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At least 1,099 records · Page 61

Chandrasekhar-type algorithms for fast recursive estimation in linear systems with constant parameters

In this recursive method proposed, the gain matrix for the Kalman filter and the convariance of the state vector are computed not via the Riccati equation, but from certain other equations. These differential equations are of Chandrasekhar-type. The 'invariant imbedding' idea resulted in the reduction of the basic boundary value problem of transport theory to an equivalent initial value system, a significant computational advance. Initial value experience showed that there is some computational savings in the method and the loss of positive definiteness of the covariance matrix is less vulnerable.

Choudhury, A. K.↗

Pioneer 9 and Pioneer 10 observations of the solar wind associated with the August 1972 events

Observations are presented of the changes in the solar wind proton parameters at 0.8 and 2.2 AU as a result of the solar flares in August 1972. These observations were obtained by the NASA Ames Research Center solar wind plasma analyzer experiments on Pioneer 9 and Pioneer 10. High time resolution measurements are presented of the solar wind proton speed associated with the arrival of the interplanetary shocks at Pioneer 9 and Pioneer 10. For these events, differential ion energy per unit charge spectra are shown which indicate the changes in the solar wind ion distribution function associated with the arrival of each of the interplanetary shocks. Four fast shocks are identified at Pioneer 9, and it is found that previously the time of arrival of the first interplanetary shock at Pioneer 9 was not correctly identified. Two fast shocks and one reverse shock are identified at Pioneer 10.

Intriligator, D. S.↗

Stabilization of computational procedures for constrained dynamical systems

A new stabilization method of treating constraints in multibody dynamical systems is presented. By tailoring a penalty form of the constraint equations, the method achieves stabilization without artificial damping and yields a companion matrix differential equation for the constraint forces; hence, the constraint forces are obtained by integrating the companion differential equation for the constraint forces in time. A principal feature of the method is that the errors committed in each constraint condition decay with its corresponding characteristic time scale associated with its constraint force. Numerical experiments indicate that the method yields a marked improvement over existing techniques.

Park, K. C.↗

In vitro differentiation of quail neural crest cells into sensory-like neuroblasts

Data are presented that demonstrate the ability of quail neural-crest embrionic cells grown as primary culture to differentiate in vitro into sensorylike neuroblasts. After 7-14 days of growth as primary culture, many of the putative sensory neuroblasts displayed substance P (SP)-like immunoreactivity and some exhibited histochemical carbonic anhydrase activity. Double staining experiments showed that the SP-like immunoreactive neuroblasts did not contain detectable levels of tyrosine hydroxylase or dopamine-beta-hydroxylase. The neuronal nature of the cultured sensorylike neuroblasts was further documented by double labeling for antibodies against the 68 kDa neurofilament polypeptide and substance P.

Sieber-Blum, Maya↗

Automatic calibration of inductive voltage dividers for the NASA Zeno experiment

Two inductive voltage dividers (IVDs) used for temperature measurements in NASA's Zeno experiment were tested. In order to obtain the required resolution of 10 parts per billion, a 30-bit binary inductive voltage divider developed at the National Institute of Standards and Technology was used to measure the differential linearity of the Zeno IVDs. Automatic measurements were performed on the dividers in the Zeno engineering model at frequencies of 266 and 351 Hz over a ratio range of 0.55-0.56. The measured differential linearity limits the temperature resolution to 5/micro-K.

Avramov, Svetlana↗

NASAs VESGEN: Systems Analysis of Vascular Phenotypes from Stress and Other Signaling Pathways Using GeneLab.

One fundamental requirement shared by humans with all higher terrestrial life forms, including insect wings, higher land plants and other vertebrates, is a complex, fractally branching vascular system. NASA's VESsel GENeration Analysis (VESGEN) software maps and quantifies vascular trees, networks, and tree-network composites according to weighted physiological rules such as vessel connectivity, tapering and bifurcational branching. According to fluid dynamics, successful vascular transport requires a complex distributed system of highly regulated laminar flow. Microvascular branching rules within vertebrates, dicot leaves and the other organisms therefore display many similarities. One unifying perspective is that vascular patterning offers a useful readout that necessarily integrates complex molecular signaling pathways. VESGEN has elucidated changes in vascular pattern resulting from inflammatory, stress response, developmental and other signaling within numerous tissues and major model organisms studied for Space Biology. For a new VESGEN systems approach, we analyzed differential gene expression in leaves of Arabidopsis thaliana reported by GeneLab (GLDS-7) for spaceflight. Vascular-related changes in leaf gene expression were identified that can potentially be phenocopied by mutants in ground-based experiments. To link transcriptional, protein and other molecular change with phenotype, alterations in the Euclidean and dynamic dimensions (x,y,t) of vascular patterns for Arabidopsis leaves and other model species are being co-localized with signaling patterns of single molecular expression analyzed as information dimensions (i,j,k,...). Previously, Drosophila microarray data returned from space suggested significant changes in genes related to wing venation development that include EGF, Notch, Hedghog, Wingless and Dpp signaling. Phenotypes of increasingly abnormal ectopic wing venation in the (non-spaceflight) Drosophila wing generated by overexpression of a Notch antagonist were analyzed by VESGEN. Other VESGEN research applications include the mouse retina, GI and coronary vessels, avian placental analogs and translational studies in the astronaut retina related to health challenges for long-duration missions.

