Complex Propagation Patterns Research Articles

Phase-field modeling of hydraulic fracture interaction with natural fractures

The problem of hydraulic fracturing has been the subject of several studies in recent years, including different proposals for analytical, experimental, and numerical models. This interest is justified by the complexity of the problem and its great relevance, with applications in various areas including the industrial, energy and engineering sectors. Several applications deal with natural reservoirs which are usually characterized by the presence of inclusions, heterogeneities and natural fractures, the latter being the subject of this study. These pre-existing fractures affect the circulation of the pressurized fluid inserted into the reservoir, influencing the path of the hydraulic fracture. The interaction between hydraulic and natural fractures generates complex fracture propagation patterns involving arrest, cross and branch phenomena between the cracks. In this sense, an interesting approach to modeling hydraulic fracturing is the use of phase-field models (PFM). Through its variational approach, the PFM is able to automatically deal with any number of cracks without restricting their shapes or trajectories and the crack path is obtained directly as part of the solution to the energy minimization problem. Therefore, this paper proposes a study of the interaction between hydraulic fractures and different networks of pre-existing natural fractures using a PFM that considers the pressure load on the surface of the hydraulic fractures. Numerical examples are presented to illustrate different possible interactions between the cracks and to explore different initial crack scenarios. All simulations were performed using the INSANE (INteractive Structural ANalysis Environment) software.

Estimation, tuning, and evaluation of propagation direction behavior in superimposed orthogonal two-dimensional structure-borne traveling waves

Abstract Structure-borne traveling waves (SBTW) are observed in nature as a means for propulsion and locomotion of creatures on land and in the ocean. Recently, various approaches have been investigated to replicate this phenomenon. Previous studies have successfully generated SBTWs suitable for propulsion applications and particle motion on active surfaces. Much recent literature has focused on generating traveling waves that propagate only along a single axis for 1D and 2D structures. This limits their potential and does not take advantage of the full potential of 2D structures.
This study examines the potential of employing superposition to control the propagation direction of 2D SBTW. This is investigated numerically using an experimentally validated Finite Element model of a 2D plate with piezoelectric actuators. The individual SBTWs are superimposed by simultaneously exciting two pairs of actuators that are aligned orthogonally on the surface of a plate. Traveling waves are excited in the plate using two-mode excitation. Structural intensity is utilized to develop quantifiable metrics to describe the overall propagation direction and uniformity, which are necessary for describing the complex propagation patterns encountered with 2D SBTW. The potential of the proposed approach along with developed tuning and evaluation methods are demonstrated through case studies of two plates, one square and one rectangular. For both cases, the overall direction of the SBTW is tuned to propagate for any direction between the individual SBTW. This was achieved while maintaining a high-quality overall SBTW. With this approach, 2D SBTW can be steered for wave-driven motion applications such as propulsion of the structure itself or conveying particles in any direction along the structure's surface without compromising the quality of the overall traveling wave.

A Survey on Fake News Detection in Social Media Using Graph Neural Networks

Nowadays, social media has become the key source of information for anyone seeking about current events across the world. This information may be fake or real news. On social media platforms, fake news negatively impacts politics, the economy, and health, and affects the stability of society. The research on fake news detection has received widespread attention in the field of computer science. There are many effective methods of fake news detection technology including natural language processing (NLP) and machine learning techniques, primarily focusing on content analysis and user behavior. While these methods have shown promise, they often fall short in capturing the complex relational and propagation patterns inherent in social networks. Fake news exhibits distinct features such as misleading headlines, and fabricated content, making its detection challenging. To address these issues, Graph Neural Networks (GNNs) have been introduced as a superior solution. GNNs are particularly effective in processing graph-structured data, allowing them to model the intricate connections and dissemination patterns of news in social networks more accurately. This study provides an overview A variety of false information and their characteristics and discusses various techniques and features used in fake news detection. As well as advanced GNN-based techniques and datasets used to implement practical fake news detection systems from multiple perspectives and future research directions. In addition, tables and summary figures help researchers understand the full picture of fake news detection. Finally, the object of this review is to help other researchers improve fake news detection models using GNNs.

