently on JET and W7-X. DRGA systems are implemented on both these devices and include sensors (and pumping methods) that are directly relevant to the ITER DRGA design. The recent JET-DTE2 campaign has provided the first experience on operating the combined ITER DRGA sensors with D-T plasmas. While enhancing system design for ITER, this experience on operating devices has also revealed additional engineering challenges, which further guide the continuing final design project. Meanwhile, the recent determination that the ITER DRGA, with slight optimization, will resolve the helium isotopes well enough to support an ITER pre-DT, He-3-based heating scheme, has greatly increased ITER Research Program interest in the DRGA and its implementation well ahead of the DT phase.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility

In vitro antibiotic susceptibility testing often fails to accurately predict in vivo drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investigate the interrelationship between antibiotic susceptibility and medium composition in Escherichia coli K-12 MG1655 as contextualized through machine learning of transcriptomics data. Application of independent component analysis, a signal separation algorithm, shows that complex phenotypic changes induced by environmental conditions or antibiotic treatment are directly traced to the action of a few key transcriptional regulators, including RpoS, Fur, and Fnr. Integrating machine learning results with biochemical knowledge of transcription factor activation reveals medium-dependent shifts in respiration and iron availability that drive differential antibiotic susceptibility. By extension, the data generation and data analytics workflow used here can interrogate the regulatory state of a pathogen under any measured condition and can be applied to any strain or organism for which sufficient transcriptomics data are available.

59 BASIC BIOLOGICAL SCIENCES↗