Venation↗

NASA GeneLab: Open Science for Life in Space

NASA’s GeneLab helps scientists understand how the fundamental building blocks of life – DNA, RNA, proteins, and metabolites – change from exposure to the space environment including microgravity and cosmic radiation exposure. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data (collectively known as omics data) alongside essential metadata describing each spaceflight and space-relevant experiment. The open-access GeneLab repository currently consists of over 300 omics datasets generated by biological experiments, involving various model organisms, that are relevant to spaceflight. In order to maximize the intelligibility of these data, particularly for users with limited bioinformatics knowledge, GeneLab has started processing and analyzing these datasets to generate differential gene expression data and identify biological and physiological pathways that are dysregulated as a result of spaceflight. To aide GeneLab’s efforts to harmonize and democratize space-relevant omics data, over 130 scientists have joined one of four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG) and together helped develop and adopted standard data analysis workflows for all data types available in GeneLab. Currently, the GeneLab Data System includes a data repository with federated search capability, an online controlled-access toolshed powered by "Galaxy" for users to process data with vetted standard workflows, a workspace for data sharing, a data submission portal, and the ability to browse and visualize transcriptomics processed data. The user interface was designed to be accessible to a broad variety of users, including high school and college students who can use it to learn about omics data analysis and space biology. The visualization portal enhances GeneLab’s ability to democratize omics data by removing the need for bioinformatics expertise to interpret transcriptomics data hosted on GeneLab. This presentation will provide an over-view of NASA’s GeneLab including how to navigate the GeneLab Data System and will conclude by providing resources for opportunities to work with GeneLab and NASA at large.

Amanda M Saravia-Butler↗

Advances in Entry Modeling for Impact Risk Assessment

A summary of recent advancements in the detailed modeling of asteroid atmospheric entry processes made through NASA’s Asteroid Threat Assessment Project (ATAP) is presented. Understanding, and accurately modeling these processes and their associated uncertainties is critical to predicting all downstream impact effects, such as blast wave and thermal damage footprints. Furthermore, there is (perhaps thankfully) a dearth of empirical data for large impactors of the kind that would pose a threat to human populations, on which to anchor and/or validate models used in risk assessments. Therefore, we must rely heavily on detailed theoretical and numerical modeling to develop robust assessments for decision makers. To that end, ATAP has made some significant progress in advancing the capabilities in this area. Two areas in particular are highlighted in the present work: meteoroid ablation mechanisms, and bolide luminosity. The first research area – meteoroid ablation mechanisms – has focused on performing novel high-enthalpy wind tunnel experiments on meteorites and meteorite analogs, and utilizing the resulting data to develop high-fidelity models for impactor mass loss at scale. These efforts have resulted in several insights. Of note, these data suggest a differential vaporization process where volatiles are liberated preferentially when the asteroidal material is subject to high heat, while refractory components remain in the molten layer on the surface. A numerical model has been developed which considers this phenomena, and its effect on the bulk impactors effective heat of ablation is examined. The second research thrust that is discussed is focused on accurate modeling of impactor radiation phenomena. While another submission to the conference will discuss the application of our approach to thermal ground damage modeling, here, we present an overview of our extensive efforts to utilize available ground- and space-based observations of large bolides (~1m diameter, and above) to inform and validate our detailed modeling approaches. These methods have been shown to accurately reconstruct the detailed spectra for the Benesov bolide, as well as approximate the burn footprint for the Tunguska event. Recent effort has focused on reconciling light curve data from multiple sources (all-sky camera networks, GLM, US government sensors), using our validated model, and providing a calibrated model for luminous efficiency which can then be utilized to infer impactor properties such as shape, mass, and composition. This work will be demonstrated through an exemplar case study focusing on a large bolide event with observational data (e.g. Chelyabinsk, Flensburg, etc.). Finally, our team’s assessment on the current maturity of atmospheric entry models, and priorities for future research will be provided.

