arXiv subjects

Huaxiong Huang

Publications and source records attributed to Huaxiong Huang.

At least 19 recordsLinked to original sources

arXiv2026

Multiscale retinal flow on a spherical cap of varying aperture

Modelling retinal haemodynamics is crucial for understanding retinal microcirculation but is computationally demanding because it involves coupling between the vasculature and surrounding tissue across multiple scales. This computational burden has been substantially alleviated by a recent analytic solution on the planar disc that enables lumping the capillary bed and surrounding tissue into an effective resistor. However, that formulation treats the retina as a flat surface, whereas the retina is a curved surface with a finite anterior aperture. In this work, we develop a nontrivial and physiologically necessary extension to spherical-cap tissue domains with varying apertures, where surface curvature and finite-aperture boundaries complicate solving coupled Darcy equations on a curved manifold. Using a stereographic projection and a decoupling transformation, we derive an analytic solution for the capillary-tissue system on the spherical cap that represents flow in both the capillary bed and interstitial tissue more realistically while retaining the efficient resistor formulation, a key advantage of the planar-disc formulation. This solution is coupled to one-dimensional (1D) arteriolar and venular flows to obtain a multiscale description of retinal haemodynamics. Using a vasculature model designed to capture retinal vascular features, we show that the multiscale model's predictions are consistent with experimental data. We further explore aperture effects using both a fixed hemispherical vasculature and aperture-dependent vasculature. The aperture affects retinal haemodynamics mainly through changes in the constructed vasculature itself, whereas the surface-averaged pressures and relative terminal flow distributions remain nearly unchanged. This framework provides a foundation for studying retinal pathophysiology on more anatomically realistic domains.

physics.bio-ph↗

arXiv2026

Interpretable Fundus Image Classification via Ring-Based Retinal Vasculature Features

Retinal fundus photography is widely used for screening and monitoring ocular diseases, but many modern classification pipelines rely on deep latent representations and provide limited interpretability. This study develops an interpretable fundus image classification framework based on a ring-structured representation of the retinal vasculature centered on the optic disc. The method quantifies vessel geometry, color appearance, oxygenation-related vascular appearance, and vessel--background entropy within concentric retinal regions. These physiologically motivated descriptors are derived from vessel masks, image intensities, and optical-density measurements and aggregated across rings to capture spatial variation in vascular properties. Using only quantitative vascular descriptors, the proposed method achieved strong classification performance across three public fundus datasets. On HRF, it achieved 91.1\% accuracy using automatically generated vessel masks, matching RETFound, a vision transformer pretrained on large-scale retinal fundus image data, under the same evaluation setting. Additional analyses suggest that pretrained image models are sensitive to acquisition-related spatial cues, including fundus scale and retinal position within the field of view, as well as broader non-vessel image characteristics. This framework may support interpretable disease classification, quantitative retinal phenotyping, and retinal biomarker discovery without requiring large task-specific training datasets.

cs.CV↗

arXiv2026

AQP4 Regulates Gap-Dominated Glymphatic Clearance through Dynamic Gliovascular Coupling

Aquaporin-4 (AQP4) is enriched at perivascular astrocytic endfeet, and impaired AQP4 function or localization is associated with reduced glymphatic transport. However, mechanical models suggest that pressure-driven exchange across the gliovascular interface occurs predominantly through inter-endfoot gaps rather than directly through the AQP4-rich membrane. How AQP4 regulates clearance in such a gap-dominated system remains unclear. We develop a reduced arterial PVS-ECS-venous PVS model coupling vascular deformation, AQP4-mediated endfoot water exchange, dynamic inter-endfoot gap regulation, and tracer transport. Cardiac-like oscillations generate strong bidirectional exchange but weak net clearance, whereas asymmetric vasodilation enhances directional transport by suppressing recovery-phase backflow. Dynamic gap regulation provides additional hydraulic rectification. Although gap-mediated flux is much larger than direct AQP4-mediated flux, PVS-facing AQP4 substantially affects clearance by altering the pressure--volume balance and hence the driving force for the dominant gap pathway. Reducing PVS-facing AQP4 permeability, or redistributing AQP4 away from the PVS-facing membrane at fixed total conductance, reduces cumulative venous output by about 40\%. Aging-like changes in vascular motion, PVS mechanical coupling, and perivascular AQP4 enrichment further compound this impairment. These results suggest that AQP4 regulates gap-dominated glymphatic clearance through dynamic hydraulic coupling at the gliovascular interface.

