Search NASA⌕ Search

SEARCH · Search NASA

Results for “Complexity bounding”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43

The quest to understand the fundamental structure of nuclear matter – outlook to QCD and the Electron-Ion Collider

Nuclear matter is made of quarks that are bound by gluons that also bind themselves. Unlike with the more familiar atomic and molecular matter, the interactions and structures in nuclear matter are inextricably mixed up, and observed properties of nucleons and nuclei, such as mass and spin, emerge out of this complex system. Ongoing and future QCD research offers the exciting prospect to obtain a multi-dimensional picture of the inner quark-gluon structure of protons and atomic nuclei and to inform us how the properties and structure of nuclear matter have emerged from the dynamics of QCD. This program is initiated at the 12-GeV Upgraded Jefferson Lab, concentrating on imaging the region in nucleon and nuclear structure where quarks prevail. A future Electron-Ion Collider (EIC) is planned at Brookhaven National Lab, in partnership with Jefferson Lab. The EIC will have a versatile range of beam energies, polarizations, and ion species, as well as high luminosity, to precisely image quarks, gluons, and their interactions in protons and complex atomic nuclei. The goal is an understanding of the internal structure of nuclear matter comparable to our knowledge of the electronic structure of atoms. The present status of the EIC will also be presented.

Ent, Rolf↗

Portal Monitoring Considerations for Treaty Verification Applications

Portal monitoring is one method in a suite of options for treaty verification and can assist in verification of treaty accountable items (TAIs). Portal monitor technology spans a wide range of sensors, including radiation detectors, break-beams, or weight sensors. For radiation-detecting portal monitors, they are able to confirm absence / presence of a radiological signature and to track TAI direction of motion. Portal monitoring uses measurements from strategically placed sensors (e.g., radiation detectors) to record the entry or egress of TAIs. The implementation of portal monitoring relies on three key elements: perimeter definition, portal locations, and sensor technology, and can be implemented in either time-bound or continuous operations depending on what is permitted by the Treaty.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

HIV-1 CD4-binding site germline antibody–Env structures inform vaccine design

BG24, a VRC01-class broadly neutralizing antibody (bNAb) against HIV-1 Env with relatively few somatic hypermutations (SHMs), represents a promising target for vaccine strategies to elicit CD4-binding site (CD4bs) bNAbs. To understand how SHMs correlate with BG24 neutralization of HIV-1, we report 4.1 Å and 3.4 Å single-particle cryo-EM structures of two inferred germline (iGL) BG24 precursors complexed with engineered Env-based immunogens lacking CD4bs N-glycans. Structures reveal critical Env contacts by BG24 iGL and identify antibody light chain structural features that impede Env recognition. In addition, biochemical data and cryo-EM structures of BG24 iGL variants bound to Envs with CD4bs glycans present provide insights into N-glycan accommodation, including structural modes of light chain adaptations in the presence of the N276 gp120 glycan. Together, these findings reveal Env regions critical for germline antibody recognition and potential sites to alter in immunogen design.

60 APPLIED LIFE SCIENCES↗

Characterization of an unusual SARS-CoV-2 main protease natural variant exhibiting resistance to nirmatrelvir and ensitrelvir

We investigate the effects of two naturally selected substitution and deletion (Δ) mutations, constituting part of the substrate binding subsites S2 and S4, on the structure, function, and inhibition of SARS CoV-2 main protease. Comparable to wild-type, MPro D48Y/ΔP168 undergoes N-terminal autoprocessing essential for stable dimer formation and mature-like catalytic activity. The structures are similar, but for an open active site conformation in MPro D48Y/ΔP168 and increased dynamics of the S2 helix, S5 loop, and the helical domain. Some dimer interface contacts exhibit shorter H bond distances corroborating the ~40-fold enhanced dimerization of the mutant although its thermal sensitivity to unfolding is 8 °C lower, relative to wild-type. ITC reveals a 3- and 5-fold decrease in binding affinity for nirmatrelvir and ensitrelvir, respectively, and similar GC373 affinity, to MPro D48Y/ΔP168 relative to wild-type. Structural differences in four inhibitor complexes of MPro D48Y/ΔP168 compared to wild-type are described. Consistent with enhanced dynamics, the S2 helix and S5 loop adopting a more open conformation appears to be a unique feature of MPro D48Y/ΔP168 both in the inhibitor-free and bound states. Our results suggest that mutational effects are compensated by changes in the conformational dynamics and thereby modulate N-terminal autoprocessing, K dimer , catalytic efficiency, and inhibitor binding.