ATAP↗

Adaptive Optimization for System Performance and Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles

The emerging urban air mobility (UAM) sector in aerospace is driving development of unconventional multi-modal vehicle configurations and autonomous flight. The combination of multi-modal vehicle dynamics, complex environment, requirements to deal with flight contingencies in an efficient and safe manner, as well as necessity for precise trajectory following and performance, are the driving influence behind adaptive optimization for system performance. We are interested in trajectory optimization algorithm that would system parameter estimation and identifying the optimal switching time between modes of hybrid dynamical systems. This presentation discusses a parameterized optimal control trajectory optimization algorithm that is an extended and generalized version of Differential Dynamic Programming (DDP), titled Parameterized Differential Dynamic Programming (PDDP). DDP is an efficient trajectory optimization algorithm relying on second order approximations of a system’s dynamics and cost function and has recently been applied to optimize systems with time invariant parameters. Experiments are presented applying PDDP to solve model predictive control (MPC) and moving horizon estimation (MHE) tasks simultaneously. In particular, PDDP is used to determine the optimal transition point between flight regimes of a complex urban air mobility (UAM) class vehicle exhibiting multiple phases of flight and to identify and compensate for actuation faults.

optimization↗

Evaluation of Differential Peptide Loading on Tandem Mass Tag-Based Proteomic and Phosphoproteomic Data Quality

Global and phosphoproteome profiling has demonstrated great utility for the analysis of clinical specimens. One major barrier to the broad clinical application of proteomic profiling is the large amount of biological material required, particularly for phosphoproteomics—currently on the order of 25 mg wet tissue weight, depending on tissue type. For hematopoietic cancers such as acute myeloid leukemia (AML), the sample requirement is in excess of 10 million (1E7) peripheral blood mononuclear cells (PBMCs). Throughout the course of a prospective study, this requirement will certainly exceed what is obtainable from many of the individual patients/timepoints. For this reason, we were interested in examining the impact of differential peptide loading across multiplex channels on proteomic data quality. Methods: To achieve this, we tested a range of channel loading amounts (20, 40, 100, 200, and 400 µg of tryptic peptides, or approximately the material obtainable from 5E5, 1E6, 2.5E6, 5E6, and 1E7 AML patient cells) to assess proteome coverage, quantification reproducibility and accuracy in experiments utilizing isobaric tandem mass tag (TMT) labeling. As expected, we found that fewer missing values are observed in TMT channels with higher peptide loading amounts compared to those with lower loading. Moreover, channels with lower loading amounts have greater quantitative variability than channels with higher loading amounts. Statistical analysis of the differences in means among the five loading groups showed that the 20 µg loading group was significantly different from the 400 µg loading group. However, no significant differences were detected among the 40, 100, 200 and 400 µg loading groups. Conclusions: These assessment data demonstrate the practical limits of loading differential quantities of peptides across channels in TMT multiplexes, and provide a basis for designing the optimal clinical proteomics study when specimen quantities are limited.

59 BASIC BIOLOGICAL SCIENCES↗

Integrated modeling and analysis of a space-truss article

MSC/NASTRAN is being used in the Controls-Structures Interaction (CSI) program at NASA Langley Research Center as a key analytical tool for structural analysis as well as the basis for control law development, closed-loop performance evaluation, and system safety checks. Guest investigators from academia and industry are performing dynamics and control experiments on a flight-like deployable space truss called Mini-Mast to determine the effectiveness of various active-vibration control laws. MSC/NASTRAN was used to calculate natural frequencies and mode shapes below 100 Hz to describe the dynamics of the 20-meter-long lightweight Mini-Mast structure. Gravitational effects contribute significantly to structural stiffness and are accounted for through a two-phase solution in which the differential stiffness matrix is calculated and then used in the eigensolution. Reduced modal models are extracted for control law design and evaluation of closed-loop system performance. Predicted actuator forces from controls simulations are then applied to the extended model to predict member loads and stresses. These pre-test analyses reduce risks associated with the structural integrity of the test article, which is a major concern in closed-loop control experiments due to potential instabilities.

