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Articles 61 - 90 of 7311

Full-Text Articles in Physical Sciences and Mathematics

Quantum Scattering Of Hc5n And Para-H2 On A New Potential Energy Surface, Shan Gao, François Lique, Ernesto Quintas-Sánchez, Richard Dawes, Jérôme Loreau Apr 2026

Quantum Scattering Of Hc5n And Para-H2 On A New Potential Energy Surface, Shan Gao, François Lique, Ernesto Quintas-Sánchez, Richard Dawes, Jérôme Loreau

Chemistry Faculty Research & Creative Works

In the interstellar medium (ISM), non-local thermodynamic equilibrium situations are common due to low density, and one needs to consider the effect of molecular collisions in order to interpret the observations. Among the species detected in the ISM, cyanopolyynes, with the general molecular formula HC2n+1N (n = 1, 2, …), are characterized by large dipole moments and small rotational constants and constitute an indispensable class of candidates for the sensitive tracers of local density and temperature. We present a study of the collisional (de-) excitation of HC5N by para-H2 (p-H2) in its ground …


Electroenzymatic Cascades For Nitrogen Upgrading: Beyond Ammonia Towards Value-Added Nitrogen Chemicals, Rohit G. Jadhav, Vamshi Krishna Kamaja, Wassim El Housseini, Monica Brachi, Shelley D. Minteer Apr 2026

Electroenzymatic Cascades For Nitrogen Upgrading: Beyond Ammonia Towards Value-Added Nitrogen Chemicals, Rohit G. Jadhav, Vamshi Krishna Kamaja, Wassim El Housseini, Monica Brachi, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

The global transition toward sustainable chemical manufacturing demands technologies that leverage natural carbon and nitrogen cycles while minimizing reliance on sacrificial reagents and fossil resources. These biogeochemical cycles are fundamental to life, and enzymes catalyze many of their key transformations. Bio electrochemical, specifically electroenzymatic, systems offer a promising route to sustainable synthesis by enabling selective redox transformations powered by electricity. However, whereas carbon-cycle enzymes are now well established in bio electrochemical synthesis, enzymes from the nitrogen cycle remain comparatively underexplored. Moreover, the nitrogen cycle alone does not access many value-added nitrogen-containing products, which require additional C-N bond formation and organic …


Characterizing User-Reported Risks Across Llm Chatbots, Lingyao Li, Renkai Ma, Zhaoqian Xue, Junjie Xiong Apr 2026

Characterizing User-Reported Risks Across Llm Chatbots, Lingyao Li, Renkai Ma, Zhaoqian Xue, Junjie Xiong

Computer Science Faculty Research & Creative Works

As Large Language Models (LLMs) become increasingly integral to daily life, users are engaging with multiple LLM chatbots for various needs; however, prior research on LLM risks often remains lab-based or focuses on single LLMs like ChatGPT or singular risks like privacy. To gain a multi-risk, cross-chatbot understanding of user experiences, we analyze Reddit discussions around seven major LLM chatbots using the NIST AI Risk Management Framework. We find that user-reported risks are unevenly distributed and chatbot-specific: ChatGPT is associated with safety and fairness concerns, Gemini with privacy, and Claude with security and resilience. Less frequent risks, such as explainability …


Synthesis And Hydrothermal Evaluation Of Poly(Styrene Phosphonate) For Conformance Control In Geothermal Reservoirs, Sara Mccauley Apr 2026

Synthesis And Hydrothermal Evaluation Of Poly(Styrene Phosphonate) For Conformance Control In Geothermal Reservoirs, Sara Mccauley

Miners Solving for Tomorrow Research Conference

As atmospheric carbon dioxide levels continue to rise, geothermal energy has emerged as a promising energy alternative to fossil fuels. A barrier to widespread implementation and energy production efficiency is macro-heterogeneity of the rock matrix. Cracks, void spaces, and flow conduits divert fluid flow away from unswept portions of the geothermal reservoir and can cause cooling of the reservoir. Flow heterogeneity has been treated in oil reservoirs by injecting hydrogel particles that travel preferentially to ultra-high permeability zones and selectively block fluid flow in these regions. We are applying polymer hydrogels that withstand hydrothermal conditions of 225 up to 275°C …


