3D Mesh Research Articles

FPGA Accelerated Implementation of 3D Mesh Secret Sharing Based on Symmetric Similarity of Model

Secret sharing is particularly important in the field of information security, which allows for the reconstruction of secret information from secure shares. However, due to the large amount of data and non-integer data type of 3D (three-dimensional) models, it is less efficient to perform sharing compared to the 2D(two-dimensional) digital images. In order to enable efficient sharing of 3D models as well, this article designs different circuit modules to parallelize the process of sharing 3D models. The proposed structure exploits the vertex extension to perform a complete reconstruction of the 3D model. In the sharing phase, the symmetric similarity of 3D model is exploited to realize the sharing in parallel, which improves the efficiency of sharing. In the reconstruction phase, the Strassen algorithm is used to optimize matrix multiplication, which saves circuit resources. Simulation results show that the structure performs more than 100 times faster than software. The utilization of circuit resources and the size of the share are both optimized. The validity of the designed hardware architecture is confirmed after analyzing the data from experiments performed on several 3D models.

Nodal auxiliary space preconditioners for mixed virtual element methods

We propose nodal auxiliary space preconditioners for facet and edge virtual elements of lowest order by deriving discrete regular decompositions on polytopal grids and generalizing the Hiptmair-Xu preconditioner to the virtual element framework. The preconditioner consists of solving a sequence of elliptic problems on the nodal virtual element space, combined with appropriate smoother steps. Under assumed regularity of the mesh, the preconditioned system is proven to have bounded spectral condition number independent of the mesh size and this is verified by numerical experiments on a sequence of polygonal meshes. Moreover, we observe numerically that the preconditioner is robust on meshes containing elements with high aspect ratios.

Abstract 4141469: Left Ventricular Septum Displacement Implications in the Limited Cardiac Reserve, RV to Pc Uncoupling and Oxygen Uptake During Exercise in Heart Failure

Background: Dyspnea on exertion is cardinal symptom in heart failure (HF) and may be caused by an unfavorable dynamic of ventricular interaction. This concept has been poorly addressed over time and we hypothesized that a careful study of the interventricular septum adaptations during maximal exercise in HF might be implicated in the limited cardiac reserve and uncoupling of right ventricular (RV) to pulmonary circulation (Pc), both yielding to a limited O2 uptake. Aim: To study the pathophysiology behind biventricular interaction during exercise in HF, evaluating the role of septum displacement during exercise and how and whether it would affect peak exercise oxygen consumption (VO 2 peak) through a limited cardiac output (CO) increase and some degrees of RV to PC uncoupling assessed by TAPSE/PASP. Methods: 22 HF performed a combined cardiopulmonary exercise testing imaging (CPET imaging) with RV 3D-imaging analysis and were compared with a control population. 3D imaging of the RV chamber was examined off-line using the 4D RV TomTec software and obtained 3D mesh of the RV model using custom software to obtain the mean curvature value of IVS in 4 regions of: inflow tract (RVIT), outflow tract (RVOT), apical and body. We acquired measurements of curvature during end-diastole (ED) and at end systole (ES) phases and obtained a parametric curvature map. Results: HF patients (mean age 72±12, 27% female) typically showed an abnormal septal curve, with a more leftward configuration either at rest and under exercise (rest =−0.01±0.007 at ED, and −0.01±0.009 at ES; peak exercise= −0.01±0.006 at ED, and −0.01±0.007 at ES) compared to controls (rest=−0.02±0.002 at ED, and −0.02±0.006 at ES; peak exercise −0.02±0.0.006 at ED, and −0.02±0.01 at ES, Figure). Notably, the degree of the IVS curvature showed a linear correlation with an impaired gas exchange performance as indicated by a lower peak VO 2 , a limited CO and impairment of TAPSE/PASP in HF (respectively, r=0.64, p<0.001, r=0.5, p<0.001, r=0.53, p<0.001 at ED during exercise; r=0.61, p<0.001 at ES during exercise; Figure). Conclusions: In HF, the evidence of right to left IVS displacement appears worth of investigation, by intervening strictly to a reduced CO response, and RV-PA uncoupling during exercise. These findings clearly point to the utility of assessing how new and current therapeutic strategies may modulate the negative septum displacement and overall cardiac mechanics.

