scholarly journals On the Role of Ionic Modeling on the Signature of Cardiac Arrhythmias for Healthy and Diseased Hearts

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2242
Author(s):  
William A. Ramírez ◽  
Alessio Gizzi ◽  
Kevin L. Sack ◽  
Simonetta Filippi ◽  
Julius M. Guccione ◽  
...  
Keyword(s):  
Ventricular Fibrillation ◽  
Cardiac Arrhythmias ◽  
Large Scale ◽  
Structural Parameters ◽  
Computational Cost ◽  
Three Dimensional ◽  
Electrophysiological Properties ◽  
Modeling Approaches ◽  
In Silico Studies ◽  
Whole Heart

Computational cardiology is rapidly becoming the gold standard for innovative medical treatments and device development. Despite a worldwide effort in mathematical and computational modeling research, the complexity and intrinsic multiscale nature of the heart still limit our predictability power raising the question of the optimal modeling choice for large-scale whole-heart numerical investigations. We propose an extended numerical analysis among two different electrophysiological modeling approaches: a simplified phenomenological one and a detailed biophysical one. To achieve this, we considered three-dimensional healthy and infarcted swine heart geometries. Heterogeneous electrophysiological properties, fine-tuned DT-MRI -based anisotropy features, and non-conductive ischemic regions were included in a custom-built finite element code. We provide a quantitative comparison of the electrical behaviors during steady pacing and sustained ventricular fibrillation for healthy and diseased cases analyzing cardiac arrhythmias dynamics. Action potential duration (APD) restitution distributions, vortex filament counting, and pseudo-electrocardiography (ECG) signals were numerically quantified, introducing a novel statistical description of restitution patterns and ventricular fibrillation sustainability. Computational cost and scalability associated with the two modeling choices suggests that ventricular fibrillation signatures are mainly controlled by anatomy and structural parameters, rather than by regional restitution properties. Finally, we discuss limitations and translational perspectives of the different modeling approaches in view of large-scale whole-heart in silico studies.

scholarly journals Prediction of Residual Stresses in a Multipass Pipe Weld by a Novel 3D Finite Element Approach

2018 ◽  
Author(s):  
Hui Huang ◽  
Jian Chen ◽  
Blair Carlson ◽  
Hui-Ping Wang ◽  
Paul Crooker ◽  
...  
Keyword(s):  
Finite Element ◽  
Residual Stresses ◽  
High Performance ◽  
Large Scale ◽  
Graphics Processing Unit ◽  
Computational Cost ◽  
Three Dimensional ◽  
Processing Unit ◽  
Girth Welds ◽  
Welding Processes

Due to enormous computation cost, current residual stress simulation of multipass girth welds are mostly performed using two-dimensional (2D) axisymmetric models. The 2D model can only provide limited estimation on the residual stresses by assuming its axisymmetric distribution. In this study, a highly efficient thermal-mechanical finite element code for three dimensional (3D) model has been developed based on high performance Graphics Processing Unit (GPU) computers. Our code is further accelerated by considering the unique physics associated with welding processes that are characterized by steep temperature gradient and a moving arc heat source. It is capable of modeling large-scale welding problems that cannot be easily handled by the existing commercial simulation tools. To demonstrate the accuracy and efficiency, our code was compared with a commercial software by simulating a 3D multi-pass girth weld model with over 1 million elements. Our code achieved comparable solution accuracy with respect to the commercial one but with over 100 times saving on computational cost. Moreover, the three-dimensional analysis demonstrated more realistic stress distribution that is not axisymmetric in hoop direction.