Adaptive Parallel Downloader For Large Genomic Datasets, Rasman Mubtasim Swargo Apr 2026

Adaptive Parallel Downloader For Large Genomic Datasets, Rasman Mubtasim Swargo

Miners Solving for Tomorrow Research Conference

Modern next-generation sequencing (NGS) projects routinely generate terabytes of data that researchers download from public repositories such as SRA and ENA. Existing download tools typically employ static concurrency settings, leading to inefficient bandwidth utilization and prolonged download times under dynamic network conditions. We introduce FastBioDL, a parallel downloader for large biological datasets with an adaptive concurrency controller. FastBioDL frames downloading as an online optimization problem, using a utility function and gradient descent to adjust the number of concurrent socket streams during runtime. This approach maximizes throughput while minimizing resource overhead. Evaluations on public genomic datasets show that FastBioDL achieves up …


Harnessing Wavefront Shaping Control For Sensing Applications, Pablo Jara Apr 2026

Harnessing Wavefront Shaping Control For Sensing Applications, Pablo Jara

Miners Solving for Tomorrow Research Conference

Diffuse optical tomography (DOT) and functional near-infrared spectroscopy (fNIRS) enable deep, non-invasive sensing in biological tissue but are fundamentally limited by the photon budget - most injected light is lost to scattering before reaching the detector. Wavefront shaping (WFS) can enhance signal strength inside scattering media via interference, but the conventional diffusion-based sensitivity model breaks down under coherent illumination. We develop a microscopic theory of optical sensitivity that captures interference effects neglected by diffusion theory. We prove analytically that the microscopic and diffusive descriptions coincide under random illumination and identify WFS strategies that enhance sensitivity beyond this limit. The maximum …


Introducing Gridtrees For Streaming, Scalable Hierarchical Data Visualization, Nathan Tibbetts Apr 2026

Introducing Gridtrees For Streaming, Scalable Hierarchical Data Visualization, Nathan Tibbetts

Miners Solving for Tomorrow Research Conference

File browsing in the consumer sphere has seen very little advancement in recent years, although attempts have been made to improve upon it. With the goal of multi-level visual file browsing in mind, we present a prototype GridTree, a dynamic, recursive, stable, spatial layout data structure based on subdividing grids, represented as a hierarchy of maps whose granularity increases with depth. We motivate this work with characteristics we have identified as important for viability of a multi-level file-browser, which have become our design goals. We touch on the underlying logic of a GridTree and identify its complexity. We briefly discuss …


Dispersive Shock And Rogue Waves In Two-Dimensional Quantum Droplets, Farhana Bristy Apr 2026

Dispersive Shock And Rogue Waves In Two-Dimensional Quantum Droplets, Farhana Bristy

Miners Solving for Tomorrow Research Conference

Quantum droplets, are liquid type configurations stabilized by the balance between attractive mean-field interactions and repulsive quantum fluctuations. They provide highly flexible platforms for the quantum simulation of hydrodynamic phenomena using ultracold gases. Here, we explore the nonlinear quantum dynamics of two-dimensional quantum droplets under Riemann initial conditions. The steepness of the latter facilitates the emergence of radially symmetric dispersive shock waves (DSWs) when quantum fluctuations dominate. In particular, the ensuing DSWs travel from the potential edges toward the center where they collide and through their interference high amplitude spatially localized rogue wave structures emerge. In contrast, tuning the interactions …


Thermal Mirage: Towards Robust Thermal Perception Via Gan-Guided Diffusion, Nuzaer Omar Apr 2026

Thermal Mirage: Towards Robust Thermal Perception Via Gan-Guided Diffusion, Nuzaer Omar