Abstract 4145884: Left ventricular 3D-sphericity is associated with 92 genetic loci

Introduction: Left ventricular (LV) sphericity is a measure of the degree to which the LV blood pool resembles a sphere. Analyses of cardiovascular magnetic resonance imaging (MRI) in the MESA cohort have shown that LV sphericity is an important mode of variation in cardiac structure that is associated with ischemia, heart failure, and atrial fibrillation. A recent genome-wide association study (GWAS) of a two-dimensional estimate of sphericity in 38,000 UK Biobank participants identified 4 genetic loci (near PDZRN3, HLA, PLN, and ANGPT1). Genetic contributions to three-dimensional (3D) sphericity remain unknown. Aims: To measure 3D sphericity from cardiovascular MRI at scale and characterize the genetic contributions to 3D sphericity. Methods: Deep learning models were constructed to perform semantic segmentation in the short- and long-axis view from cardiovascular MRI in UK Biobank. These models were applied to all participants with MRI. Poisson surface reconstruction was used to build 3D meshes of the left ventricle. Sphericity was estimated at end-systole and end-diastole as the area of a perfect sphere with the same volume as the left ventricle, divided by the estimated surface area from the mesh. Heritability was estimated with ldsc; GWAS was conducted with REGENIE. Results: Sphericity was estimated in 68,978 individuals, of whom 3,096 were excluded due to atrial fibrillation or atrial dysfunction, and 2,686 were excluded during genetic quality control; 63,196 participants were included in the GWAS. Ldsc heritability was 29.7% for sphericity in diastole and 26.0% for sphericity in systole. 49 genetic loci were associated with 3D sphericity in diastole as were 64 in systole (92 distinct loci). 46 of these loci were unique to sphericity and not found for other LV traits, including loci near the genes encoding calsequestrin 2, troponin T2, palladin, supervillin, and angiopoietins 1 and 2. Shared loci included those near RXFP4, encoding a relaxin-family peptide receptor, and MICU2 (previously implicated in cardiac relaxation). Conclusion: Left ventricular sphericity is heritable, with genetic underpinnings distinct from standard LV measurements.

Comparing assisting technologies for proficiency in cardiac morphology: 3D printing and mixed reality versus CT slice images for morphological understanding of congenital heart defects by medical students.

Learning cardiac morphology largely involves spatial abilities and studies indicate benefits from innovative 3D visualization technologies that speed up and increase the learning output. Studies comparing these teaching tools and their educational output are rare and few studies include complex congenital heart defects. This study compared the effects of 3D prints, mixed reality (MR) viewing of 3D meshes and standard cardiac CT slice images on medical students' understanding of complex congenital heart defect morphology, measuring both objective level of understanding and subjective educational experience. The objective of this study was to compare morphological understanding and user experiences of 3D printed models, MR 3D visualization and axial 2D CT slices, in medical students examining morphological details in complex congenital heart defects. Medical students in the median 4th year of study (range 2nd to 6th) examined three of five different complex congenital heart defects by three different modalities: 3D printed model, MR viewed 3D mesh, and cardiac CT slices, answering a questionnaire on morphology and user experience. Time to complete task, diagnostic accuracy, and user experience data were collected and compared on group level. Task times were similar for all modalities. The percentage of correct answers was higher with MR visualization, which was also the preferred modality overall. Medical students both prefer and better understand the morphology of complex congenital heart disease with 3D models viewed using MR, without spending more time than with 3D prints or 2D CT images.