Phase field method to model hydraulic fracturing in saturated porous reservoir with natural fractures

In the present work, phase field model has been implemented for simulating hydraulic fracturing in porous reservoir which consists of several poorly connected natural fractures. We have used the finite element method (FEM) for solving the poro-elastic deformation and phase field equation, while the finite volume method (FVM) has been considered for solving the flow field. The validations of the numerical model with existing analytical and numerical solutions of fracture propagation are presented for an elastic medium subjected to incremental external loads and a poro-elastic medium undergoes hydraulic fracturing due to the increase of fluid injection pressure. The simulation results in this study show the ability of the phase field method based hydraulic fracturing (HF) model to obtain complex fracture propagation patterns including crack branching, merging, curving, and interacting with pre-existing natural fractures. Numerical simulation results suggest that for high injection pressure it is possible to get crack branching which is a desirable in the context of hydraulic fracture to create multiple high permeable flow paths with improved connectivity among the natural fractures for fluid circulation among injection and production wells. In the present study the values of aperture along the newly created hydraulic fracture and pre-existing fracture are determined from the displacement and phase fields at the end of hydraulic fracture simulations. The enhancement of effective transmissivity of the reservoir after hydraulic fracturing is compared for different network of pre-existing natural fracture. These results may be very insightful for industrial applications of hydraulic fracturing.

Regional-scale assessment of earthquake-induced slope displacement considering uncertainties in subsurface soils and hydrogeological condition

Realistic prediction of coseismic landslides is crucial for the design of civil infrastructures and geotechnical systems in seismically active regions. Coseismic landslides are complicated nonlinear and large-deformation processes triggered by ground shaking. To date, many gaps still remain in the scientific understanding of the landslides, particularly in areas lacking information on the subsurface stratigraphy. Analytical methods for estimating coseismic landslides have been based on highly simplified models, where many key influential factors have been overlooked, leading to large uncertainty in using empirical models for landslide prediction. In addition, more evidence recently underscores the necessity of modeling coupled effects between topography and soil amplification, which gives rise to complex wave propagation patterns due to scattering and diffracting of waves within the low-velocity near-surface layers. Neglecting topographic amplification and soil layers could result in significantly underpredicted regional-scale hazards of landslides. In this study, a regional-scale coseismic landslide simulation is carried out using the integral Spectral Element Method (SEM)-Newmark method for Hong Kong Island to quantify the coupled effect of 3D topography, subsurface soil condition as well as hydrogeological conditions. By leveraging extensive geological borehole data, a rigorous statistical model that characterizes uncertainties associated with subsurface soils is established. Influence of key factors that are not well considered in previous coseismic landslide studies, such as variation in irregular rockhead and spatially distributed shear-wave velocity are quantitatively analyzed. Numerical results demonstrate that by rigorously incorporating multiple sources of subsurface soil uncertainties, the total area of landslides in the study region can increase up to 30% compared with benchmark model as evidenced in the physics-based numerical simulation. These case studies will provide a valuable opportunity to revisit key factors that influence coseismic landslides using measured field data.

Horizontal refraction and diffraction of underwater sound around an island.

The three-dimensional (3D) propagation effects of horizontal refraction and diffraction were measured on a tetrahedral hydrophone array deployed near the coast of Block Island, RI. Linear frequency modulated chirp signals, centered at 1 kHz with a 400 Hz bandwidth, were transmitted from a ship moving out of the acoustic shadow zone blocked by the island from the perspective of the hydrophone array. The observed shadow zone boundary was consistent with the prediction made by a 3D sound propagation model incorporating high-resolution bathymetry and realistic sound speed obtained from a data-assimilated regional ocean model. The 3D modal ray calculation provided additional insight into the frequency dependence of the signal spreading. This analysis found that the modes at higher frequencies can propagate closer to the coast of the island with shallower modal cutoff depths, where the sound energy penetrates the sloping seafloor at supercritical incidence. The evidence of horizontal caustics of the sound was shown in the parabolic equation and modal ray models by comparing to the arrival pattern observed in the data. The arrival angle measurements on the tetrahedral array show the complex propagation patterns, including the diffracted energy in the island shadow and acoustic energy refracted away from the island.