Miners Solving for Tomorrow Research Conference

Thermal object detection systems are critical for safety sensitive applications due to their reliability under adverse conditions. However, existing robustness evaluations in thermal domain primarily focuses on physical or sensor-level perturbations, overlooking vulnerabilities from semantically realistic scene and object manipulations. We introduce Thermal Mirage, a generative framework that leverages GAN-guided diffusion to expose weaknesses in thermal detectors through controlled object and context level perturbations. Our approach learns class-conditional thermal priors via a GAN and uses diffusion to transform object appearances into ambiguous or low-saliency patterns. Simultaneously, a context module degrades scene conditions by simulating harsher night environments. Integrated with a …


Distributed Control Plane For Cross-Silo Federated Learning, Rabin Pandey Apr 2026

Distributed Control Plane For Cross-Silo Federated Learning, Rabin Pandey

Miners Solving for Tomorrow Research Conference

Cross-silo federated learning (FL) trains shared models across geographically distributed institutions without centralizing raw data, but its reliance on wide-area networks makes round completion time highly sensitive to heterogeneous link conditions, congestion, and straggler clients. Existing SDN-based FL frameworks address this through centralized traffic engineering, an approach that breaks down when silos span independent administrative domains where no single entity can maintain complete, timely network knowledge. We replace the centralized control plane with a fully distributed overlay in which each silo gateway operates as an equal peer, continuously probing local links, exchanging EWMA-smoothed metrics via bounded gossip, and computing least-cost …


Transition Metal Chalcogenide As Multifunctional Biosenser To Detect Neurochemicals, Amitav Sen Apr 2026

Transition Metal Chalcogenide As Multifunctional Biosenser To Detect Neurochemicals, Amitav Sen

Miners Solving for Tomorrow Research Conference

The development of highly sensitive real-time sensing platforms for selectively detecting dopamine (DA) and norepinephrine (NE) is of significant clinical importance since these are closely associated with several neurodegenerative disorders. Herein, we report copper telluride (Cu₂Te) nanostructure as a bifunctional electrocatalyst for the simultaneous detection of dopamine and norepinephrine. Cu₂Te exhibits excellent electrocatalytic activity toward both DA and NE oxidation, as demonstrated by detailed electrochemical measurements. High sensitivities of 24 and 40 µA cm⁻² µM⁻¹ for DA and NE, respectively, were obtained with a wide linear detection range of 10–200 nM and low limit of detection (LOD), 31 nM for …


Robust Federated Learning With Strategic Adversaries, Manoj Twarakavi Apr 2026

Robust Federated Learning With Strategic Adversaries, Manoj Twarakavi

Miners Solving for Tomorrow Research Conference

Federated Learning (FL) leverages the intelligence of untrusted distributed devices through collaborative training. This makes the training process susceptible to malicious behavior. Existing defense mechanisms largely consider an adversary who attacks a proactive FL server without any adaptability. However, they overlook the presence of a strategic adversary. To address this challenge, our work proposes a Robust Game-theoretic framework where the adversary is both strategic and is equipped with the capability of performing large-scale poisoning attacks.


Variational Data Assimilation With Steepest Descent Method For Coupled Time-Dependent Stokes-Darcy Model With Bjsj Interface Condition, Yafang Hei Apr 2026

Variational Data Assimilation With Steepest Descent Method For Coupled Time-Dependent Stokes-Darcy Model With Bjsj Interface Condition, Yafang Hei

Miners Solving for Tomorrow Research Conference

Variational data assimilation (VDA) determines the initial condition of a dynamical system by minimizing the mismatch between model predictions and observed data. This work studies VDA for the time-dependent Stokes–Darcy system with the BJSJ interface condition. The problem is formulated as a PDE-constrained optimization problem, and the first-order optimality system is derived using the Gâteaux derivative and adjoint variables. A steepest descent method is applied for efficient computation. Spatial and temporal discretizations are carried out using the finite element method and backward Euler scheme, respectively. Numerical results confirm accuracy and convergence.