Review of Talking Head Synthesis for Driving Mechanisms and Portrait Rendering

Abstract. Talking head synthesis has emerged as a vital area of research, enabling the generation of realistic and expressive digital avatars. This paper explores the primary mechanisms driving talking head synthesis, categorized into video-driven and audio-driven methods. Video-driven techniques manipulate facial movements using key points, 3D meshes, and latent spaces, while audio-driven approaches focus on synchronizing lip movements and facial expressions with audio inputs. Recent advances in each method, highlighting key innovations and the challenges faced, such as occlusion, identity preservation, and lip synchronization are reviewed. The technology's applications span smart customer service, online education, telemedicine, and video creation. Future research directions focus on overcoming challenges like handling large-angle poses, ensuring temporal consistency, and improving multilingual performance.

Quantitative Analysis of the Brachialis and Triceps Brachii Insertion Sites on the Proximal Epiphysis of the Ulna in Modern Hominid Primates and Fossil Hominins.

In several species of hominid primates with different types of locomotor behavior, we quantitatively studied the insertion sites of the brachialis and triceps brachii on the proximal epiphysis of the ulna. Our main objective was to evaluate the possibility of using the anatomical features of these insertion sites to infer the locomotor behavior of different species of fossil hominins. We measured the area of these muscle insertion sites using 3D bone meshes and obtained the value of each insertion site relative to the total size of the two insertion sites for each of the species studied. We also compared these relative values of the osteological samples with the relative mass of the brachialis and triceps brachii, which we obtained by dissecting these muscles in the same primate species. The relative values for the brachialis insertion were highest in orangutans, followed by bonobos, chimpanzees, gorillas, and humans. Fossil Australopithecus and Paranthropus had values similar to those of bonobos, while fossil Homo had values similar to those of Homo sapiens. The observed similarity in ulnar attachment sites between Australopithecus and Paranthropus and extant bonobos suggest that these hominins used arboreal locomotion to complement their bipedalism. These adaptations to arboreal locomotion were not observed in Homo.

Additive Manufacturing simulations: An approach based on space partitioning and dynamic 3D mesh adaptation

Additive Manufacturing simulations: An approach based on space partitioning and dynamic 3D mesh adaptation

Geothermal modeling in complex geological systems with ComPASS

In deep geothermal reservoirs, faults and fractures play a major role, serving as regulators of fluid flow and heat transfer while also providing feed zones for production wells. To accurately model the operation of geothermal fields, it is necessary to explicitly consider objects of varying spatial scales, from the reservoir scale itself, to that of faults and fractures, down to the scale of the injection and production wells.Our main objective in developing the ComPASS geothermal flow simulator, was to take into account all of these geometric constraints in a flow and heat transfer numerical model using generic unstructured meshes. In its current state, the code provides a parallel implementation of a spatio-temporal discretization of the non-linear equations driving compositional multi-phase thermal flows in porous fractured media on unstructured meshes. It allows an explicit discretization of faults and fractures as 2D hybrid objects, embedded in a 3D matrix. Similarly, wells are modeled as one dimensional graphs discretized by edges of the 3D mesh which allows arbitrary multi-branch wells. The resulting approach is particularly flexible and robust in terms of modeling.Its practical interest is demonstrated by two case studies in high-energy geothermal contexts.

Mesh optimization for the virtual element method: How small can an agglomerated mesh become?

We present an optimization procedure for generic polygonal or polyhedral meshes, tailored for the Virtual Element Method (VEM). Once the local quality of the mesh elements is analyzed through a quality indicator specific to the VEM, groups of elements are agglomerated to optimize the global mesh quality. A user-set parameter regulates the percentage of mesh elements, and consequently of faces, edges, and vertices, to be removed. This significantly reduces the total number of degrees of freedom associated with a discrete problem defined over the mesh with the VEM, particularly for high-order formulations. We show how the VEM convergence rate is preserved in the optimized meshes, and the approximation errors are comparable with those obtained with the original ones. We observe that the optimization has a regularization effect over low-quality meshes, removing the most pathological elements. In such cases, these “badly-shaped” elements yield a system matrix with very large condition number, which may cause the VEM to diverge, while the optimized meshes lead to convergence. We conclude by showing how the optimization of a real CAD model can be used effectively in the simulation of a time-dependent problem.

