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At least 595 records · Page 33

A Geometry-Driven Longitudal Topic Model

A simple and scalable framework for longitudinal analysis of Twitter data is developed that combines latent topic models with computational geometric methods. Dimensionality reduction tools from computational geometry are applied to learn the intrinsic manifold on which the latent, temporal topics reside. Then shortest path distances on the manifold are used to link together these topics. The proposed framework permits visualization of the low-dimensional embedding which provides clear interpretation of the complex, high-dimensional trajectories that may exist among latent topics. Practical application of the proposed framework is demonstrated through its ability to capture and effectively visualize natural progression of latent COVID-19 related topics learned from Twitter data. Interpretability of the trajectories is achieved by comparing to real-world events. In addition, the framework permits study of spatial variation in Twitter behavior for learned topics. The analysis demonstrates that the proposed framework is able to capture granular-level impact of COVID-19 on public discussions. We end by arguing that Twitter data, when analyzed within the proposed framework, can serve as a valuable supplementary data stream for COVID-related studies.

97 MATHEMATICS AND COMPUTING↗

AQuaRef: machine learning accelerated quantum refinement of protein structures

Cryo-EM and X-ray crystallography provide crucial experimental data for obtaining atomic-detail models of biomacromolecules. Refining these models relies on library-based stereochemical data, which, in addition to being limited to known chemical entities, do not include meaningful noncovalent interactions. Quantum mechanical (QM) calculations could alleviate these issues but are too expensive for large molecules. Here we present a novel AI-enabled Quantum Refinement (AQuaRef) based on AIMNet2 machine learned interatomic potential (MLIP) mimicking QM at substantially lower computational costs. By refining 41 cryo-EM and 30 X-ray structures, we show that this approach yields atomic models with superior geometric quality compared to standard techniques, while maintaining an equal or better fit to experimental data. Notably, AQuaRef aids in determining proton positions, as illustrated in the challenging case of short hydrogen bonds in the parkinsonism-associated human protein DJ-1 and its bacterial homolog YajL.

Zubatyuk, Roman [Carnegie Mellon University, Pitts↗

Inverse design of cellular structures with the targeted nonlinear mechanical response

Advanced additive manufacturing capabilities have enabled a transformational ability to create sophisticated cellular structures using diverse materials. By altering the topology of the unit cell, the mechanical behavior, such as the stress-strain response during compression, can be modulated. Nevertheless, identifying a printable topology within an enormous design space that would precisely deliver the targeted nonlinear material response is challenging. We propose a data-driven generative framework based on a conditional variational autoencoder (cVAE) architecture that can inverse design the cellular structure based on the intended nonlinear stress-strain response. Trained on a dataset of structure-property pairs, the cVAE learns a compact and expressive latent space that enables efficient mapping from targets to feasible geometries. Two inference modes are explored: (1) decoder-only generation, which enables the exploration of diverse designs conditioned solely on the desired mechanical response, and (2) encoder-decoder generation, which further allows for the incorporation of desired topologies, ensuring the generated structure conforms to both mechanical properties and to desired-topology constraints. The results demonstrate that the model can generate structurally plausible and mechanically accurate designs, with the predicted stress-strain curves closely matching the targets. Even under joint conditioning, the model effectively balances geometric fidelity and functional performance.

36 MATERIALS SCIENCE↗

Deep transfer operator learning for partial differential equations under conditional shift

Transfer learning enables the transfer of knowledge gained while learning to perform one task (source) to a related but different task (target), hence addressing the expense of data acquisition and labelling, potential computational power limitations and dataset distribution mismatches. Here, we propose a new transfer learning framework for task-specific learning (functional regression in partial differential equations) under conditional shift based on the deep operator network (DeepONet). Task-specific operator learning is accomplished by fine-tuning task-specific layers of the target DeepONet using a hybrid loss function that allows for the matching of individual target samples while also preserving the global properties of the conditional distribution of the target data. Inspired by conditional embedding operator theory, we minimize the statistical distance between labelled target data and the surrogate prediction on unlabelled target data by embedding conditional distributions onto a reproducing kernel Hilbert space. We demonstrate the advantages of our approach for various transfer learning scenarios involving nonlinear partial differential equations under diverse conditions due to shifts in the geometric domain and model dynamics. Our transfer learning framework enables fast and efficient learning of heterogeneous tasks despite considerable differences between the source and target domains.

