Statistical Inference with Topological Data Analysis with Applications to Precision Medicine
Explore the source record for details and available documents.
Datta, Esha↗
SEARCH · Search NASA
Results for “Topological analysis”
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.
Topology Data Analysis Guided Prompt Optimization of Segment Anything Model for Zero-Shot Segmentation of Biological Images
Explore the source record for details and available documents.
Biological and medical sciences, Computer science↗
Three-dimensional atomic scale characterization of {11$\overline{2}$2} twin boundaries in titanium
The {11$\overline{2}$2}<11$\overline{23}$> compression twin can accommodate a considerable amount of strain under c-axis compression in Ti. However, unlike the tensile twin, the structure of the {10$\overline{1}$2}$\langle$$\overline{1}$011$\rangle$ compressive twins has not been completely characterized. In this study, we apply a combined technique of HR-TEM characterization, topological analysis, and atomistic simulations to explore the facets that bound the {11$\overline{2}$2}<11$\overline{23}$> twin in Ti. In addition to the currently known facets (CTB and B-Py), six new facets are observed and categorized for the first time from atomic-scale TEM observations along five crystallographic directions. The six new facets are (11$\overline{2}$0)//(11$\overline{2}$6), PrPr1, PyPy1, (2$\overline{11}$1)//($\overline{1}$2$\overline{1}$2), (1$\overline{1}$04)//(01$\overline{11}$), and (01$\overline{1}$0)//(2$\overline{11}$4). Results from the topological and computational analysis are in reasonable agreement with and support the HRTEM observations. Specifically, (1) the observed facets align with low-index interfaces in both twin and matrix domains, (2) the facets with lower surface energies are found to form extended interfaces, and (3) high-surface-energy facets are found at the twin tip region and explained by the fact that the energy of the combined facet and facet junction configuration is energetically preferred in the twin tip region. These results not only provide a comprehensive understanding of the 3D structure of the {11$\overline{2}$2}<11$\overline{23}$> compressive twins in Ti, but also validate the MD procedure and the Ti interatomic potential employed. This is extremely important for future study of the {11$\overline{2}$2} twin mobility and interactions with other defects, both features that remain extremely challenging to capture in experiments.
36 MATERIALS SCIENCE↗
Topological Guided Detection of Extreme Wind Phenomena: Implications for Wind Energy
Extreme wind phenomena play a crucial role in the efficient operation of wind farms for renewable energy generation. However, existing detection methods are computationally expensive, limited to specific coordinate. In real-world scenarios, understanding the occurrence of these phenomena over a large area is essential. Therefore, there is a significant demand for a fast and accurate approach to forecast such events. In this paper, we propose a novel method for detecting wind phenomena using topological analysis, leveraging the gradient of wind speed or critical points in a topological framework. By extracting topological features from the wind speed profile within a defined region, we employ topological distance to identify extreme wind phenomena. Our results demonstrate the effectiveness of utilizing topological features derived from regional wind speed profiles. We validate our approach using high-resolution simulations with the Weather Research and Forecasting model (WRF) over a month in the US East Coast.
MATHEMATICS AND COMPUTING,WIND ENERGY↗
Topological Guided Detection of Extreme Wind Phenomena: Implications for Wind Energy: Preprint
Extreme wind phenomena play a crucial role in the efficient operation of wind farms for renewable energy generation. However, existing detection methods are computationally expensive, limited to specific coordinate. In real-world scenarios, understanding the occurrence of these phenomena over a large area is essential. Therefore, there is a significant demand for a fast and accurate approach to forecast such events. In this paper, we propose a novel method for detecting wind phenomena using topological analysis, leveraging the gradient of wind speed or critical points in a topological framework. By extracting topological features from the wind speed profile within a defined region, we employ topological distance to identify extreme wind phenomena. Our results demonstrate the effectiveness of utilizing topological features derived from regional wind speed profiles. We validate our approach using high-resolution simulations with the Weather Research and Forecasting model (WRF) over a month in the US East Coast.