Junction conditions for one-dimensional network hemodynamic model for total cavopulmonary connection using physically informed deep learning technique

Abstract This paper presents a novel methodology utilizing physics-informed neural network (PINN) as a junction condition for a 1D network model of blood flow in total cavopulmonary connection generated by the Fontan procedure. The technique integrates a 3D mesh generation process based on the parameterization of the junction geometry, along with a sophisticated physically regularized neural network architecture. Synthetic datasets are produced using 3D steady Stokes simulations within fixed boundaries. We use a physically informed feedforward neural network that utilizes a physically regularized loss function, which incorporates the principle of mass conservation. Our PINN achieves a tolerance of 6% on the test set. We develop a 1D-PINN multiscale model based on a previously developed method for multiscale 1D–3D simulations. Comparison with 1D–3D Stokes based model and 3D Navier–Stokes based model verifies the 1D-PINN model. In the first and second comparison, the maximum deviations of the averaged pressures and flows do not exceed 1.48% and 12.26%, respectively.

Enhanced Multi-Scale Attention-Driven 3D Human Reconstruction from Single Image

Due to the inherent limitations of a single viewpoint, reconstructing 3D human meshes from a single image has long been a challenging task. While deep learning networks enable us to approximate the shape of unseen sides, capturing the texture details of the non-visible side remains difficult with just one image. Traditional methods utilize Generative Adversarial Networks (GANs) to predict the normal maps of the non-visible side, thereby inferring detailed textures and wrinkles on the model’s surface. However, we have identified challenges with existing normal prediction networks when dealing with complex scenes, such as a lack of focus on local features and insufficient modeling of spatial relationships.To address these challenges, we introduce EMAR—Enhanced Multi-scale Attention-Driven Single-Image 3D Human Reconstruction. This approach incorporates a novel Enhanced Multi-Scale Attention (EMSA) mechanism, which excels at capturing intricate features and global relationships in complex scenes. EMSA surpasses traditional single-scale attention mechanisms by adaptively adjusting the weights between features, enabling the network to more effectively leverage information across various scales. Furthermore, we have improved the feature fusion method to better integrate representations from different scales. This enhanced feature fusion allows the network to more comprehensively understand both fine details and global structures within the image. Finally, we have designed a hybrid loss function tailored to the introduced attention mechanism and feature fusion method, optimizing the network’s training process and enhancing the quality of reconstruction results. Our network demonstrates significant improvements in performance for 3D human model reconstruction. Experimental results show that our method exhibits greater robustness to challenging poses compared to traditional single-scale approaches.

Penguin colony georegistration using camera pose estimation and phototourism.

Satellite-based remote sensing and uncrewed aerial imagery play increasingly important roles in the mapping of wildlife populations and wildlife habitat, but the availability of imagery has been limited in remote areas. At the same time, ecotourism is a rapidly growing industry and can yield a vast catalog of photographs that could be harnessed for monitoring purposes, but the inherently ad-hoc and unstructured nature of these images make them difficult to use. To help address this, a subfield of computer vision known as phototourism has been developed to leverage a diverse collection of unstructured photographs to reconstruct a georeferenced three-dimensional scene capturing the environment at that location. Here we demonstrate the use of phototourism in an application involving Antarctic penguins, sentinel species whose dynamics are closely tracked as a measure of ecosystem functioning, and introduce a semi-automated pipeline for aligning and registering ground photographs using a digital elevation model (DEM) and satellite imagery. We employ the Segment Anything Model (SAM) for the interactive identification and segmentation of penguin colonies in these photographs. By creating a textured 3D mesh from the DEM and satellite imagery, we estimate camera poses to align ground photographs with the mesh and register the segmented penguin colony area to the mesh, achieving a detailed representation of the colony. Our approach has demonstrated promising performance, though challenges persist due to variations in image quality and the dynamic nature of natural landscapes. Nevertheless, our method offers a straightforward and effective tool for the georegistration of ad-hoc photographs in natural landscapes, with additional applications such as monitoring glacial retreat.