Controlled Gelation Of Co₂-Resistant Polymer Systems For Improved Conformance In Co₂-Eor, Maryam Sharifi Paroushi Apr 2026

Controlled Gelation Of Co₂-Resistant Polymer Systems For Improved Conformance In Co₂-Eor, Maryam Sharifi Paroushi

Miners Solving for Tomorrow Research Conference

This presentation introduces a CO₂-resistant hydrogel developed to control fluid movement and improve CO₂ injection performance in subsurface reservoirs for Enhanced Oil Recovery (EOR) and Carbon Capture and Storage (CCS). Conventional polymer gels often lose strength in CO₂-rich environments, resulting in weak plugging, early breakdown, and ineffective flow control. To address this limitation, a sulfonated HPAM-based gel system crosslinked with chromium was developed. The effects of polymer concentration, molecular weight, crosslinker ratio, ionic strength, and pH were investigated to better understand gelation behavior and performance. The formulation exhibited controlled gelation, strong resistance to temperature and CO₂, and minimal shrinkage over …


Robustness Of Fuzzy Artmap To Adversarial Attacks And Progressive Adversarial Training For Streaming Learning, Shane Cairns Apr 2026

Robustness Of Fuzzy Artmap To Adversarial Attacks And Progressive Adversarial Training For Streaming Learning, Shane Cairns

Miners Solving for Tomorrow Research Conference

Incremental learners deployed on streaming data must remain robust to evolving adversarial perturbations, yet most adversarial-robustness studies assume offline multi-epoch training with repeated access to historical data. We investigate adversarial robustness in Fuzzy ARTMAP, a prototype-based Adaptive Resonance Theory model that supports single-pass learning without replay. We propose WB-Softmax, a differentiable relaxation that aggregates category-level activations into class-level scores for gradient-based attacks. WB-Softmax PGD achieves 89–100% attack success on vanilla models, exceeding transfer and query-based baselines. We then study adversarial training under true streaming constraints by comparing offline versus online adversarial example generation and standard versus selective updates. Offline adversarial …


Direct Energy Cascade Of 2d Quantum Turbulence In Supersolids, Lukas Farthing Apr 2026

Direct Energy Cascade Of 2d Quantum Turbulence In Supersolids, Lukas Farthing

Miners Solving for Tomorrow Research Conference

The non-equilibrium turbulent response of periodically driven three-dimensional ultracold dipolar gases is induced by an external time-dependent ring potential. To model this system and monitor its non-equilibrium quantum dynamics, we invoke an extended Gross-Pitaevskii framework containing the first-order quantum correction to the mean-field energy functional. The shape of the external perturbing potential is chosen to trigger angular roton excitations, driving the supersolid configuration out of equilibrium and attaining a turbulent state. Following the generation of shallow vortical defects in the bulk, a direct cascade front manifests, transporting energy from larger to smaller length scales. This leads to a non-equilibrium quasi-steady …


Cytokinesis And Dbf2, Katharine Gray Apr 2026

Cytokinesis And Dbf2, Katharine Gray

Miners Solving for Tomorrow Research Conference

The Mitotic Exit Network (MEN) is a signaling pathway that allows a dividing cell to exit cytokinesis. Dbf2 is a MEN protein kinase in yeast, which provides a simplified model for studying this pathway. By altering Dbf2’s activity through phosphorylation mutants, its effect on cytokinesis can be studied. Transformed cells with a mutant and degron Dbf2 allele are prompted to destroy the degron Dbf2 protein, leaving only mutated Dbf2 behind. This allows for clear analysis of the effect of the phosphorylation mutant on division. Fluorescence microscopy can be used to visualise this degradation, and the impact on actin ring formation …