MATHEMATICS AND COMPUTING,WIND ENERGY↗
Optimal D-FACTS Placement in Moving Target Defense Against False Data Injection Attacks
Moving target defense (MTD) is a defense strategy to detect stealthy false data injection (FDI) attacks against the power system state estimation using distributed flexible AC transmission system (D-FACTS) devices. However, existing studies neglect to address a fundamental yet critical issue, i.e., the D-FACTS placement, by assuming that all lines are equipped with D-FACTS devices. Here, to tackle this problem, we first derive analytical necessary conditions and requirements on the D-FACTS placement for a complete MTD. Further, we propose sufficient conditions using a graph theory-based topology analysis to ensure that the MTD under the proposed D-FACTS placement has the maximum rank of its composite matrix, which is indicative of the MTD effectiveness. Based on the analytical conditions, we design D-FACTS placement algorithms by using the minimum number of D-FACTS devices to achieve the maximum MTD effectiveness. A novel MTD-based ACOPF model, in which the reactance of D-FACTS lines is introduced as decision variables, is proposed to find a trade-off between the system loss and the MTD effectiveness. Numerical results on 6-bus, IEEE 14-bus, and IEEE 118-bus systems show the efficacy of MTDs using the proposed D-FACTS placement algorithms in maximizing the composite matrix rank and detecting FDI attacks.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Coexisting kagome and heavy fermion flat bands in YbCr 6 Ge 6
Flat bands, electronic states with nearly dispersionless energy-momentum structure, provide fertile ground for unconventional quantum phases. Recent observations of flat bands at the Fermi level in kagome metals open the possibility of unifying topology and correlation-driven heavy-fermion physics. Here we show that topology and heavy-fermion correlations coexist in the layered kagome metal YbCr 6 Ge 6 . At high temperatures, an intrinsic kagome flat band—arising from frustrated hopping on the kagome lattice—dominates the Fermi level. Upon cooling, localized Yb 4f-states hybridize with the topological kagome flat bands, transforming this state into momentum-independent Kondo resonance states across the entire Brillouin zone. Topological analysis of the hybridization gaps reveals filling-tunable weak and strong topological Kondo-insulating regimes, and identifies a topological Dirac–Kondo semimetal. Taken together, these results identify YbCr 6 Ge 6 as a prototype of a topological heavy-fermion system and a platform where geometric frustration, strong correlations, and topology converge, with broad implications for correlated quantum matter.
36 MATERIALS SCIENCE↗
Exploring Classification of Topological Priors With Machine Learning for Feature Extraction
In many scientific endeavors, increasingly abstract representations of data allow for new interpretive methodologies and conceptualization of phenomena. For example, moving from raw imaged pixels to segmented and reconstructed objects allows researchers new insights and means to direct their studies toward relevant areas. Thus, the development of new and improved methods for segmentation remains an active area of research. With advances in machine learning and neural networks, scientists have been focused on employing deep neural networks such as U-Net to obtain pixel-level segmentations, namely, defining associations between pixels and corresponding/referent objects and gathering those objects afterward. Topological analysis, such as the use of the Morse-Smale complex to encode regions of uniform gradient flow behavior, offers an alternative approach: first, create geometric priors, and then apply machine learning to classify. This approach is empirically motivated since phenomena of interest often appear as subsets of topological priors in many applications. Using topological elements not only reduces the learning space but also introduces the ability to use learnable geometries and connectivity to aid the classification of the segmentation target. Here, in this article, we describe an approach to creating learnable topological elements, explore the application of ML techniques to classification tasks in a number of areas, and demonstrate this approach as a viable alternative to pixel-level classification, with similar accuracy, improved execution time, and requiring marginal training data.