Alan E Stockwell↗

Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons

Neural networks (NNs) are currently changing the computational paradigm on how to combine data with mathematical laws in physics and engineering in a profound way, tackling challenging inverse and ill-posed problems not solvable with traditional methods. However, quantifying errors and uncertainties in NN-based inference is more complicated than in traditional methods. This is because in addition to aleatoric uncertainty associated with noisy data, there is also uncertainty due to limited data, but also due to NN hyperparameters, overparametrization, optimization and sampling errors as well as model misspecification. Although there are some recent works on uncertainty quantification (UQ) in NNs, there is no systematic investigation of suitable methods towards quantifying the total uncertainty effectively and efficiently even for function approximation, and there is even less work on solving partial differential equations and learning operator mappings between infinite-dimensional function spaces using NNs. In this work, we present a comprehensive framework that includes uncertainty modeling, new and existing solution methods, as well as evaluation metrics and post-hoc improvement approaches. Further, to demonstrate the applicability and reliability of our framework, we present an extensive comparative study in which various methods are tested on prototype problems, including problems with mixed input-output data, and stochastic problems in high dimensions. In the Appendix, we include a comprehensive description of all the UQ methods employed. Further, to help facilitate the deployment of UQ in Scientific Machine Learning research and practice, we present and develop in [1] an open-source Python library (github.com/Crunch-UQ4MI/neuraluq), termed NeuralUQ, that is accompanied by an educational tutorial and additional computational experiments.

11 physics-informed neural networks↗

Measurement of the double-differential inclusive jet cross section in proton-proton collisions at $\sqrt{s}$ = 5.02 TeV

The inclusive jet cross section is measured as a function of jet transverse momentum pT and rapidity y. The measurement is performed using proton-proton collision data at $\sqrt{s}$ = 5.02 TeV, recorded by the CMS experiment at the LHC, corresponding to an integrated luminosity of 27.4 pb −1 . The jets are reconstructed with the anti-k T algorithm using a distance parameter of R = 0.4, within the rapidity interval |y| < 2, and across the kinematic range 0.06 < p T < 1 TeV. The jet cross section is unfolded from detector to particle level using the determined jet response and resolution. The results are compared to predictions of perturbative quantum chromodynamics, calculated at both next-to-leading order and next-to-next-to-leading order. The predictions are corrected for nonperturbative effects, and presented for a variety of parton distribution functions and choices of the renormalization/factorization scales and the strong coupling α S .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Multicellular magnetotactic bacteria are genetically heterogeneous consortia with metabolically differentiated cells

Consortia of multicellular magnetotactic bacteria (MMB) are currently the only known example of bacteria without a unicellular stage in their life cycle. Because of their recalcitrance to cultivation, most previous studies of MMB have been limited to microscopic observations. To study the biology of these unique organisms in more detail, we use multiple culture-independent approaches to analyze the genomics and physiology of MMB consortia at single-cell resolution. We separately sequenced the metagenomes of 22 individual MMB consortia, representing 8 new species, and quantified the genetic diversity within each MMB consortium. This revealed that, counter to conventional views, cells within MMB consortia are not clonal. Single consortia metagenomes were then used to reconstruct the species-specific metabolic potential and infer the physiological capabilities of MMB. To validate genomic predictions, we performed stable isotope probing (SIP) experiments and interrogated MMB consortia using fluorescence in situ hybridization (FISH) combined with nanoscale secondary ion mass spectrometry (NanoSIMS). By coupling FISH with bioorthogonal noncanonical amino acid tagging (BONCAT), we explored their in situ activity as well as variation of protein synthesis within cells. We demonstrate that MMB consortia are mixotrophic sulfate reducers and that they exhibit metabolic differentiation between individual cells, suggesting that MMB consortia are more complex than previously thought. These findings expand our understanding of MMB diversity, ecology, genomics, and physiology, as well as offer insights into the mechanisms underpinning the multicellular nature of their unique lifestyle.

59 BASIC BIOLOGICAL SCIENCES↗

Beam Dynamics of the Muon $g\textrm{-}2$ Experiment

The Muon $g\textrm{-}2$ Experiment (E989) at Fermilab aims to measure the muon anomalous magnetic moment $a_{\mu}$ with unprecedented precision, potentially uncovering physics beyond the Standard Model of particle physics. The result based on Runs 1-3, released in 2023, achieved a precision of 0.20 ppm. The experiment circulates muons in a storage ring, measuring $a_{\mu}$ from decay positron time and energy measurements collected with calorimeters. To achieve the required accuracy, it is crucial to measure and control the magnetic field in the ring with high precision. Beam dynamics corrections are necessary for muons not orbiting exactly in the midplane, for their oscillations, and for electric field effects. Highly accurate beam dynamics simulations are instrumental for quantifying and validating the beam dynamics corrections, ultimately improving the precision of the $a_{\mu}$ measurement and facilitating the achievement of the ambitious $70\:\mathrm{ppb}$ systematic uncertainty goal. The measured field data was incorporated into models for simulations using three codes: \texttt{gm2ringsim} (an internal Geant4-based code), \textit{COSY INFINITY}, and \textit{BMAD}. The advantages of \texttt{gm2ringsim} include using CAD-based geometry and modelling the detector effects. \textit{COSY INFINITY} is a highly accurate and efficient code that uses high-order differential-algebraic transfer maps, precise fringe field calculations, and advanced symplectification methods. Symplectification is important for maintaining the physical correctness of the muon beam behaviour with high precision over the storage time, ensuring conservation of phase space volume and preventing artificial damping or excitation of particle motion. The experiment completed its final Run 6 in July 2023, collecting 21 times more data than the previous BNL experiment. Analyses of data from Runs 4-6 are ongoing, with results planned for release in 2025, potentially resolving the current tension between experiment and theory.