The Effects of Fibrotic Cell Type and Its Density on Atrial Fibrillation Dynamics: An In Silico Study.

Remodeling in atrial fibrillation (AF) underlines the electrical and structural changes in the atria, where fibrosis is a hallmark of arrhythmogenic structural alterations. Fibrosis is an important feature of the AF substrate and can lead to abnormal conduction and, consequently, mechanical dysfunction. The fibrotic process comprises the presence of fibrotic cells, including fibroblasts, myofibroblasts and fibrocytes, which play an important role during fibrillatory dynamics. This work assesses the effect of the diffuse fibrosis density and the intermingled presence of the three types of fibrotic cells on the dynamics of persistent AF. For this purpose, the three fibrotic cells were electrically coupled to cardiomyocytes in a 3D realistic model of human atria. Low (6.25%) and high (25%) fibrosis densities were implemented in the left atrium according to a diffuse fibrosis representation. We analyze the action potential duration, conduction velocity and fibrillatory conduction patterns. Additionally, frequency analysis was performed in 50 virtual electrograms. The tested fibrosis configurations generated a significant conduction velocity reduction, where the larger effect was observed at high fibrosis density (up to 82% reduction in the fibrocytes configuration). Increasing the fibrosis density intensifies the vulnerability to multiple re-entries, zigzag propagation, and chaotic activity in the fibrillatory conduction. The most complex propagation patterns were observed at high fibrosis densities and the fibrocytes are the cells with the largest proarrhythmic effect. Left-to-right dominant frequency gradients can be observed for all fibrosis configurations, where the fibrocytes configuration at high density generates the most significant gradients (up to 4.5 Hz). These results suggest the important role of different fibrotic cell types and their density in diffuse fibrosis on the chaotic propagation patterns during persistent AF.

Non-invasive Estimation of Atrial Fibrillation Driver Position With Convolutional Neural Networks and Body Surface Potentials.

Atrial fibrillation (AF) is characterized by complex and irregular propagation patterns, and AF onset locations and drivers responsible for its perpetuation are the main targets for ablation procedures. ECG imaging (ECGI) has been demonstrated as a promising tool to identify AF drivers and guide ablation procedures, being able to reconstruct the electrophysiological activity on the heart surface by using a non-invasive recording of body surface potentials (BSP). However, the inverse problem of ECGI is ill-posed, and it requires accurate mathematical modeling of both atria and torso, mainly from CT or MR images. Several deep learning-based methods have been proposed to detect AF, but most of the AF-based studies do not include the estimation of ablation targets. In this study, we propose to model the location of AF drivers from BSP as a supervised classification problem using convolutional neural networks (CNN). Accuracy in the test set ranged between 0.75 (SNR = 5 dB) and 0.93 (SNR = 20 dB upward) when assuming time independence, but it worsened to 0.52 or lower when dividing AF models into blocks. Therefore, CNN could be a robust method that could help to non-invasively identify target regions for ablation in AF by using body surface potential mapping, avoiding the use of ECGI.