Joint Optimization-Based Texture and Geometry Enhancement Method for Single-Image-Based 3D Content Creation

Recent studies have explored the generation of three-dimensional (3D) meshes from single images. A key challenge in this area is the difficulty of improving both the generalization and detail simultaneously in 3D mesh generation. To address this issue, existing methods utilize fixed-resolution mesh features to train networks for generalization. This approach is capable of generating the overall 3D shape without limitations on object categories. However, the generated shape often exhibits a blurred surface and suffers from suboptimal texture resolution due to the fixed-resolution mesh features. In this study, we propose a joint optimization method that enhances geometry and texture by integrating generalized 3D mesh generation with adjustable mesh resolution. Specifically, we apply an inverse-rendering-based remeshing technique that enables the estimation of complex-shaped mesh estimations without relying on fixed-resolution structures. After remeshing, we enhance the texture to improve the detailed quality of the remeshed mesh via a texture enhancement diffusion model. By separating the tasks of generalization, detailed geometry estimation, and texture enhancement and adapting different target features for each specific network, the proposed joint optimization method effectively addresses the characteristics of individual objects, resulting in increased surface detail and the generation of high-quality textures. Experimental results on the Google Scanned Objects and ShapeNet datasets demonstrate that the proposed method significantly improves the accuracy of 3D geometry and texture estimation, as evaluated by the PSNR, SSIM, LPIPS, and CD metrics.

Impact of adjacent thoracic structures in negative left atrial remodelling in atrial fibrillation

Abstract Background Previous work has suggested that compression from external structures can promote negative atrial remodelling in atrial fibrillation (AF) [1]. This is mechanistically plausible, with many recognised risk factors in developing AF (age, hypertension, obesity, obstructive sleep apnoea, etc.) related through activation of the autonomic nervous system with an associated increase in atrial pressure and chronic elevation in wall stress [2,3]. Such negative remodelling contributes to the existence of arrhythmogenic atrial substrate [4]. This is highly significant when we consider catheter ablation of extrapulmonary vein targets. Purpose This study aims to investigate the relationship between abnormal conduction patterns indicative of potential AF drivers and their proximity to structures adjacent to the left atrium (LA). Methods Eight patients with paroxysmal or persistent AF, scheduled for an elective catheter ablation procedure using a charge density mapping (CDM) system [5] underwent pre-procedural cardiac MRI. 3D surface mesh reconstructions of individuals’ LA and adjacent structures (ascending aorta [AoA], descending aorta [AoD], and spine) were produced from 2D MRI slices using a proprietary graphical interface tool developed in MATLAB (Figure 1A & B) [6]. MRI derived LA geometries were registered with their CDM counterparts by the Iterative Closest Point algorithm (Figure 1C); this enabled integration of MRI LA geometries into the CDM system. Subsequently, non-contact intrachamber voltage measurements from individuals’ procedures were used to derive cardiac activation directly onto MRI LA geometries. Abnormal conduction patterns representing possible AF drivers (focal firing, rotational propagation, and pivoting propagation) [5] were quantified as occurrences per second at each vertex of MRI LA geometries (Figure 1D). These conduction patterns could then be visualised and assessed in the context of adjacent structures (Figure 1E), with the Euclidean distance between each vertex of the MRI LA geometries and the closest point to their adjacent structures being calculated. Results Mean age was 65±9 years; 4 patients (50%) were male; AF was paroxysmal in 3 (37%) and persistent in 5 (63%); median time since AF diagnosis was 1 (1-3.8) years; ablation type was de novo in 5 (63%) and retreatment in 3 (38%). Frequencies of pivoting and rotational propagation were notably higher in regions of the LA closer to the AoA, and lower near the AoD and spine (Figure 2A & B). Conversely, focal firing showed a less prominent trend, being more frequent in LA regions nearer the AoD and distant from the AoA (Figure 2C). Conclusions Compression from the ascending aorta may promote anterior LA remodelling in AF, leading to increased pivoting and rotational AF drivers. Clinically, this suggests a potential target for ablation therapy with an anterior seatbelt line connecting the right superior pulmonary vein to the mitral annulus.