97 MATHEMATICS AND COMPUTING↗
Emergence of Unstable Focused Flow Induced by Variable‐Density Flows in Vertical Fractures
Abstract Fluids with different densities often coexist in subsurface fractures and lead to variable‐density flows that control subsurface processes such as seawater intrusion, contaminant transport, and geologic carbon sequestration. In nature, fractures have dip angles relative to gravity, and density effects are maximized in vertical fractures. However, most studies on flow and transport through fractures are often limited to horizontal fractures. Here, we study the mixing and transport of variable‐density fluids in vertical fractures by combining three‐dimensional (3D) pore‐scale numerical simulations and visual laboratory experiments. Two miscible fluids with different densities are injected through two inlets at the bottom of a fracture and exit from an outlet at the top of the fracture. Laboratory experiments show the emergence of an unstable focused flow path, which we term a “runlet.” We successfully reproduce the unstable runlet using 3D numerical simulations and elucidate the underlying mechanisms triggering the runlet. Dimensionless number analysis shows that the runlet instability arises due to the Rayleigh‐Taylor instability (RTI), and flow topology analysis is applied to identify 3D vortices that are caused by the RTI. Even under laminar flow regimes, fluid inertia is shown to control the runlet instability by affecting the size and movement of vortices. Finally, we confirm the emergence of a runlet in rough‐walled fractures. Since a runlet dramatically affects fluid distribution, residence time, and mixing, the findings in this study have direct implications for the management of groundwater resources and subsurface applications.
Environmental Sciences & Ecology↗
H-Atom Assignment and Sb–O Bonding of [Mes 3 SbOH][O 3 SPh] Confirmed by Neutron Diffraction, Multipole Modeling, and Hirshfeld Atom Refinement
Neutron wavelength-resolved Laue diffraction experiments permit accurate refinement of the H-atom positions and anisotropic displacement parameters of [Mes 3 SbOH][O 3 SPh]. A multipole-based charge density refinement and a topological analysis of the refined electron density were also performed. Hirshfeld atom refinement (HAR) recovers the neutron-determined H-atom parameters, and the quantum-mechanical electron density used in HAR recovers the electron density topology from the refined multipole model. We report these results confirm that [Mes 3 SbOH][O 3 SPh] does indeed feature a hydroxystibonium cation with a nominal Sb–O single bond and not a stibine oxide with an Sb=O/Sb + –O – bond.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Gene network centrality analysis identifies key regulators coordinating day-night metabolic transitions in Synechococcus elongatus PCC 7942 despite limited accuracy in predicting direct regulator-gene interactions
Synechococcus elongatus PCC 7942 is a model organism for studying circadian regulation and bioproduction, where precise temporal control of metabolism significantly impacts photosynthetic efficiency and CO 2 -to-bioproduct conversion. Despite extensive research on core clock components, our understanding of the broader regulatory network orchestrating genome-wide metabolic transitions remains incomplete. We address this gap by applying machine learning tools and network analysis to investigate the transcriptional architecture governing circadian-controlled gene expression. While our approach showed moderate accuracy in predicting individual transcription factor-gene interactions - a common challenge with real expression data - network-level topological analysis successfully revealed the organizational principles of circadian regulation. Our analysis identified distinct regulatory modules coordinating day-night metabolic transitions, with photosynthesis and carbon/nitrogen metabolism controlled by day-phase regulators, while nighttime modules orchestrate glycogen mobilization and redox metabolism. Through network centrality analysis, we identified potentially significant but previously understudied transcriptional regulators: HimA as a putative DNA architecture regulator, and TetR and SrrB as potential coordinators of nighttime metabolism, working alongside established global regulators RpaA and RpaB. This work demonstrates how network-level analysis can extract biologically meaningful insights despite limitations in predicting direct regulatory interactions. The regulatory principles uncovered here advance our understanding of how cyanobacteria coordinate complex metabolic transitions and may inform metabolic engineering strategies for enhanced photosynthetic bioproduction from CO 2 .