Comparison Between Isotropic and Anisotropic Electrical Properties of a DTI-Based Cardiac Model

2008 ◽  
Author(s):  
Ana Maria Saaibi ◽  
Isaac Chang ◽  
Min-Sig Hwang ◽  
Malisa Sarntinoranont
Keyword(s):  
Electrical Properties ◽  
Ventricular Fibrillation ◽  
Cardiac Function ◽  
Cardiac Arrhythmias ◽  
Three Dimensional ◽  
Delicate Balance ◽  
Cardiac Model ◽  
Myocardial Fibers ◽  
Fiber Organization ◽  
Cardiac Fibers

Cardiac function is influenced by the three-dimensional organization of the myocardial fibers. Cardiac fibers are arranged in a circumferential, longitudinal, and a sheet-like fashion, forming counter-wound helices from the base to the apex of the heart. This fiber organization is responsible for the delicate balance between mechanical and electrical functioning of the heart. When electrical disruption of this coordinated function occurs, this is associated with cardiac arrhythmias which may lead to more serious conditions like ventricular fibrillation.

scholarly journals The Role of Dimensionality in Understanding Granuloma Formation

Computation ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 58 ◽  
Author(s):  
Simeone Marino ◽  
Caitlin Hult ◽  
Paul Wolberg ◽  
Jennifer Linderman ◽  
Denise Kirschner
Keyword(s):  
Experimental Data ◽  
Large Scale ◽  
Bacterial Load ◽  
Computational Cost ◽  
Granuloma Formation ◽  
In Silico Studies ◽  
Cellular Recruitment ◽  
2D And 3D

Within the first 2–3 months of a Mycobacterium tuberculosis (Mtb) infection, 2–4 mm spherical structures called granulomas develop in the lungs of the infected hosts. These are the hallmark of tuberculosis (TB) infection in humans and non-human primates. A cascade of immunological events occurs in the first 3 months of granuloma formation that likely shapes the outcome of the infection. Understanding the main mechanisms driving granuloma development and function is key to generating treatments and vaccines. In vitro, in vivo, and in silico studies have been performed in the past decades to address the complexity of granuloma dynamics. This study builds on our previous 2D spatio-temporal hybrid computational model of granuloma formation in TB (GranSim) and presents for the first time a more realistic 3D implementation. We use uncertainty and sensitivity analysis techniques to calibrate the new 3D resolution to non-human primate (NHP) experimental data on bacterial levels per granuloma during the first 100 days post infection. Due to the large computational cost associated with running a 3D agent-based model, our major goal is to assess to what extent 2D and 3D simulations differ in predictions for TB granulomas and what can be learned in the context of 3D that is missed in 2D. Our findings suggest that in terms of major mechanisms driving bacterial burden, 2D and 3D models return very similar results. For example, Mtb growth rates and molecular regulation mechanisms are very important both in 2D and 3D, as are cellular movement and modulation of cell recruitment. The main difference we found was that the 3D model is less affected by crowding when cellular recruitment and movement of cells are increased. Overall, we conclude that the use of a 2D resolution in GranSim is warranted when large scale pilot runs are to be performed and if the goal is to determine major mechanisms driving infection outcome (e.g., bacterial load). To comprehensively compare the roles of model dimensionality, further tests and experimental data will be needed to expand our conclusions to molecular scale dynamics and multi-scale resolutions.

Process modeling, joint-property characterization and construction of joint connectors for mechanical fastening by self-piercing riveting

2014 ◽  
Vol 10 (4) ◽  
pp. 631-658 ◽  
Author(s):  
Mica Grujicic ◽  
Jennifer Snipes ◽  
S. Ramaswami ◽  
Fadi Abu-Farha
Keyword(s):  
Mechanical Properties ◽  
Finite Element ◽  
Large Scale ◽  
Constitutive Relations ◽  
Computational Cost ◽  
Three Dimensional ◽  
Modeling And Simulations ◽  
Content Type ◽  
Material Parameters ◽  
Computational Analyses

Purpose – The purpose of this paper is to propose a computational approach in order to help establish the effect of various self-piercing rivet (SPR) process and material parameters on the quality and the mechanical performance of the resulting SPR joints. Design/methodology/approach – Toward that end, a sequence of three distinct computational analyses is developed. These analyses include: (a) finite-element modeling and simulations of the SPR process; (b) determination of the mechanical properties of the resulting SPR joints through the use of three-dimensional, continuum finite-element-based numerical simulations of various mechanical tests performed on the SPR joints; and (c) determination, parameterization and validation of the constitutive relations for the simplified SPR connectors, using the results obtained in (b) and the available experimental results. The availability of such connectors is mandatory in large-scale computational analyses of whole-vehicle crash or even in simulations of vehicle component manufacturing, e.g. car-body electro-coat paint-baking process. In such simulations, explicit three-dimensional representation of all SPR joints is associated with a prohibitive computational cost. Findings – It is found that the approach developed in the present work can be used, within an engineering optimization procedure, to adjust the SPR process and material parameters (design variables) in order to obtain a desired combination of the SPR-joint mechanical properties (objective function). Originality/value – To the authors’ knowledge, the present work is the first public-domain report of the comprehensive modeling and simulations including: self-piercing process; virtual mechanical testing of the SPR joints; and derivation of the constitutive relations for the SPR connector elements.