physics.med-ph↗

arXiv2026

A novel multiscale modelling for the hemodynamics in retinal microcirculation with an analytic solution for the capillary-tissue coupled system

Mathematical modelling of the microcirculatory hemodynamics in the retina is an essential tool for understanding various diseases of the retina, yet remains challenging due to the multiscale nature of the retinal vasculature and its coupling to surrounding tissue. To address this, we develop a multiscale model that couples retinal vasculature across scales with interstitial tissue. Our model combines the one-dimensional (1D) model for arterioles and venules with the coupled Darcy equations for capillaries and tissue. The model uses an analytic solution for capillary-tissue coupled system that provides a simple interpretation of the results along with much faster computation. The analytic solution implies a dynamic coupling condition that links the capillary bed with upstream arteriolar and downstream venular flows. The model is mathematically robust, demonstrated through analysis of the solution's truncation error and convergence. Its predictive accuracy is validated against experimental data and other models, making it useful in interpreting experimental results. Finally, the role of various parameters in controlling retinal hemodynamics is explored.

physics.bio-ph↗

arXiv2025

TWLR: Text-Guided Weakly-Supervised Lesion Localization and Severity Regression for Explainable Diabetic Retinopathy Grading

Accurate medical image analysis can greatly assist clinical diagnosis, but its effectiveness relies on high-quality expert annotations Obtaining pixel-level labels for medical images, particularly fundus images, remains costly and time-consuming. Meanwhile, despite the success of deep learning in medical imaging, the lack of interpretability limits its clinical adoption. To address these challenges, we propose TWLR, a two-stage framework for interpretable diabetic retinopathy (DR) assessment. In the first stage, a vision-language model integrates domain-specific ophthalmological knowledge into text embeddings to jointly perform DR grading and lesion classification, effectively linking semantic medical concepts with visual features. The second stage introduces an iterative severity regression framework based on weakly-supervised semantic segmentation. Lesion saliency maps generated through iterative refinement direct a progressive inpainting mechanism that systematically eliminates pathological features, effectively downgrading disease severity toward healthier fundus appearances. Critically, this severity regression approach achieves dual benefits: accurate lesion localization without pixel-level supervision and providing an interpretable visualization of disease-to-healthy transformations. Experimental results on the FGADR, DDR, and a private dataset demonstrate that TWLR achieves competitive performance in both DR classification and lesion segmentation, offering a more explainable and annotation-efficient solution for automated retinal image analysis.

cs.CV↗

arXiv2025

Glymphatic Clearance in the Optic Nerve: A Multidomain Electro-osmostic Model

Effective metabolic waste clearance and maintaining ionic homeostasis are essential for the health and normal function of the central nervous system. To understand its mechanism and the role of fluid flow, we develop a multidomain electro-osmotic model of optic-nerve microcirculation that couples hydrostatic and osmotic fluid transport with electro-diffusive solute movement across axons, glia, the extracellular space, and arterial/venous/capillary perivascular spaces. Cerebrospinal fluid enters the optic nerve via the arterial parivascular space, passes both the glial and ECS before exiting through the venous parivascular space. Exchanges across astrocytic endfeet are essential and they occur in two distinct and coupled paths: through AQP4 on glial membranes and gaps between glial endfeet, thus establishing a mechanistic substrate for two modes of glymphatic transport, at rest and during stimulus-evoked perturbations. Parameter sweeps show that lowering AQP4-mediated fluid permeability or PVS permeability elevates pressure, suppresses radial exchange and slows clearance, effects most pronounced for solutes reliant on PVS V export. The model reproduces baseline and stimulus-evoked flow and demonstrates that PVS-mediated export is the primary clearance route for both small and moderate solutes. Small molecules clear faster because rapid ECS diffusion broadens their distribution and enhances ECS PVS exchange, whereas moderate species have low ECS diffusivity, depend on transendfoot transfer, and clear more slowly via PVS V convection. Our framework can also be used to explain the sleep-wake effect mechanistically: enlarging ECS volume or permeability increases transinterface flux and accelerates waste removal.

q-bio.CB↗

arXiv2025

Pump-driven droplet electrohydrodynamics: deformation, pinch-off and recoalescence