Vortex Generation In Dipolar Supersolids, Jacob Harl Apr 2026

Vortex Generation In Dipolar Supersolids, Jacob Harl

Miners Solving for Tomorrow Research Conference

Ultracold atomic gases offer highly tunable platforms for exploring complex quantum many-body phenomena. In addition, dipolar quantum gases of magnetic atoms featuring long-range anisotropic interactions are exquisite systems for realizing exotic phases-of-matter in an experimentally controlled way. A prototypical example is the supersolid state which simultaneously exhibits frictionless flow of superfuids and crystalline density modulation of solids. In this realm, we investigate the dynamical generation of vortex topological defects by imprinting a suitable phase jump in quasi-two-dimensional dipolar supersolids. This protocol enables the nucleation of a dark soliton which consecutively becomes unstable via the eponymous snake instability due to its …


Elucidating Complex H Behavior In Amorphous Oxide Semiconductors By Machine Learning, Lucas Ethington Apr 2026

Elucidating Complex H Behavior In Amorphous Oxide Semiconductors By Machine Learning, Lucas Ethington

Miners Solving for Tomorrow Research Conference

In this project, the disordered oxide structures will be mapped by a machine-learning algorithm (e.g., HDBSCAN) to identify characteristic behaviors of the proton across different material densities and defect types. This should help identify the under-coordinated, highly distorted, weakly-bonded, and dynamically unstable atoms to predict the most probable H locations. This fast and accurate prediction of energetically favorable H distribution will enable a reliable and fast screening of a large number of AOSs with variable cation and/or anion compositions. The approach will help find AOSs with suppressed numbers of M-OH defects (that form deep electron traps, limiting the number of …


The Structure Of Amorphous Alox And Its Role In H Distribution And Dynamics, Lana Herkenhoff Apr 2026

The Structure Of Amorphous Alox And Its Role In H Distribution And Dynamics, Lana Herkenhoff

Miners Solving for Tomorrow Research Conference

Hydrogen is known to be the culprit of electron decoherence in Josephson junctions, greatly affecting the performance of superconducting quantum circuits. For Al/AlOx interfaces, the challenge is two-fold: 1) similar Al-Al and Al-H bond strength promotes bond switching and, hence, facilitates vigorous H motion; whereas 2) oxygen has only a slight preference to form Al-O rather than H-O bond, implying that (meta)stable Al--O-H are likely to occur, especially in a disordered oxide. In this project, ab initio molecular dynamics (MD) simulations are employed to generate the atomistic models of Al2O3-x with oxygen vacancy defects and to quantify the H diffusion, …


Wheel-Spoke Encoding: A Product Quantization-Compatible Radial Encoding Scheme For Convex Polygonal Data, Maris Reinkemeyer Apr 2026

Wheel-Spoke Encoding: A Product Quantization-Compatible Radial Encoding Scheme For Convex Polygonal Data, Maris Reinkemeyer

Miners Solving for Tomorrow Research Conference

Product quantization has historically been unapplied to GIS datasets, likely due to a mismatch between quantization’s input precondition of fixed, equal length vectors and GIS data’s inherent variability in the number of data points. Therefore, any quantization-compatible encoding method must operate independently of the data points within GIS records. The challenge is to balance the guarantee of producing fixed, equal length vectors with the preservation of semantic meaning present in the raw data. Here, we develop a radial polygon encoding method that achieves this balance while providing acceptable recall in a time complexity of O(nrv), where n is the number …


Dynamical Transition From A Two-Dimensional Soliton To A Rogue Wave In Quantum Droplets, Punit Sesha Sai Turlapati Apr 2026

Dynamical Transition From A Two-Dimensional Soliton To A Rogue Wave In Quantum Droplets, Punit Sesha Sai Turlapati