42 ENGINEERING↗

Controlling inversion disorder in a stoichiometric spinel magnet

In the study of frustrated quantum magnets, it is essential to be able to control the nature and degree of site disorder during the growth process, as many measurement techniques are incapable of distinguishing between site disorder and frustration-induced spin disorder. Pyrochlore-structured spinel oxides can serve as model systems of geometrically frustrated three-dimensional quantum magnets; however, the nature of the magnetism in one well-studied spinel, ZnFe 2 O 4 , remains unclear. Here, we demonstrate simultaneous control of both stoichiometry and inversion disorder in the growth of ZnFe 2 O 4 single crystals, directly yielding a revised understanding of both the collective spin behavior and lattice symmetry. Crystals grown in the stoichiometric limit with minimal site inversion disorder contravene all the previously suggested exotic spin phases in ZnFe 2 O 4 . Furthermore, the structure is confirmed on the F$\bar{4}$3m space group with broken inversion symmetry that induces antiferroelectricity. The effective tuning of magnetic behavior by site disorder in the presence of robust antiferroelectricity makes ZnFe 2 O 4 of special interest to multiferroic devices.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

VorLap

SAND2025-10210O VorLap is a vortex-induced vibration overlap prediction tool for static structures, such as parked wind turbines and marine turbines encountering fluid flow (water or air movement around them) that may induce vortex-induced vibration. This tool uses precomputed frequency domain data for specific cross-sectional shapes or a generalized shedding model, along with geometric data and structural natural frequency data, to identify areas and conditions where vortex-induced vibration may occur. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Moore, Kevin [Sandia National Lab. (SNL-CA), Liver↗

Microwave characteristics of the ocean surface in the 1-10 GHz band

The microwave characteristics of calm, rough, and foam-covered ocean surfaces were studied, and a technique was developed for deriving thermodynamic ocean surface temperatures from brightness temperatures measured by an earth-orbiting radiometer. This investigation encompassed frequencies in the range 1 to 10 GHz (wavelength range of 30 to 3 cm) and was based on the use of a one-dimensional geometrical optics roughness model, including shadowing and multiple scattering of radiant electromagnetic energy. Provision is made in the model for characterizing surface roughness through the rms slope versus wind velocity relations previously established. Suitable foam and atmospheric models were superimposed on the roughness model.

Strong, A. E.↗

Algebraic, geometric, and stochastic aspects of genetic operators

Genetic algorithms for function optimization employ genetic operators patterned after those observed in search strategies employed in natural adaptation. Two of these operators, crossover and inversion, are interpreted in terms of their algebraic and geometric properties. Stochastic models of the operators are developed which are employed in Monte Carlo simulations of their behavior.

Foo, N. Y.↗

Aerodynamic load distributions at transonic speeds for a close-coupled wing-canard configuration: Tabulated pressure data

Wind tunnel studies are reported on both the canard and wing surfaces of a model that is geometrically identical to one used in several force and moment tests to provide insight into the various aerodynamic interference effects. In addition to detailed pressures measurements, the pressures were integrated to illustrate the effects of Mach number, canard location, and canard-wing interference on various aerodynamic parameters. Transonic pressure tunnel Mach numbers ranged from 0.70 to 1.20 for data taken from 0 deg to approximately 16 deg angle-of-attack at 0 deg sideslip.

Washburn, K. E.↗

Charging analysis of the SCATHA satellite

A detailed model of the geometrical, material, and electrical properties of the SCATHA satellite for use with the NASA charging analyzer program is described. Charging calculations in an intense magnetospheric substorm environment demonstrated that: (1) long booms can significantly perturb the potentials near the spacecraft, and (2) discharging by sunlight or by active control can cause serious time-dependent differential charging problems.

Schnuelle, G. W.↗

Calculation of transonic aileron buzz

An implicit finite-difference computer code that uses a two-layer algebraic eddy viscosity model and exact geometric specification of the airfoil has been used to simulate transonic aileron buzz. The calculated results, which were performed on both the Illiac IV parallel computer processor and the Control Data 7600 computer, are in essential agreement with the original expository wind-tunnel data taken in the Ames 16-Foot Wind Tunnel just after World War II. These results and a description of the pertinent numerical techniques are included.

Steger, J. L.↗

The half-wave rectifier response of the magnetosphere and antiparallel merging

In some ways the magnetosphere behaves as if merging occurs only when the interplanetary magnetic field (IMF) is southward, and in other ways it behaves as if merging occurs for all IMF orientations. An explanation of this duality is offered in terms of a geometrical antiparallel merging model which predicts merging for all IMF orientations but magnetic flux transfer to the tail only for southward IMF. This is in contrast to previous models of component merging, where merging and flux transfer occur together for nearly all IMF orientations. That the problematic duality can be explained by the model is compelling evidence that antiparallel merging should be seriously considered in constructing theories of the merging process.