We investigate pump-driven droplet electrohydrodynamics with an emphasis on deformation, pinch-off, and recoalescence. A thermodynamically consistent phase-field framework is developed that couples Nernst--Planck--Poisson electrodiffusion with incompressible Navier--Stokes--Cahn--Hilliard flow, and incorporates interfacial ionic pumps as prescribed surface fluxes. In the pump-free baseline, applied fields merely polarise the droplet and deformation is negligible. By contrast, surface-localised pumping drives the accumulation of positive ions within the droplet, elevates the interior potential, and generates non-uniform electric fields. The resulting Lorentz stresses stretch and displace the droplet, thin interfacial necks, and trigger pinch-off; the daughter droplets subsequently recoalesce, often after wall contact, yielding flattened remnants. In multiple-droplet settings, pump-induced charging produces lateral electrostatic repulsion and asymmetric deformation; under geometric confinement, crescent bending and star-like morphologies emerge. Shear-flow tests further show that a pumped droplet can be immobilised and ruptured while an unpumped neighbour is advected downstream, suggesting a route to sorting. Taken together, the results establish interfacial pumping as an internal actuation mechanism that robustly controls droplet morphology and dynamics across configurations.

physics.flu-dyn↗

arXiv2025

Proper Orthogonal Decomposition-based Model-Order Reduction for Smoothed Particle Hydrodynamics Simulation -- Mass-Spring-Damper System

Model Order Reduction (MOR) based on Proper Orthogonal Decomposition (POD) and Smooth Particle Hydrodynamics (SPH) has proven effective in various applications. Most MOR methods utilizing POD are implemented within a pure Eulerian framework, while significantly less attention has been given to POD in a Lagrangian context. In this paper, we present the POD-MOR of SPH simulations applied to a mass-spring-damper system with two primary objectives: 1. To evaluate the performance of the data-driven POD-MOR approach. 2. To investigate potential methods for accelerating POD-MOR computations. Although the mass-spring-damper system is linear, its SPH implementations are nonlinear, and POD-MOR does not automatically lead to faster computations. Our findings indicate that (1) the POD-MOR effectively reduces the degrees of freedom in the SPH simulations by capturing the essential modes, and (2) in various cases, the acceleration of POD-MOR can be achieved without compromising accuracy. We hope that our results will motivate further investigations into the design of POD-MOR algorithms for nonlinear Lagrangian systems.

physics.comp-ph↗

arXiv2025

Proper Orthogonal Decomposition-based Model-Order Reduction for Smoothed Particle Hydrodynamics Simulation

In this paper, we present a projection-based model-order reduction (MOR) technique for smoothed particle hydrodynamics (SPH) simulations, which is a mesh-free approach within the Lagrangian framework. Our approach utilizes the proper orthogonal decomposition (POD) technique to generate a subspace basis for the reduction process. The main objective of this study is to conduct an initial exploration of the feasibility of employing POD-based MOR (POD-MOR) in SPH simulations and to quantify the associated POD error. To illustrate the effectiveness of this approach, we consider the friction stir spot welding problem, which involves the coupling of flow equations and heat equation. Our findings reveal that, with the same degrees of freedom, POD-MOR significantly reduces computational error compared to the uniform reduction of particle numbers in SPH simulations. Additionally, the acceleration technique of POD-MOR for SPH simulation via linearization and freezing coefficients has been shown to be effective while keeping the error small. We have also showed the effectiveness of POD-MOR in predictive settings in SPH simulations with different parameter values.

physics.comp-ph↗

arXiv2025

Beyond Single-Channel: Multichannel Signal Imaging for PPG-to-ECG Reconstruction with Vision Transformers

Reconstructing ECG from PPG is a promising yet challenging task. While recent advancements in generative models have significantly improved ECG reconstruction, accurately capturing fine-grained waveform features remains a key challenge. To address this, we propose a novel PPG-to-ECG reconstruction method that leverages a Vision Transformer (ViT) as the core network. Unlike conventional approaches that rely on single-channel PPG, our method employs a four-channel signal image representation, incorporating the original PPG, its first-order difference, second-order difference, and area under the curve. This multi-channel design enriches feature extraction by preserving both temporal and physiological variations within the PPG. By leveraging the self-attention mechanism in ViT, our approach effectively captures both inter-beat and intra-beat dependencies, leading to more robust and accurate ECG reconstruction. Experimental results demonstrate that our method consistently outperforms existing 1D convolution-based approaches, achieving up to 29% reduction in PRD and 15% reduction in RMSE. The proposed approach also produces improvements in other evaluation metrics, highlighting its robustness and effectiveness in reconstructing ECG signals. Furthermore, to ensure a clinically relevant evaluation, we introduce new performance metrics, including QRS area error, PR interval error, RT interval error, and RT amplitude difference error. Our findings suggest that integrating a four-channel signal image representation with the self-attention mechanism of ViT enables more effective extraction of informative PPG features and improved modeling of beat-to-beat variations for PPG-to-ECG mapping. Beyond demonstrating the potential of PPG as a viable alternative for heart activity monitoring, our approach opens new avenues for cyclic signal analysis and prediction.