43 PARTICLE ACCELERATORS↗

Anonymization of Network Traces Data through Condensation-based Differential Privacy

Network traces are considered a primary source of information to researchers, who use them to investigate research problems such as identifying user behavior, analyzing network hierarchy, maintaining network security, classifying packet flows, and much more. However, most organizations are reluctant to share their data with a third party or the public due to privacy concerns. Therefore, data anonymization prior to sharing becomes a convenient solution to both organizations and researchers. Although several anonymization algorithms are available, few of them allow sufficient privacy (organization need), acceptable data utility (researcher need), and efficient data analysis at the same time. This article introduces a condensation-based differential privacy anonymization approach that achieves an improved tradeoff between privacy and utility compared to existing techniques and produces anonymized network trace data that can be shared publicly without lowering its utility value. Our solution also does not incur extra computation overhead for the data analyzer. A prototype system has been implemented, and experiments have shown that the proposed approach preserves privacy and allows data analysis without revealing the original data even when injection attacks are launched against it. When anonymized datasets are given as input to graph-based intrusion detection techniques, they yield almost identical intrusion detection rates as the original datasets with only a negligible impact.

97 MATHEMATICS AND COMPUTING↗

Self‐Assembly Methods Induce Different Individual‐Polymer‐Block Solvation Responses

An understanding of block-specific responses to stimuli in self-assembled copolymers is essential for the effective design of responsive materials. Here, materials formed from different post-reaction processing methods of the same ROMP block copolymer exhibit different block-specific solvent responses, as characterized in situ by fluorescence lifetime imaging microscopy (FLIM). FLIM data were acquired by tagging the polar or nonpolar block separately with a covalently incorporated viscosity-sensitive fluorescent molecular rotor to measure the changing tightness or looseness of assembly upon changes in solvent composition. Rapid precipitation from an insoluble solvent to form a film results in tighter assembly and less difference in tightness/looseness between the two blocks. Further, it interrupts individual block-solvent response behavior. Both results indicate an apparent disruption of the core–shell assembly. This model from FLIM is further supported by differential scanning calorimetry (DSC) and small-angle X-ray scattering (SAXS) data from isolated solids, which show tighter long-range interactions and more long-range order in these kinetically trapped states. Here, the experiments develop FLIM as a method for pinpointing stimuli-responsive behaviors from different processing methods to individual blocks. Together these outcomes provide a future handle for tailoring solvent-triggered assembly/disassembly behavior.

López, Pía A. [University of California, Irvine, C↗

The Effects of Material-Filled Voids on Detonation Wave Shape in Rubberized RDX Explosives

The sensitivity of explosives is affected by inhomogeneities within the material. This is evident in the increased shock sensitivity of explosives with slightly lower densities resulting from an increased number of hotspots. The influence of hotspots on explosive initiation has been well studied; however, few studies have been conducted on the effect of intermediate-sized voids (0.1–10 mm) on a propagating detonation wave. Cylindrical voids filled with air have been studied for diameters ranging from 0.3 mm to 0.8 mm for both 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX) and 1,3,5-trinitro-1,3,5-triazinane (RDX)-based rubberized explosives. Continuing the investigation into single cylindrical voids, this study examined the effects of 0.5 mm diameter voids filled with different inert cylindrical metals on the detonation wave shape for an RDX-based rubberized explosive. The metals selected for experiments were 1066 aluminum, brass, copper, and tungsten. The propagation of the detonation wave was captured using a digital streak camera. Experimental results showed that the extent of detonation wave shaping was closely tied to the density differential between the bulk explosive and metal insert. Forty-four different filler materials, including non-metals, were simulated using a hydrodynamic code to further analyze material inclusion effects. The main factors hypothesized to be of interest were bulk sound speed, shock impedance, and filler material density. We found that the local detonation delay could be correlated fairly well to a ratio of bulk sound speed and density. Understanding the influence of material inclusions on detonation performance and wave shape allows for tailoring of detonations.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