59 BASIC BIOLOGICAL SCIENCES↗
Scalar Field Comparison with Topological Descriptors: Properties and Applications for Scientific Visualization
In topological data analysis and visualization, topological descriptors such as persistence diagrams, merge trees, contour trees, Reeb graphs, and Morse–Smale complexes play an essential role in capturing the shape of scalar field data. Herein we present a state–of–the–art report on scalar field comparison using topological descriptors. We provide a taxonomy of existing approaches based on visualization tasks associated with three categories of data: single fields, time–varying fields, and ensembles. These tasks include symmetry detection, periodicity detection, key event/feature detection, feature tracking, clustering, and structure statistics. Our main contributions include the formulation of a set of desirable mathematical and computational properties of comparative measures, and the classification of visualization tasks and applications that are enabled by these measures.
97 MATHEMATICS AND COMPUTING↗
Development of a metamodelling framework for building energy models with application to fifth-generation district heating and cooling networks
Fully defined physics-based building energy models can accurately represent building systems; however, generating models based on high-level parameters is time consuming and simulation time of complex models can be slow. This article discusses the development of a Metamodelling Framework to create metamodels from a building energy modelling dataset. The framework generates metamodels using either linear regression, random forests, or support vector regressions. A fifth-generation district heating and cooling system analysis use case was used to motivate the development of the framework. The use case required quick and accurate representations of annual building loads reported hourly. Typical annual building modelling approaches can result in a runtime of 10 min. The metamodels runtime was reduced to less than 10 s to load and run an annual simulation with user-defined covariates. The results of the metamodel performance and an abbreviated topology analysis based on the motivating use case will be presented.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Intermolecular Interactions in Direct Air Capture Materials: Insights from Charge Density Analysis
Direct air capture (DAC) materials enable the removal of CO 2 from the atmosphere, but improving their efficiency requires a detailed understanding of the intermolecular interactions that govern CO 2 sorption and release. Here, we present an experimental electron density study of methylglyoxal-bis(iminoguanidine) (MGBIG), a promising DAC material, using high-resolution X-ray and neutron diffraction data combined with quantum crystallographic analysis. This approach bridges theoretical and experimental data by quantifying electron density distributions and revealing how hydrogen bonds stabilize CO 2 -derived carbonate phases and may influence the desorption behavior. We identify distinct hydrogen-bonding environments in two crystalline carbonate phases: P1, a transient kinetic product, and P3, a thermodynamically stable phase. Multipolar refinement and electrostatic potential and multipole moment calculations precisely map electron density distributions, revealing key hydrogen bonds involved in CO 2 capture. Topological analysis of electron density highlights a cooperative hydrogen-bonding network in the thermodynamically favored P3 phase, where enhanced electron density delocalization and water-mediated interactions contribute to a more stable lattice. Energetic analyses confirm that stronger hydrogen bonding networks enhance the stability of P3 with a binding energy of −607.0 kJ/mol and greater lattice stability (−847.3 kJ/mol) compared to P1 (−302.5 and −571.0 kJ/mol, respectively). Electrostatic potential maps further illustrate polarization patterns that may influence the stability of the binding of CO 2 and release conditions. These findings establish a direct experimental framework for linking electron density distributions to intermolecular interactions in DAC materials, providing a rational design strategy for optimizing sorbents with improved CO 2 capture efficiency and reduced energy demands.