eess.IV↗

arXiv2025

Micro-Macro Modeling of Polymeric Fluids with Multi-Bead Polymer Chain

This work extends the classical dumbbell (two-bead) model of polymer chains to a more detailed multi-bead representation, where each polymer chain consists of $N$ beads connected by $N-1$ springs. We develop a thermodynamically consistent micro-macro model based on the energy variational method to describe the coupled dynamics of polymer configurations and fluid flow. The resulting framework captures complex microscopic behaviors, such as bond stretching and alignment under flow, and links them to macroscopic stress responses.

cond-mat.soft↗

arXiv2025

A thermodynamically consistent phase-field model for mass transport with interfacial reaction and deformation

In this paper, a thermodynamically consistent phase-field model is proposed to describe the mass transport and reaction processes of multiple species in a fluid. A key feature of this model is that reactions between different species occur only at the interface, and may induce deformation of the interface. For the governing equations derived based on the energy variational method, we propose a structure-preserving numerical scheme that satisfies the mass conservation and energy dissipation laws at the discrete level. Furthermore, we carry out a rigorous error analysis of the time-discrete scheme for a simplified case. A series of numerical experiments are conducted to validate the effectiveness of the model as well as the accuracy and stability of the scheme. In particular, we simulate microvessels with straight and bifurcated structures to illustrate the risk of microaneurysm formation.

math.NA↗

arXiv2025

CLEP-GAN: An Innovative Approach to Subject-Independent ECG Reconstruction from PPG Signals

This study addresses the challenge of reconstructing unseen ECG signals from PPG signals, a critical task for non-invasive cardiac monitoring. While numerous public ECG-PPG datasets are available, they lack the diversity seen in image datasets, and data collection processes often introduce noise, complicating ECG reconstruction from PPG even with advanced machine learning models. To tackle these challenges, we first introduce a novel synthetic ECG-PPG data generation technique using an ODE model to enhance training diversity. Next, we develop a novel subject-independent PPG-to-ECG reconstruction model that integrates contrastive learning, adversarial learning, and attention gating, achieving results comparable to or even surpassing existing approaches for unseen ECG reconstruction. Finally, we examine factors such as sex and age that impact reconstruction accuracy, emphasizing the importance of considering demographic diversity during model training and dataset augmentation.

eess.SP↗

arXiv2024

Multidomain Model for Optic Nerve Potassium Clearance: Roles of Glial Cells and Perivascular Spaces

The accumulation of potassium in the extracellular space surrounding nerve cells is a fundamental aspect of biophysics that has garnered significant attention in recent research. This phenomenon holds implications for various neurological conditions, including spreading depression, migraine, certain types of epilepsy, and potentially, learning processes. A quantitative analysis is essential for understanding the dynamics of potassium clearance following a series of action potentials. This clearance process involves multiple structures along the nerve, including glia, the extracellular space, axons, and the perivascular space, necessitating a spatially distributed systems approach akin to the cable equations of nerve physiology. In this study, we propose a multi-domain model for the optic nerve to investigate potassium accumulation and clearance dynamics. The model accounts for the convection, diffusion, and electrical migration of fluid and ions, revealing the significant roles of glia and the perivascular space in potassium buffering. Specifically, our findings suggest that potassium clearance primarily occurs through convective flow within the syncytia of glia, driven by osmotic pressure differences. Additionally, the perivascular space serves as a crucial pathway for potassium buffering and fluid circulation, further contributing to the overall clearance process. Importantly, our model's adaptability allows for its application to diverse structures with distinct channel and transporter distributions across the six compartments, extending its utility beyond the optic nerve.

physics.bio-ph↗

arXiv2024

A multi-domain model for microcirculation in optic nerve: blood flow and oxygen transport