Miners Solving for Tomorrow Research Conference

We investigate the nonequilibrium dynamics of two-dimensional quantum droplets: ultracold self-bound many-body states stabilized by the interplay of mean-field attractive interactions and repulsive quantum fluctuations. Flat-top ground state droplets are subject to an external potential, an attractive well and a repulsive barrier. Under the influence of the attractive well, we observe signatures of a Townes soliton formation, which for increasing strength of the well transitions into a two-dimensional rogue wave structure, a time-periodic highly localized configuration with amplitude three times larger than the background. The barrier instead favors a dynamical splitting of the droplet. We have developed a parallelized simulation …


Analysis Of Autonomous Vehicle Survivability To 5g Communication Errors, Sydney Clark Apr 2026

Analysis Of Autonomous Vehicle Survivability To 5g Communication Errors, Sydney Clark

Miners Solving for Tomorrow Research Conference

Autonomous vehicles rely on low-latency, high-reliability data exchange for real-time perception and control. Disruptions such as packet loss, latency variation, protocol-level errors, and malicious interference can pose significant safety risks to both passengers and surrounding environments. This project aims to evaluate, quantify, and predict the survivability of autonomous vehicle systems to communication errors, with focus on 5G network environments. The impact of these communication impairments on vehicle stability and control will be investigated through high-fidelity cyber-physical simulation of the vehicle and its surrounding environment. Experiments designed to capture varying network conditions will be used to assess a broad range of …


A Wearable Mxene-Based Sweat Sensor For Real-Time Monitoring Of Inflammatory Biomarkers, Ariel Pilger Apr 2026

A Wearable Mxene-Based Sweat Sensor For Real-Time Monitoring Of Inflammatory Biomarkers, Ariel Pilger

Miners Solving for Tomorrow Research Conference

Many conventional biosensing approaches rely on invasive sampling or bulky benchtop instrumentation, limiting their use in continuous and portable applications. This project focuses on the development of wearable sweat-based biosensors that enable non-invasive, continuous, and portable monitoring of physical, chemical, and biological markers. The system will be designed to target markers present in sweat and transduce the biochemical interactions into measurable electrical signals. These signals will be processed through integrated electronics to produce clear, interpretable outputs for users and medical professionals. Supporting circuitry including filters, amplifiers, and an independent power supply will be implemented as necessary to ensure signal accuracy, …


Lay Summarization For Medical Patents, Manav Raja Vinotha Apr 2026

Lay Summarization For Medical Patents, Manav Raja Vinotha

Miners Solving for Tomorrow Research Conference

Technical documents, such as medical patents, are often inaccessible to non-expert audiences due to specialized terminology. This paper presents a multi-agent system for automated lay summarization that optimizes both quality and computational efficiency through strategic task decomposition. The proposed pipeline utilizes four specialized stages: autonomous medical entity retrieval from the Unified Medical Language System (UMLS), context distillation into lay conceptualizations, and a structured writer-critic loop for iterative refinement. By distributing cognitive load across specialized agents, this architecture effectively leverages smaller, cost-effective language models while maintaining the performance of SOTA LLMs. Evaluated against single-agent baselines using an LLM as a Judge …


The Effects Of Preventing Dephosphorylation Of Lqg1 On Cytokinesis, Jenna Mueller Apr 2026

The Effects Of Preventing Dephosphorylation Of Lqg1 On Cytokinesis, Jenna Mueller

Miners Solving for Tomorrow Research Conference

Iqg1 plays crucial roles in cytokinesis, including the assembly, contraction, and disassembly of the actomyosin ring, as well as the coordination of contraction and septation. Given that cytokinesis must occur post-mitosis, Iqg1 is regulated by the cell cycle. This study explores hypotheses regarding Iqg1 regulation: it’s binding to action is negatively influenced by the cyclin-dependent kinase (CDK) Cdc28 and positively influenced by dephosphorylation via Cdc14. Newly developed yeast degron tagged strains allow for rapid depletion of specific proteins. Iqg1 mutations that alter serine to threonine, which allows phosphorylation but not dephosphorylation, in the degron strain allow testing of mutant phenotypes. …


The Stability Study Of Dna-Polymer Hybrids For Nanotechnology Applications, Ethan Kuehn, Milan Jebaraj Apr 2026