Electron density↗
Reactions of concerted decomposition of cyclic molecules, as studied by the quantum chemistry methods and parabolic model
Reactions of concerted decomposition of cyclic molecules (Diels—Alder retro-reactions) were studied using quantum chemical modeling and the method of intersecting parabolas (M3IP model). According to results of quantum chemical calculations and topological analysis of transition states (TSs) of five concerted decomposition reactions of cyclic molecules, all TSs represent six-membered rings in which the bonds being cleaved are weak covalent ones. The presence of ring heteroatoms (N, O, or S) has a strong impact on the TS geometry and on the energy characteristics of the reactions. The M3IP model was used to process the experimental results to develop an algorithm for calculating the activation energies (E) of the reactions in question and the classical potential barriers to thermally neutral reaction (E{sub e}{sup 0}). Factors influencing the energies E were determined and assessed. These include the enthalpy of reaction, substituents, ring heteroatoms, the force constants of bonds, and the bond dissociation energies. A comparison of the activation energies E and the enthalpies of reaction ΔH obtained from the M3IP and density functional B3LYP/6-311++G** calculations revealed good agreement between them.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Comparative Study of Solvatomorphs of Stryker's Reagent Using MicroED and Quantum Mechanics
Abstract The atomic position of hydrogen atoms in metal hydrides has been a long‐standing structural question in inorganic chemistry given that hydride delivery is integral to diverse chemical reactions. Microcrystal electron diffraction (microED), with it's increased sensitivity toward hydrogen atoms relative to X‐ray diffraction, offers a potential path to addressing this challenge. Herein, the first microED study of Stryker's reagent is reported, resulting in the structure of a new benzene solvate. Improved accuracy for hydrogen atom positions was obtained via a quantum crystallography (QCr) approach, Hirshfeld atom refinement (HAR). Structural and topological analysis supports edge bridging hydrides in the microED structure of a THF solvate form, consistent with previous diffraction studies. Interestingly, analysis of a new benzene solvate, discovered in this study, is consistent with mixed edge‐ and face‐bridging hydrides.
Jha, Kunal K. [Division of Chemistry &, Chemica↗
The role of deviatoric stress and dislocations on the α to ω phase transformation in Ti
Under extreme conditions, α-Ti becomes unstable and transforms either into β-Ti at high temperature or into ω-Ti at high pressure. In what concerns the α to ω phase transformation (PT), there has been a wide range of experimentally reported transition pressures from approximately 2 to 15 GPa at room temperature. Deviatoric stresses and internal defects are often assumed to be the root cause of this variation. Here, in this study, these postulates are revisited using both continuum mechanics and molecular dynamics (MD) simulations. First, a simple continuum model, assuming linear elasticity and isotropic plasticity, is developed to describe the effects of applied stress and dislocations on the stability of an ω nucleus in an infinite α domain. Second, a new MD simulation method is developed to generate an ω nucleus in the α domain utilizing the displacement field identified from the topological analysis. Results from MD simulations show that despite the fact that phase diagrams typically delineate the limits between two phases in terms of only P and T, deviatoric stress promotes the α to ω phase transformation by reducing the critical radius above which an ω nucleus is stable. Furthermore, the required deviatoric stress to nucleate and stabilize a nanoscale ω nucleus is likely emanating from the internal stress of defects such as dislocations. The MD-informed micromechanics models are used to identify favorable configurations where dislocations help favor the α to ω transformation. These configurations show that the interaction with a basal or prismatic dislocation reduces the critical radius of a ω nucleus by about 10 or 16 %, respectively. In addition, prismatic edge dislocations are found to promote the growth of ω nucleus when interacting with the ($\bar{1}$$\bar{1}$20) α //(0001) ω interface. Importantly, a simple model of the arrival of dislocation at an ω nucleus suggests that PT does not necessarily require a pile-up to be present but could alternatively be mediated by a constant rapid flow of dislocations.
36 MATERIALS SCIENCE↗
Intricate Genetic Programs Controlling Dormancy in Mycobacterium tuberculosis
Mycobacterium tuberculosis (MTB) displays the remarkable ability to transition in and out of dormancy, a hallmark of the pathogen’s capacity to evade the immune system and exploit susceptible individuals. Uncovering the gene regulatory programs that underlie the phenotypic shifts in MTB during disease latency and reactivation has posed a challenge. We develop an experimental system to precisely control dissolved oxygen levels in MTB cultures in order to capture the transcriptional events that unfold as MTB transitions into and out of hypoxia-induced dormancy. Using a comprehensive genome-wide transcription factor binding map and insights from network topology analysis, we identify regulatory circuits that deterministically drive sequential transitions across six transcriptionally and functionally distinct states encompassing more than three-fifths of the MTB genome. The architecture of the genetic programs explains the transcriptional dynamics underlying synchronous entry of cells into a dormant state that is primed to infect the host upon encountering favorable conditions.
59 BASIC BIOLOGICAL SCIENCES↗