60 APPLIED LIFE SCIENCES↗

Theoretically and practically efficient parallel nucleus decomposition

This paper studies the nucleus decomposition problem, which has been shown to be useful in finding dense substructures in graphs. We present a novel parallel algorithm that is efficient both in theory and in practice. Our algorithm achieves a work complexity matching the best sequential algorithm while also having low depth (parallel running time), which significantly improves upon the only existing parallel nucleus decomposition algorithm (Sariyüce et al. , PVLDB 2018). The key to the theoretical efficiency of our algorithm is a new lemma that bounds the amount of work done when peeling cliques from the graph, combined with the use of a theoretically-efficient parallel algorithms for clique listing and bucketing. We introduce several new practical optimizations, including a new multi-level hash table structure to store information on cliques space-efficiently and a technique for traversing this structure cache-efficiently. On a 30-core machine with two-way hyper-threading on real-world graphs, we achieve up to a 55x speedup over the state-of-the-art parallel nucleus decomposition algorithm by Sariyüce et al. , and up to a 40x self-relative parallel speedup. We are able to efficiently compute larger nucleus decompositions than prior work on several million-scale graphs for the first time.

Computer Science↗

Data-Driven Model Reduction of Multiphase Flow in a Single-Hole Automotive Injector

Fuel injector design has a substantial influence on the performance and emissions of direct injection engines. To date, large eddy simulations coupled with a single-fluidmixture modeling approach have shown great success in evaluating the complex interplay among injector design, fuel properties, and operating conditions on the injector performance. However, this simulation approach is too computationally expensive to be used by industry routinely for injector design due to the fine temporal and spatial resolution required to resolve wall-bounded flow within the injector. The work presented in this paper highlights a potential pathway to addressing this issue. To study the influence of injector design, fuel properties, and operating conditions on injector performance, large eddy simulations were performed to model the turbulent multiphase flow development through a side-oriented singlehole diesel injector. Using Latin hypercube sampling, the design space spanning a range of fuel properties, operating conditions, and needle lifts were explored. Two techniques for dimensionality reduction, namely proper orthogonal decomposition and autoencoders, were compared to evaluate their accuracy in representing the flow in a reduced dimensional space. Finally, based on the findings from this work, recommendations are provided in using machine learning approaches within the context of emulation to construct reduced-ordermodels for internal flow development relevant to automotive applications.

42 ENGINEERING↗

An Iterative Approach for Solving the SCOPF Problem Applying LP, SOCP, and NLP Subproblems

We propose to develop efficient algorithms and software for the SCOPF problem. We will employ an iterative approach that will: a) use linear subproblems and other active set filtering techniques to identify the most important contingencies and drastically reduce the SCOPF model size; b) solve SOCP relaxations of the reduced SCOPF to converge to the neighborhood of the global optimal solution and establish a lower bound on the solution, and; c) use a non-convex, nonlinear interior-point solver, Artelys Knitro, to converge quickly to the optimal solution. To identify the most effective approach, we will experiment with several techniques to identify the tradeoffs between contingency subproblem complexity and fast solvability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A solution to the surface intersection problem

An application-independent geometric model within a data base framework should support the use of Boolean operators which allow the user to construct a complex model by appropriately combining a series of simple models. The use of these operators leads to the concept of implicitly and explicitly defined surfaces. With an explicitly defined model, the surface area may be computed by simply summing the surface areas of the bounding surfaces. For an implicitly defined model, the surface area computation must deal with active and inactive regions. Because the surface intersection problem involves four unknowns and its solution is a space curve, the parametric coordinates of each surface must be determined as a function of the arc length. Various subproblems involved in the general intersection problem are discussed, and the mathematical basis for their solution is presented along with a program written in FORTRAN IV for implementation on the IBM 370 TSO system.