scholarly journals MicroCT analysis of connectivity in porous structures: optimizing data acquisition and analytical methods in the context of tissue engineering

2020 ◽  
Vol 17 (165) ◽  
pp. 20190833
Author(s):  
Malavika Nair ◽  
Jennifer H. Shepherd ◽  
Serena M. Best ◽  
Ruth E. Cameron
Keyword(s):  
Tissue Engineering ◽  
Analytical Methods ◽  
Large Scale ◽  
Structural Parameters ◽  
Three Dimensional ◽  
Data Capture ◽  
Pixel Size ◽  
Scale Invariant ◽  
Structural Anisotropy

Micro-computed X-ray tomography (MicroCT) is one of the most powerful techniques available for the three-dimensional characterization of complex multi-phase or porous microarchitectures. The imaging and analysis of porous networks are of particular interest in tissue engineering due to the ability to predict various large-scale cellular phenomena through the micro-scale characterization of the structure. However, optimizing the parameters for MicroCT data capture and analyses requires a careful balance of feature resolution and computational constraints while ensuring that a structurally representative section is imaged and analysed. In this work, artificial datasets were used to evaluate the validity of current analytical methods by considering the effect of noise and pixel size arising from the data capture, and intrinsic structural anisotropy and heterogeneity. A novel ‘segmented percolation method’ was developed to exclude the effect of anomalous, non-representative features within the datasets, allowing for scale-invariant structural parameters to be obtained consistently and without manual intervention for the first time. Finally, an in-depth assessment of the imaging and analytical procedures are presented by considering percolation events such as micro-particle filtration and cell sieving within the context of tissue engineering. Along with the novel guidelines established for general pixel size selection for MicroCT, we also report our determination of 3 μm as the definitive pixel size for use in analysing connectivity for tissue engineering applications.

Δ-Quantum machine learning for medicinal chemistry

2021 ◽  
Author(s):  
Kenneth Atz ◽  
Clemens Isert ◽  
Markus N. A. Böcker ◽  
José Jiménez-Luna ◽  
Gisbert Schneider
Keyword(s):  
Machine Learning ◽  
Message Passing ◽  
Density Functional ◽  
Large Scale ◽  
Molecular Design ◽  
Low Cost ◽  
Computational Cost ◽  
Three Dimensional ◽  
Biomolecular Systems ◽  
Quantum Observables

Many molecular design tasks benefit from fast and accurate calculations of quantum-mechanical (QM) properties. However, the computational cost of QM methods applied to drug-like molecules currently renders large-scale applications of quantum chemistry challenging. Aiming to mitigate this problem, we developed DelFTa, an open-source toolbox for the prediction of electronic properties of drug-like molecules at the density functional (DFT) level of theory, using Δ-machine-learning. Δ-Learning corrects the prediction error (Δ) of a fast but inaccurate property calculation. DelFTa employs state-of-the-art three-dimensional message-passing neural networks trained on a large dataset of QM properties. It provides access to a wide array of quantum observables on the molecular, atomic and bond levels by predicting approximations to DFT values from a low-cost semiempirical baseline. Δ-Learning outperformed its direct-learning counterpart for most of the considered QM endpoints. The results suggest that predictions for non-covalent intra- and intermolecular interactions can be extrapolated to larger biomolecular systems. The software is fully open-sourced and features documented command-line and Python APIs.