Exploring LGE areas in the atria: Insights from electroanatomical voltage mapping in AF patients

Abstract Introduction Late gadolinium enhancement MRI (LGE MRI) is a common method for the evaluation of the atrial substrate in atrial fibrillation (AF) patients. The extent of LGE is associated with atrial cardiomyopathy and ablation outcomes. However, previous studies have yielded inconsistent results in detecting low voltage areas (LVA) using bipolar electroanatomical mapping (EAM) in LGE regions. Objective Conduct a thorough analysis of the bipolar and unipolar voltage in LGE areas and its relationship with the voltage in non-LGE areas, utilizing high-density (HD) EAM generated by a multipolar HD-mapping catheter. Methods In this study, 20 patients undergoing AF ablation were examined using LGE-MRI. A 3D mesh integrating LGE data was generated. HD-EAM (> 4000 points) was performed in sinus rhythm. The EAM map and MRI mesh underwent manual alignment and registration. Using a nearest neighbor algorithm, EAM points nearest to LGE areas were identified, and the corresponding unipolar and bipolar voltage values, along with LGE voxel intensity, were exported for analysis. Results LGE areas exhibited a median bipolar voltage amplitude of 0.93 mV, median unipolar voltage of 1.73 mV. In contrast, areas without enhancement displayed median bipolar voltage of 2.33 mV, unipolar voltage of 3.58 mV. We observed a variation in voltage amplitudes across the different LGE areas: bipolar voltage ranged from 0.04 to 2.51 mV and unipolar voltage from 0.22 to 3.75 mV. This variation strongly correlated with voxel intensity in LGE areas (correlation coefficient r = -0.86 [p <0.001]). Irrespective of the voltage amplitude in the examined LGE areas, a significant voltage drop was observed, with an average reduction of 54% in bipolar and 51% in unipolar voltages, compared to the amplitudes in non-LGE areas within the same atria. Conclusion Variations in bipolar and unipolar voltage within LGE areas are significantly correlated with local voxel intensity. Despite the inconsistent overlap with the predefined bipolar threshold for LVA, LGE regions exhibit a pronounced and consistent reduction in both bipolar and unipolar voltage compared to non-LGE areas. This pattern suggests notable electrophysiological changes in these areas. These insights underscore the need for further investigation to better understand the implications and mechanisms underlying these alterations in LGE regions.

Interventricular abnormal septum displacement as contributory mechanism for impaired peak oxygen consumption and exercise cardiac output response in heart failure

Abstract Background In Heart failure (HF), the role of septum position and abnormal right ventricular (RV) geometry in determining exercise performance is unknown. Especially an abnormal interventricular septal (IVS) position is a well-known sign of RV pressure overload which affects left ventricular filling and output due to interdependence. Aim We postulated that an abnormal septum displacement during exercise and RV geometry alteration would affect peak exercise oxygen consumption (VO2) and cardiac output (CO) increase. Methods 17 HF patients with reduced ejection fraction (HFrEF) (mean age 71±12) underwent a cardiopulmonary exercise testing imaging (iCPET) with RV 3D-imaging analysis and were compared with a control population (mean age 67±14). 3D imaging of the RV chamber was examined off-line using the 4D RV TomTec software and obtained 3D mesh of the RV model using custom software to obtain the mean curvature value of IVS in 4 regions of: inflow tract (RVIT), outflow tract (RVOT), apical and body.We acquired measurements of curvature during end-diastole (ED) and at end systole (ES) phases and obtained a parametric curvature map. Results HF patients typically exhibited an abnormal of septal curve, with a more leftward configuration either at rest and under exercise (rest =−0.01±0.004 at ED, and −0.01±0.006 at ES; peak exercise= −0.01±0.004 at ED, and −0.01±0.004 at ES, Figure) compared to controls (rest=−0.02±0.003 at ED, and −0.02±0.005 at ES; peak exercise −0.02±0.008 at ED, and −0.03±0.006 at ES, Figure). Notably, the degree of the IVS curvature was found to linearly correlate with an impaired gas exchange performance as lower peak VO2 and a limited CO in HF (respectively r=0.62, p<0.001 and r=0.5, p<0.001 at ED during exercise; r=0.34, p<0.001 at ES during exercise, Figure). Conclusions In HF, the RV geometrical alterations reflected by an abnormal IVS displacement appear as novel contributory factors to a reduced exercise performance, impaired oxygen uptake and decreased CO.