Application of recurrence plot analysis to characterise whole chamber propagation of atrial fibrillation

Abstract Funding Acknowledgements Type of funding sources: Public hospital(s). Main funding source(s): Oxford Biomedical Research Centre Introduction Non-contact charge density mapping allows visualisation of whole chamber propagation during atrial fibrillation (AF). The identification of regions with repetitive or, conversely, more complex patterns of wavefront propagation may provide clues to mechanisms responsible for AF maintenance and lead to improved outcomes from catheter ablation. Our novel mapping approach based on signal recurrence plots has never been applied to whole chamber, bi-atrial recording of atrial fibrillation. Purpose To apply recurrence analysis to characterise whole chamber bi-atrial AF propagation. Methods Non-contact dipole signals from left and right atrial maps were obtained during simultaneous bi-atrial charge density mapping of AF. Signals were converted to phase and mean phase coherence calculated for the generation of recurrence distance matrices for the whole chamber and each anatomical region (6x LA and 4x RA) over the 30-second recording duration, where a value of 1 (purple, see figure panel A) represents uniform repetitive conduction, and 0 (red), irregular, non-repetitive activity. Whole chamber and regional mean recurrence values were calculated and correlated with the frequency of wavefronts of localised irregular activation patterns. Results Maps were obtained prior to ablation in 21 patients (5 paroxysmal (pAF), 16 persistent AF (persAF)) undergoing de-novo catheter ablation procedures. Whole chamber recurrence was higher in patients with pAF (0.40 ± 0.08) than persAF (0.34 ± 0.05), p < 0.0005. There was an inverse correlation between regional recurrence values and the number of localised irregular activations detected (-0.7021, p < 0.0005, figure panel B) with the lateral LA and anterior RA demonstrating the highest recurrence values in each chamber (figure panel C). Conclusion Use of recurrence distance matrices characterises global AF propagation phenotypes. Regional values are inversely correlated with the frequency of localised irregular activation patterns identified demonstrating an anatomic dependence in the level of AF propagation complexity, greatest in the anterior LA and septal RA. Comparison of strategies targeting regions with maximal vs. minimal values during catheter ablation may define an optimal approach to treatment of persistent AF. Abstract Figure. Recurrence abstract figure

Diversity of the Boreal Summer Intraseasonal Oscillation

AbstractBoreal summer intraseasonal oscillation (BSISO) profoundly impacts Northern Hemisphere monsoon onsets and breaks, tropical cyclones, and many climate extremes. BSISO exhibits more complex propagation patterns than the dominant eastward propagation of the Madden‐Julian Oscillation. Previous studies have extensively examined the dominant northeastward propagating BSISO mode and its northward component, but this mode only accounts for about half of the total cases. We conducted an objective cluster analysis of the two‐dimensional BSISO propagation and revealed two new forms of BSISO propagation besides the northeastward propagation: the dipolar northward propagation and the eastward expansion. We investigate processes governing the different propagation forms using moisture tendency analysis. We show that the propagation diversity is related to BSISO’s circulation structural asymmetries and the associated moistening processes. The Rossby‐wave component in the background zonal wind shear favors northward propagation while the Kelvin‐wave component favors eastward propagation. The circulation differences are affected by the variation of background states, especially those season‐dependent variations. The results provide insights into the BSISO diversity and potential precursors for foreseeing BSISO propagation.

Novel approaches to mechanism-based atrial fibrillation ablation.

Modern cardiac electrophysiology has reported significant advances in the understanding of mechanisms underlying complex wave propagation patterns during atrial fibrillation (AF), although disagreements remain. One school of thought adheres to the long-held postulate that AF is the result of randomly propagating wavelets that wonder throughout the atria. Another school supports the notion that AF is deterministic in that it depends on a small number of high-frequency rotors generating three-dimensional scroll waves that propagate throughout the atria. The spiralling waves are thought to interact with anatomic and functional obstacles, leading to fragmentation and new wavelet formation associated with the irregular activation patterns documented on AF tracings. The deterministic hypothesis is consistent with demonstrable hierarchical gradients of activation frequency and AF termination on ablation at specific (non-random) atrial regions. During the last decade, data from realistic animal models and pilot clinical series have triggered a new era of novel methodologies to identify and ablate AF drivers outside the pulmonary veins. New generation electroanatomical mapping systems and multielectrode mapping catheters, complimented by powerful mathematical analyses, have generated the necessary platforms and tools for moving these approaches into clinical procedures. Recent clinical data using such platforms have provided encouraging evidence supporting the feasibility of targeting and effectively ablating driver regions in addition to pulmonary vein isolation in persistent AF. Here, we review state-of-the-art technologies and provide a comprehensive historical perspective, characterization, classification, and expected outcomes of current mechanism-based methods for AF ablation. We discuss also the challenges and expected future directions that scientists and clinicians will face in their efforts to understand AF dynamics and successfully implement any novel method into regular clinical practice.