A particle-based model to investigate nanoparticle diffusion in a 3D biofilm environment

2020 ◽  
Author(s):  
Bart Coppens ◽  
Jiří Pešek ◽  
Bart Smeets ◽  
Herman Ramon
Keyword(s):  
Surface Properties ◽  
Large Scale ◽  
Extracellular Polymeric Substances ◽  
Structural Parameters ◽  
Computational Cost ◽  
Coarse Graining ◽  
Single Particle Tracking ◽  
Solid Base ◽  
Limiting Factor ◽  
Chemical Surface

<p>Biofilms exhibit heavily increased antibiotic tolerance in comparison to planktonic bacteria, leading to chronic complications during infection. This increased tolerance originates from extracellular polymeric substances (EPS). By binding the antibiotics, they limit access of active compounds to target sites. Embedding the antibiotics in polymer nanoparticles (NPs) provides a promising strategy to deal with this inactivation mechanism. Antibiotic compounds are then protected from unwanted interaction with the biofilm matrix. However, diffusion and subsequently penetration of NPs in the biofilm becomes the limiting factor. Chemical surface modifications would then allow to modify NP interaction with the biofilm and mediate deeper penetration. </p> <p>We present a particle-based model to investigate how structural differences in the biofilm impact NP diffusion, which can later be used to evaluate performance of various NP surface properties. We model the structure of the biofilm, diffusion of low NP concentrations and their interaction with the biofilm. Spherocylindrical bacteria are seeded according to empirically-derived structural parameters such as cell-cell distance, vertical and radial alignment. Interactions with the EPS matrix are represented as spherical zones with higher effective viscosity around the bacteria. We then use this setup to study how differences in biofilm organization and differences in matrix viscosity influence NP penetration depth. </p> <p>We show that sterical interaction with the bacteria alone is insufficient to explain the slowdown in diffusion found in single particle tracking (SPT) experiments. Higher effective EPS viscosity leads to lower NP penetration, but spread of the EPS zones were found to lower NP penetration more. These results are consistent with literature. </p> <p>The method we present here is suitable to evaluate the diffusion and entrapment of NPs in small concentrations in a heterogeneous biofilm environment, taking interactions with EPS and structure of the biofilm into account. Organization of the bacteria and the nature of interaction with EPS can be spatially varied and NPs can actively change the environment. This setup can be used on large scale biofilms, in contrast to computational fluid dynamics approaches, where the amount of computational cells would outscale the number of particles in the simulation. This particle-based model additionally allows to model interactions between NPs such as aggregation. The current coarse graining method for interactions between EPS and NPs allows to increase scale with less strain on the computational cost. This model will provide a solid base to study the fate of nanoparticles in highly heterogeneous biofilms and provide suggestions for NP surface properties and increase success rate for nanomedicine development. </p>

scholarly journals Impact of UAV Surveying Parameters on Mixed Urban Landuse Surface Modelling

2020 ◽  
Vol 9 (11) ◽  
pp. 656
Author(s):  
Muhammad Hamid Chaudhry ◽  
Anuar Ahmad ◽  
Qudsia Gulzar
Keyword(s):  
Point Cloud ◽  
Large Scale ◽  
Accuracy Assessment ◽  
Computational Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
Ground Control ◽  
Control Points ◽  
Ground Control Points ◽  
High Computational Cost

Unmanned Aerial Vehicles (UAVs) as a surveying tool are mainly characterized by a large amount of data and high computational cost. This research investigates the use of a small amount of data with less computational cost for more accurate three-dimensional (3D) photogrammetric products by manipulating UAV surveying parameters such as flight lines pattern and image overlap percentages. Sixteen photogrammetric projects with perpendicular flight plans and a variation of 55% to 85% side and forward overlap were processed in Pix4DMapper. For UAV data georeferencing and accuracy assessment, 10 Ground Control Points (GCPs) and 18 Check Points (CPs) were used. Comparative analysis was done by incorporating the median of tie points, the number of 3D point cloud, horizontal/vertical Root Mean Square Error (RMSE), and large-scale topographic variations. The results show that an increased forward overlap also increases the median of the tie points, and an increase in both side and forward overlap results in the increased number of point clouds. The horizontal accuracy of 16 projects varies from ±0.13m to ±0.17m whereas the vertical accuracy varies from ± 0.09 m to ± 0.32 m. However, the lowest vertical RMSE value was not for highest overlap percentage. The tradeoff among UAV surveying parameters can result in high accuracy products with less computational cost.