Microcirculation of blood and oxygen transport play important roles in biological function of optic nerve and are directly affected by damages or pathologies. This work develops a multi-domain model for optic nerve, that includes important biological structures and various physical mechanisms in blood flow and oxygen delivery. The two sets of vasculature network are treated as five domains in the same geometric region, with various exchanges among them (such as Darcy's law for fluid flow) and with the tissue domain (such as water leak, diffusion). The numerical results of the coupled model for a uniform case of vasculature distribution show mechanisms and scales consistent with literature and intuition. The effects of various important model parameters (relevant to pathological conditions) are investigated to provide insights into the possible implications. The vasculature distribution (resting volume fractions here) has significant impacts on the blood circulation and could lead to insufficient blood supply in certain local region and in turn affect the oxygen delivery. The water leak across the capillary wall will have nontrivial effects after the leak coefficients pass a threshold. The periodic arterial pressure conditions lead to expected periodic patterns and stable spatial profiles, and the uniform case is almost the averaged version of periodic case. The effects of viscosity, the stiffness of blood vessel wall, oxygen demand, etc. have also been analyzed. The framework can be extended to include ionic transport or to study the retina when more biological structural information is available.

physics.bio-ph↗

arXiv2023

Coupled Chemical Reactions: Effects of Electric Field, Diffusion and Boundary Control

Chemical reactions involve the movement of charges, and this work presents a mathematical model for describing chemical reactions in electrolytes. The model is developed using an energy variational method that aligns with classical thermodynamics principles. It encompasses both electrostatics and chemical reactions within consistently defined energetic and dissipative functionals. Furthermore, the energy variation method is extended to account for open systems that involve the input and output of charge and mass. Such open systems have the capability to convert one form of input energy into another form of output energy. In particular, a two-domain model is developed to study a reaction system with self-regulation and internal switching, which plays a vital role in the electron transport chain of mitochondria responsible for ATP generation crucial process for sustaining life. Simulations are conducted to explore the influence of electric potential on reaction rates and switching dynamics within the two-domain system. It shows that the electric potential inhibits the oxidation reaction while accelerating the reduction reaction.

physics.chem-ph↗

arXiv2023

Micro-Macro Modeling of Polymeric Fluids and Shear-Induced Microscopic Behaviors

This article delves into the micro-macro modeling of polymeric fluids, considering various microscopic potential energies, including the classical Hookean potential, as well as newly proposed modified Morse and Elastic-plastic potentials. These proposed potentials encompass microscopic-scale bond-breaking processes. The development of a thermodynamically consistent micro-macro model is revisited, employing the energy variational method. To validate the model's predictions, we conduct numerical simulations utilizing a deterministic particle-FEM method. Our numerical findings shed light on the distinct behaviors exhibited by polymer chains at the micro-scale in comparison to the macro-scale velocity and induced shear stresses of fluids under shear flow. Notably, we observe that polymer elongation, rotation, and bond breaking contribute to the zero polymer-induced stress in the micro-macro model when employing Morse and Elastic-plastic potentials. Furthermore, at high shear rates, polymer rotation is found to induce shear-thinning behavior in the model employing the classical Hookean potential.

cond-mat.soft↗

arXiv2023

A phase field model for droplets suspended in viscous liquids under the influence of electric fields

In this paper, we propose a Poisson-Nernst-Planck-Navier-Stokes-Cahn-Hillard (PNP-NS-CH)model for an electrically charged droplet suspended in a viscous fluid subjected to an external electric field. Our model incorporates spatial variations of electric permittivity and diffusion constants, as well as interfacial capacitance. Based on a time scale analysis, we derive two approximations of the original model, namely a dynamic model for the net charge and a leaky-dielectric model. For the leaky-dielectric model, we conduct a detailed asymptotic analysis to demonstrate the convergence of the diffusive-interface leaky-dielectric model to the sharp interface model as the interface thickness approaches zero. Numerical computations are performed to validate the asymptotic analysis and demonstrate the model's effectiveness in handling topology changes, such as electrocoalescence. Our numerical results of these two approximation models reveal that the polarization force, which is induced by the spatial variation of electric permittivity in the direction perpendicular to the external electric field, consistently dominates the Lorentz force, which arises from the net charge. The equilibrium shape of droplets is determined by the interplay between these two forces along the direction of the electric field. Furthermore, in the presence of the interfacial capacitance, a local variation of effective permittivity leads to an accumulation of counter-ions near the interface, resulting in a reduction in droplet deformation. Our numerical solutions also confirm that the leaky dielectric model serves as a reasonable approximation of the original PNP-NS-CH model when the electric relaxation time is sufficiently short. The Lorentz force and droplet deformation both decrease when the diffusion of net charge is significant.

physics.flu-dyn↗