Timer, H. G.↗

The Wisconsin magmatic terrane: An Early Proterozoic greenstone-granite terrane formed by plate tectonic processes

The Wisconsin magmatic terrane (WMT) is an east trending belt of dominantly volcanic-plutonic complexes of Early Proterozoic age (approx. 1850 m.y.) that lies to the south of the Archean rocks and Early Proterozoic epicratonic sequence (Marquette Range Supergroup) in Michigan. It is separated from the epicratonic Marquette Range Supergroup by the high-angle Niagara fault, is bounded on the south, in central Wisconsin, by Archean gneisses, is truncated on the west by rocks of the Midcontinent rift system, and is intruded on the east by the post-orogenic Wolf river batholith. The overall lithologic, geochemical, metallogenic, metamorphic, and deformational characteristics of the WMT are similar to those observed in recent volcanic arc terranes formed at sites of plate convergence. It is concluded that the WMT represents an evolved oceanic island-arc terrane accreated to the Superior craton in the Early Proterozoic. This conclusion is strengthened by the apparent absence of Archean basement from most of the WMT, and the recent recognition of the passive margin character of the epicratonic Marquette Range Supergroup.

Schulz, K. J.↗

Over-Expression, Purification and Crystallization of Human Dihydrolipoamide Dehydrogenase

Dehydrolipoamide dehydrogenase (E3; dihydrolipoan-tide:NAD+ oxidoreductase, EC 1.8.1.4) is a common catalytic component found in pyruvate dehydrogenase complex, alpha-ketoglutarate dehydrogenase complex, and branched-chain cc-keto acid dehydrogenase complex. E3 is also a component (referred to as L protein) of the glycine cleavage system in bacterial metabolism (2). Active E3 forms a homodimer with four distinctive subdomain structures (FAD binding, NAD+ binding, central and interface domains) with non-covalently but tightly bound FAD in the holoenzyme. Deduced amino acids from cloned full-length human E3 gene showed a total of 509 amino acids with a leader sequence (N-terminal 35 amino acids) that is excised (mature form) during transportation of expressed E3 into mitochondria membrane. So far, three-dimensional structure of human E3 has not been reported. Our effort to achieve the elucidation of the X-ray crystal structure of human E3 will be presented. Recombinant pPROEX-1 expression vector (from GIBCO BRL Life Technologies) having the human E3 gene without leader sequence was constructed by Polymerase Chain Reaction (PCR) and subsequent ligation, and cloned in E.coli XL1-Blue by transformation. Since pPROEX-1 vector has an internal His-tag (six histidine peptide) located at the upstream region of a multicloning site, one-step affinity purification of E3 using nickelnitriloacetic acid (Ni-NTA) agarose resin, which has a strong affinity to His-tag, was feasible. Also a seven-amino-acid spacer peptide and a recombinant tobacco etch virus protease recognition site (seven amino acids peptide) found between His-tag and first amino acid of expressed E3 facilitated the cleavage of His-tag from E3 after the affinity purification. By IPTG induction, ca. 15 mg of human E3 (mature form) was obtained from 1L LB culture with overnight incubation at 25C. Over 98% of purity of E3 from one-step Ni-NTA agarose affinity purification was confirmed by SDS-PAGE analysis. For crystallization, E3 samples were prepared with and without His-tag. To minimize the aggregation of E3, apo- and holo- forms of E3s were tested, as well as a mutated E3. Dynamic light scattering measurements revealed that the E3 preparations without His-tag and substrate are highly monodispersive with regard to homodimers. Consequent crystallization trials of this E3 preparation led to single crystals of E3 grown by the vapor diffusion method. Crystals were obtained within a few days from solution containing poly (ethylene glycol) monomethyl ether 5000 as a precipitant. Autoindexing and integration of the X-ray diffraction data showed that E3 crystals belong to an orthorhombic system with unit cell parameters a-- 123. 1, b= 165.3 and c=214.3A. Further optimization of protein preparation and crystallization experiments for the structural determination will be discussed.