Crooker, N. U.↗

GASP- General Aviation Synthesis Program. Volume 2: Geometry

The gross characteristics of an aircraft under study are specified to the subroutines SIZE. The principal quantities specified are both geometric (lengths and areas) and operational (altitude and Mach number). The sequence of computations carried out by SIZE is controlled by the parameter NPC which is passed into SIZE by COMMON. When NPC-0, the computation is initialized. Subsequently, NPC is set to 2 and the program advances through the geometric computations. Geometry models for the fuselage, wing, empennage, cabin pressurization, and nacelle area are examined.

Hague, D.↗

Spectropolarimetry and the physical structure of proto-planetary nebulae

Optical spectropolarimetry and spectrophotometry are presented of the two bipolar nebulae GL 618 and M2-9. A comparison of the polarization in the emission lines and the continuum is used to construct geometrical and physical models for each object. It is found that the forbidden lines arise largely in the visible nebulae, whereas the permitted lines are formed in a central high-density region and are scattered with the stellar continuum by dust grains in the lobes. Condensations are found to be an important component of the lobes, reinforcing the view that these bipolars represent a very early phase in the life of a planetary nebula.

Schmidt, G. D.↗

Model error estimation for large space systems

In-flight estimation of large structure model errors may have to be carried out in order to detect inevitable deficiencies in large structure controller/estimator models. These error estimates can most efficiently be obtained by the minimization of a quadratic functional of the model errors and on the subsequent analysis of the resulting optimal model error estimates. An integral operator approach to estimation leads to a geometrical interpretation of the model error estimation process. One of the significant insights gained with this interpretation is that the actual but unknown model errors can be decomposed as the sum of two distinct components that are orthogonal in some sense. One of these components is a so-called minimal error vector that retains many of the significant dynamics of the actual errors. The basic ideas in the model error estimation approach are first set forth with a two-dimensional analogy that has most of the essential features of the general estimation problem. The generalized results are then established and their application to a reference large structure model illustrated.

Rodriguez, G.↗

The design of a wind tunnel VSTOL fighter model incorporating turbine powered engine simulators

A wind-tunnel model of a supersonic VSTOL fighter aircraft configuration has been developed for use in the evaluation of airframe-propulsion system aerodynamic interactions. The model may be employed with conventional test techniques, where configuration aerodynamics are measured in a flow-through mode and incremental nozzle-airframe interactions are measured in a jet-effects mode, and with the Compact Multimission Aircraft Propulsion Simulator which is capable of the simultaneous simulation of inlet and exhaust nozzle flow fields so as to allow the evaluation of the extent of inlet and nozzle flow field coupling. The basic configuration of the twin-engine model has a geometrically close-coupled canard and wing, and a moderately short nacelle with nonaxisymmetric vectorable exhaust nozzles near the wing trailing edge, and may be converted to a canardless configuration with an extremely short nacelle. Testing is planned to begin in the summer of 1982.

Bailey, R. O.↗

Interpretation of satellite-observed thunderstorm anvil structure

The radiative characteristics of an anvil plume sensed by satellite radiometers are studied to discern the reason for an observed 'V' pattern of colder temperatures and a corresponding internal warm region. The measured black body temperature is affected by the ice water content and particle distributions in the cloud layer. Attention is given to 'V' anvil structure examined by Haynesfield et al. (1979). The GOES satellite IR data are treated with a plane parallel geometric radiative transfer model and a particle trajectory model is used to simulate ice particle concentrations downwind from a strongly divergent cloud top. Output from the two models indicate the 'V' pattern arises from divergence in the storm anvil. The particle concentration was elevated within the V-shaped region, causing lower temperatures in the V arms. The V is produced by strong upper level flow as well as strong mass and moisture divergence in the storm outflow.

Heymsfield, G. M.↗

Fiber optic pressure sensors in skin-friction measurements

A fiber optic lever sensing technique that can be used to measure normal pressure as well as shear stresses is discussed. This method uses three unequal fibers combining small size and good sensitivity. Static measurements appear to confirm the theoretical models predicted by geometrical optics and dynamic tests performed at frequencies up to 10 kHz indicate a flat response within this frequency range. These sensors are intended for use in a low speed wind tunnel environment.

Cuomo, F. W.↗