Unipolar electroanatomical mapping outperforms bipolar voltage in detecting LGE areas in the left atrium

Abstract Introduction In atrial fibrillation (AF) management, understanding left atrial substrate is crucial. While both electroanatomical mapping (EAM) and late gadolinium enhancement MRI (LGE MRI) are reliable methods in assessing atrial substrate and are associated with the ablation outcome, recent findings have highlighted significant discrepancies between bipolar low voltage areas (LVA) in EAM and LGE areas. Objective Explore the relationship between LGE areas and unipolar LVAs by utilizing multipolar high-density (HD) mapping. Methods Nineteen patients scheduled for AF ablation underwent pre-ablation LGE-MRI. Left atrial (LA) segmentation was conducted using a convolutional neural network, which subsequently generated a 3D mesh integrating the LGE data. HD-EAM was performed in sinus rhythm for each patient, capturing at least 4000 points. The EAM map and LGE MRI mesh were co-registered. LVA areas were defined using voltage cut-offs of 0.5 mV for bipolar and 2.5 mV for unipolar measurements. Correspondence between LGE areas and LVAs on the anterior and posterior LA wall was analyzed. Results Both bipolar and unipolar LVA demonstrated high precision in detecting LGE areas (100% and 88% respectively). However, unipolar LVA exhibited a remarkable accuracy of 81% for detecting LGE areas specifically, whereas bipolar LVA displayed a significantly lower accuracy of 28%. These findings were consistent across the different atrial walls. Conclusion Incorporating unipolar voltage data into electroanatomical mapping in the atrium may bridge the observed gap between LGE areas and bipolar LVAs. Our findings highlight the significance of unipolar voltage in evaluating the left atrial substrate, potentially offering a more comprehensive insight into the different layers of atrial walls, and opening the door for new approaches in AF therapy.

A Unified Virtual Model for Real-Time Visualization and Diagnosis in Architectural Heritage Conservation

The aim of this paper is to propose a workflow for the real-time visualization of virtual environments that supports diagnostic tasks in heritage buildings. The approach integrates data from terrestrial laser scanning (3D point clouds and meshes), along with panoramic and thermal images, into a unified virtual model. Additionally, the methodology incorporates several post-processing stages designed to enhance the user experience in visualizing both the building and its associated damage. The methodology was tested on the Medieval Templar Church of Vera Cruz in Segovia, utilizing a combination of visible and infrared data, along with manually prepared damage maps. The project results demonstrate that the use of a hybrid digital model—combining 3D point clouds, polygonal meshes, and panoramic images—is highly effective for real-time rendering, providing detailed visualization while maintaining adaptability for mobile devices with limited computational power.

Lignin-Based N-Carbon Dots Anchoring NiCo2S4/Graphene Hydrogel Exhibits Excellent Performance as Anodes for Hybrid Supercapacitor.

A NiCo2S4/N-CDs/RGO ternary composite hydrogel was prepared via a one-step hydrothermal method, utilizing lignin-based nitrogen-doped carbon dots as a bridge connecting NiCo2S4 and graphene. The specific capacitance of NiCo2S4/N-CDs/RGO significantly outperforms that of the GH and NiCo2S4/RGO electrodes, achieving 1050 F g-1. The 3D mesh porous hydrogel structure mitigates NiCo2S4 nanoparticle aggregation, providing a larger specific surface area for enhanced charge storage. The abundant functional groups of N-CDs interact with Ni (II) and Co (III) cations, favoring NiCo2S4 particle synthesis. Additionally, an assembled solid-state asymmetric supercapacitor employing NiCo2S4/N-CDs/RGO as the positive electrode exhibited excellent energy density (68.4 Wh kg-1) and cycle stability (82% capacitance retention after 10,000 constant current charge-discharge cycles).