Hong, Y. S.↗

(abstract) A Low-Cost Mission to 2060 Chiron Based on the Pluto Fast Flyby

The Pluto Fast Flyby-based mission to Chiron described in this paper is a low cost, scientifically rewarding, focused mission in the outer solar system. The proposed mission will make a flyby of 2060 Chiron, an active 'comet' with over 10(sup 4) times the mass of Halley, and an eccentric, Saturn-crossing orbit which ranges from 8.5 to 19 AU. This mission concept achieves the flyby 4.2 years after launch on a direct trajectory from Earth, is independent of Jupiter launch windows, and fits within Discovery cost guidelines. This mission offers the scientific opportunity to examine a class of object left unsampled by the trail-blazing Mariners, Pioneers, Voyagers, and missions to Halley. Spacecraft reconnaissance of Chiron addresses unique objectives relating to cometary science, other small bodies, the structure of quasi-bound atmospheres on modest-sized bodies, and the origin of primitive bodies and the giant planets. Owing to Chiron's large size (180<D<370 km), unique nature, and unusual orbit, this mission is likely to draw significant public interest. As described by COMPLEX, the SSEC, and later the SSES, flybys are the appropriate scale missions for initial reconnaissance missions. Carrying three sophisticated instruments, the proposed flyby will return critical data about Chiron's size, shape, polar obliquity, atmosphere, surface morphology, surface composition, internal structure, surface activity (including the nature of Chiron's outbursts), and origin. Engineering analysis indicates that the spacecraft is capable of navigating to and encountering Chiron at close approach distances of less than 5 000 km, well inside the 50 000 to 150 000 km coma, and perhaps within the collisional chemistry zone of the coma. The low cost of the proposed Chiron mission is based on the opportunity to use the planned Pluto Flyby spare spacecraft and a Proton Expendable Launch Vehicle (ELV) (the pluto spacecraft is being designed to be compatible with a Proton launch). Backup launch opportunities on Delta II and Atlas ELVs are available. The Pluto Fast Flyby mission plans to develop a low cost ($150M), lightweight (<150 kg) outer planet spacecraft which is well suited to flyby reconnaissance in the outer solar system. This Chiron flyby mission is designed to leverage SSED's Pluto spacecraft investment into a scientifically valuable successor mission within the Discovery cost cap. Taking advantage of the spare spacecraft, we estimate the Discovery Chiron intercept mission can be launched for less than $100 M. We believe this makes a highly attractive proposal, which maintains US presence and leadership in the study of the outer solar system, and enables the first-time exploration of a wholly new class of planetary target, an outer solar system planetesimal.

2060 Chiron planetesimal flyby Pluto Fast Flyby sp↗

On streak spacing in wall-bounded turbulent flows

The present study is a continuation of the examination by Hamilton et al. of the regeneration mechanisms of near-wall turbulence and an attempt to investigate the conjecture of Waleffe et al. The basis of this study is an extension of the 'minimal channel' approach of Jimenez and Moin that emphasizes the near-wall region and reduces the complexity of the turbulent flow by considering a plane Couette flow of near minimum Reynolds number and stream-wise and span-wise extent. Reduction of the flow Reynolds number to the minimum value which will allow turbulence to be sustained has the effect of reducing the ratio of the largest scales to the smallest scales or, equivalently, of causing the near-wall region to fill more of the area between the channel walls. A plane Couette flow was chosen for study since this type of flow has a mean shear of a single sign, and at low Reynolds numbers, the two wall regions are found to share a single set of structures.

Hamilton, James M.↗

Efficient Training of Deep Neural Operator Networks via Randomized Sampling

Neural operators (NOs) employ deep neural networks to learn the mappings between infinitedimensional function spaces. Deep operator network (DeepONet), a popular NO architecture, has demonstrated success in the real-time prediction of complex dynamics across various scientific and engineering applications. In this work, we introduce a random sampling technique to be adopted during the training of DeepONet, aimed at improving the generalization ability of the model, while significantly reducing the computational time. The proposed approach targets the trunk network of the DeepONet model that outputs the basis functions corresponding to the spatiotemporal locations of the bounded domain on which the physical system is defined. While constructing the loss function, DeepONet training traditionally considers a uniform grid of spatiotemporal points at which all the output functions are evaluated for each iteration. This approach leads to a larger batch size, resulting in poor generalization and increased memory demands, due to the limitations of the stochastic gradient descent (SGD) optimizer. The proposed random sampling over the inputs of the trunk net mitigates these challenges, improving generalization and reducing the memory requirements during training, resulting in significant computational gains. We validate our hypothesis through three benchmark examples, demonstrating substantial reductions in training time while achieving comparable or lower overall test errors relative to the traditional training approach. Our results indicate that incorporating randomization in the trunk network inputs during training enhances the efficiency and robustness of DeepONet, offering a promising avenue for improving the framework’s performance in modeling complex physical systems.