Comparison of Experimental and Numerically Predicted Three-Dimensional Wake Behaviour of a Vertical Axis Wind Turbine

2017 ◽  
Author(s):  
Joseph Saverin ◽  
David Marten ◽  
David Holst ◽  
George Pechlivanoglou ◽  
Christian Oliver Paschereit ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Large Scale ◽  
Computational Cost ◽  
Three Dimensional ◽  
Vertical Axis ◽  
Tip Vortex ◽  
Vertical Axis Wind Turbine ◽  
Design And Optimization ◽  
Aerodynamic Model ◽  
Lift And Drag

The evolution of the wake of a wind turbine contributes significantly to its operation and performance, as well as to those of machines installed in the vicinity. The inherent unsteady and three-dimensional aerodynamics of Vertical Axis Wind Turbines (VAWT) have hitherto limited the research on wake evolution. In this paper the wakes of both a troposkien and a H-type VAWT rotor are investigated by comparing experiments and calculations. Experiments were carried out in the large-scale wind tunnel of the Politecnico di Milano, where unsteady velocity measurements in the wake were performed by means of hot wire anemometry. The geometry of the rotors was reconstructed in the open-source wind-turbine software QBlade, developed at the TU Berlin. The aerodynamic model makes use of a lifting line free-vortex wake (LLFVW) formulation, including an adapted Beddoes-Leishman unsteady aerodynamic model; airfoil polars are introduced to assign sectional lift and drag coefficients. A wake sensitivity analysis was carried out to maximize the reliability of wake predictions. The calculations are shown to reproduce several wake features observed in the experiments, including blade-tip vortex, dominant and submissive vortical structures, and periodic unsteadiness caused by sectional dynamic stall. The experimental assessment of the simulations illustrates that the LLFVW model is capable of predicting the unsteady wake development with very limited computational cost, thus making the model ideal for the design and optimization of VAWTs.

Research on the surface of multilayer weft knitted fabrics using computer simulation

2015 ◽  
Vol 27 (4) ◽  
pp. 561-572 ◽  
Author(s):  
Lanming Jin ◽  
Gaoming Jiang
Keyword(s):  
Computer Simulation ◽  
Large Scale ◽  
Structural Parameters ◽  
Three Dimensional ◽  
Surface Model ◽  
Knitted Fabric ◽  
Loop Model ◽  
Knitted Fabrics ◽  
Content Type ◽  
3D Effect

Purpose – Multilayer weft knitted fabrics possess many advantages, such as strongly stereoscopic patterns, soft handling and adjustable thickness of apparel and home textiles use. However, it is difficult to predict the final visual effects before the productive process because of the three-dimensional (3D) effect caused by the connecting yarn of the fabric. The purpose of this paper is to realize a realistic simulation of the fabric. Design/methodology/approach – The authors applied to the curve and surface model to simulate the knitted fabric, instead of previous single loop model by NURBS. Macro simulation is more suitable for the fabric with the 3D effect because of the quick, real and convenient simulation. This research includes experiments on the structural parameters concerning the regular sag of multilayer weft knitted fabrics, and analysis of parameter data and the simulation process with the aim of realizing a computer simulation of the fabric, especially with a sense of reality. The Digital Elevation Model was also applied to build a simulated 3D model. Findings – To obtain the values for the change rules, different samples were used and the outputs of the model were found to be close to the experimental results. The thickest and thinnest lengths and the changing curves between them were established. Patterned simple multilayer weft knitted fabric could be simulated through the results of the research. It is possible to simulate different real fabrics using their materials and expected effects. The authors are going to improve the model to simulate the complicate large-scale jacquard fabrics in further research. Practical implications – The results will be useful for establishing a computer surface simulation system for stereo perception of fabrics. Originality/value – The authors put forward the concept of surface warpage degree (R). It is an important factor affecting the fabric stereo feeling. The larger the value of R, the stronger the stereo sense of the fabric. It could be applied to most 3D fabric. A thickness difference testing method was proposed to characterize the stereo perception of fabrics. It is possible to simulate different real fabrics quickly without the model of the woven loop.

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