The Stability Study Of Dna-Polymer Hybrids For Nanotechnology Applications, Ethan Kuehn, Milan Jebaraj

Miners Solving for Tomorrow Research Conference

DNA nanostructures have garnered increasing interest in their application as drug delivery vehicles. However, DNA is susceptible to degradation under physiological conditions. To remedy this, we have devised a novel method to coat DNA nanostructures with the polysaccharide chitosan (a natural derivative of chitin). Chitosan binds to DNA electrostatically and inhibits nuclease activity that would normally degrade DNA in a physiological environment. We used both agarose gel electrophoresis (AGE) and atomic force microscopy (AFM) to determine the stability of DNA before and after immersion in a simulated biological environment. Physiological conditions were mimicked by incubating the DNA in cell culture …


Asphalt Pavement Rejuvenation Investigated By Nuclear Magnetic Resonance Relaxometry, Catherine Skaggs Apr 2026

Asphalt Pavement Rejuvenation Investigated By Nuclear Magnetic Resonance Relaxometry, Catherine Skaggs

Miners Solving for Tomorrow Research Conference

Asphalt is a relatively inexpensive material commonly used for road pavements; however, asphalt ages from exposure to oxygen and UV radiation, leading to loss of elasticity, which leads to cracks and potholes. To slow or reverse asphalt aging, pavement preservation treatments are in use. It’s unclear whether these treatments truly rejuvenate the pavement structure or merely offer a short-term benefit. Nuclear Magnetic Resonance (NMR) relaxometry is an analytical technique that uses the recovery of excited nuclear magnetization as a parameter to gain insights into molecular environments. Recovery-time distributions gathered from asphalt materials show differences between regular and rejuvenated asphalt samples, …


The Kaczmarz Algorithm In Hilbert C∗-Modules, Daniel Alpay, Chad Berner, Eric S. Weber Apr 2026

The Kaczmarz Algorithm In Hilbert C∗-Modules, Daniel Alpay, Chad Berner, Eric S. Weber

Mathematics and Statistics Faculty Research & Creative Works

The Kaczmarz algorithm in Hilbert spaces is a classical iterative method for stably recovering vectors from inner product data. In this paper, we extend the algorithm to the setting of Hilbert C∗-modules and establish analogues of its effectiveness in both finite-dimensional and stationary cases. Consequently, we demonstrate that continuous families of elements in a Hilbert space can be uniformly recovered using the Kaczmarz algorithm. Additionally, we develop a normalized Cauchy transform for continuous families of measures and use it to provide sufficient conditions under which standard frames in Hilbert C(X)-modules can be generated by the Kaczmarz algorithm and …


A Fully Discrete Decoupled Scheme And Applications For Non-Isothermal Two-Phase Flow Model With Different Viscosities And Thermal Diffusivities, Jian Li, Chunhao Chen, Xiaoyong Chen, Rui Li, Xiaoming He Apr 2026

A Fully Discrete Decoupled Scheme And Applications For Non-Isothermal Two-Phase Flow Model With Different Viscosities And Thermal Diffusivities, Jian Li, Chunhao Chen, Xiaoyong Chen, Rui Li, Xiaoming He

Mathematics and Statistics Faculty Research & Creative Works

To study natural convection problems in two-phase flows, a non-isothermal two-phase flow model incorporating differential viscosities and thermal diffusivities is considered and analyzed via the phase-field method. This modeling framework involves the Multiphysics coupling of the Cahn-Hilliard phase field equations, heat transfer equation, and Navier-Stokes equations, resulting in a strongly nonlinear system. To efficiently solve the sophisticated system, we develop, analyze, and demonstrate a decoupled linear fully discrete scheme, which leverages the invariant energy quadratization strategy for the Cahn-Hilliard phase field system, the artificial compressibility method without artificial pressure boundary condition, an explicit-implicit treatment of nonlinear terms, and the addition …