Karumuri, Sharmila [Department of Civil & Systems ↗

Challenges and Opportunities in State‐of‐the‐Art Proteomics Analysis for Biomarker Development From Plasma Extracellular Vesicles

Extracellular vesicles (EVs) are membrane-bound particles secreted by cells, playing crucial roles in intercellular communication. The composition of EVs can undergo changes in response to stress and disease conditions, making them excellent biomarker candidates. However, extracting protein information from EVs can be challenging due to their low abundance in complex biofluids and copurification with contaminant proteins and particles. Techniques to enrich EVs have their strengths and limitations, without one being able to purify EVs to complete homogeneity. This can lead to compromised recovery rates and increased complexity, making data interpretation difficult. In this viewpoint article, we explore the concept that better characterization of EV composition, followed by quantification of EV proteins in complex samples, might be a more viable route for biomarker development. Mass spectrometers can provide reproducible deep coverage of the EV proteome, despite sample impurities. This paradigm shift presents opportunities to integrate advanced bioinformatics tools to refine the EV proteome landscape, identify novel biomarkers, and streamline validation processes in biomarker development. By focusing on leveraging technology rather than achieving absolute purity, this approach can transform current practices and open opportunities for robust biomarker discovery. Herein, we highlight not only such opportunities but also challenges to implement this concept.

Dakup, Panshak P. [Pacific Northwest National Labo↗

Neural-network model for force prediction in multi-principal-element alloys

Atomistic simulations can provide useful insights into the physical properties of multi-principal-element alloys. However, classical potentials mostly fail to capture key quantum (electronic-structure) effects. Here we present a deep 3D convolutional neural network (3D CNN) based framework combined with a voxelization technique to design interatomic potentials for chemically complex alloys. We highlight the performance of the 3D CNN model and its efficacy in computing potentials using the medium-entropy alloy TaNbMo. In order to provide insights into the effect of voxel resolution, we implemented two approaches based on the inner and outer bounding boxes. An efficient 3D CNN model, which is as accurate as the density-functional theory (DFT) approach, for calculating potentials will provide a promising schema for accurate atomistic simulations of structure and dynamics of general multi-principle element alloys.

36 MATERIALS SCIENCE↗

Structures of drug-specific monoclonal antibodies bound to opioids and nicotine reveal a common mode of binding

Opioid-related fatal overdoses have reached epidemic proportions. Because existing treatments for opioid use disorders offer limited long-term protection, accelerating the development of newer approaches is critical. Monoclonal antibodies (mAbs) are an emerging treatment strategy that targets and sequesters selected opioids in the bloodstream, reducing drug distribution across the blood-brain barrier, thus preventing or reversing opioid toxicity. We previously identified a series of murine mAbs with high affinity and selectivity for oxycodone, morphine, fentanyl, and nicotine. To determine their binding mechanism, we used X-ray crystallography to solve the structures of mAbs bound to their respective targets, to 2.2 Å resolution or higher. Structural analysis showed a critical convergent hydrogen bonding mode that is dependent on a glutamic acid residue in the mAbs’ heavy chain and a tertiary amine of the ligand. Further, characterizing drug-mAb complexes represents a significant step toward rational antibody engineering and future manufacturing activities to support clinical evaluation.

60 APPLIED LIFE SCIENCES↗

Site-specific electronic structure of covalently linked bimetallic dyads from nitrogen K-edge x-ray absorption spectroscopy

A nitrogen K-edge x-ray absorption near-edge structure (XANES) survey is presented for tetrapyrido[3,2-a:',3'-c:3'',2''-h:2''',3'''-j]phenazine (tpphz)-bridged bimetallic assemblies that couple chromophore and catalyst transition metal complexes for light driven catalysis, as well as their individual molecular constituents. We demonstrate the high N site sensitivity of the N pre-edge XANES features, which are energetically well-separated for the phenazine bridge N atoms and for the individual metal-bound N atoms of the inner coordination sphere ligands. By comparison with the time-dependent density functional theory calculated spectra, we determine the origins of these distinguishable spectral features. We find that metal coordination generates large shifts toward higher energy for the metal-bound N atoms, with increasing shift for 3d < 4d < 5d metal bonding. This is attributed to increasing ligand-to-metal σ donation that increases the effective charge of the bound N atoms and stabilizes the N 1s core electrons. In contrast, the phenazine bridge N pre-edge peak is found at a lower energy due to stabilization of the low energy electron accepting orbital localized on the phenazine motif. While no sensitivity to ground state electronic coupling between the individual molecular subunits was observed, the spectra are sensitive to structural distortions of the tpphz bridge. Here these results demonstrate N K-edge XANES as a local probe of electronic structure in large bridging ligand motifs, able to distinctly investigate the ligand-centered orbitals involved in metal-to-ligand and ligand-to-ligand electron transfer following light absorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