Bi-atrial high-density mapping reveals inhibition of wavefront turning and reduction of complex propagation patterns as main antiarrhythmic mechanisms of vernakalant.

AimsComplex propagation patterns are observed in patients and models with stable atrial fibrillation (AF). The degree of this complexity is associated with AF stability. Experimental work suggests reduced wavefront turning as an important mechanism for widening of the excitable gap. The aim of this study was to investigate how sodium channel inhibition by vernakalant affects turning behaviour and propagation patterns during AF.Methods and resultsTwo groups of 8 goats were instrumented with electrodes on the left atrium, and AF was maintained by burst pacing for 3 or 22 weeks. Measurements were performed at baseline and two dosages of vernakalant. Unipolar electrograms were mapped (249 electrodes/array) on the left and right atrium in an open-chest experiment. Local activation times and conduction vectors, flow lines, the number of fibrillation waves, and local re-entries were determined. At baseline, fibrillation patterns contained numerous individual fibrillation waves conducting in random directions. Vernakalant induced conduction slowing and cycle length prolongation and terminated AF in 13/15 goats. Local re-entries were strongly reduced. Local conduction vectors showed increased preferential directions and less beat-to-beat variability. Breakthroughs and waves were significantly reduced in number. Flow line curvature reduced and waves conducted more homogenously in one direction. Overall, complex propagation patterns were strongly reduced. No substantial differences in drug effects between right and left atria or between goats with different AF durations were observed.ConclusionsDestabilization of AF by vernakalant is associated with a lowering of fibrillation frequency and inhibition of complex propagation patterns, wave turning, local re-entries, and breakthroughs.

Material point method (MPM) hydro-mechanical modelling of flows impacting rigid walls

The study on impact mechanisms of flow-like landslides against structures is still an open issue in the scientific literature. Many researchers have so far employed either experiments or numerical methods, but the evaluation of the impact forces on mitigation obstacles remains difficult especially if the solid–fluid interaction within the flow is considered. This study shows how advanced numerical tools, such as material point method, may be used in simulating those complex processes. The simulations are carried out for two well-documented laboratory tests: a dry granular flow impacting a rigid wall under different geometries and testing conditions in a small-scaled flume and a saturated flow with complex propagation pattern in a centrifuge apparatus. The numerical modelling is validated against the observations and then used to explore the response of different flows impacting rigid structures in other conditions than in the experiments. The soil–fluid interaction influences the type of impact mechanism, the kinematics of the flow, and the space–time trend of the impact pressure against the structure.

Experiments and analysis on the influence of multiple closed cemented natural fractures on hydraulic fracture propagation in a tight sandstone reservoir

This work designs an experimental model of tight sandstone with a closed cemented pre-existing fracture network (CCPF) to explore the influence of closed cemented natural fractures on the propagation behavior of hydraulic fracture (HF) in tight sandstone formations. The influence of CCPFs with different directions on the initiation, deflection, and propagation of HF is studied based on tri-axial hydraulic fracturing experiments with acoustic emission (AE) monitoring technology. The experimental results show four types of interaction behavior between HFs and CCPFs: deflection I; deflection II; penetration; and composite pattern. When the angle (α) between the HFs and CCPF is 0° ± 15°, their interaction is deflection I. During the process of hydraulic fracturing, the CCPF open with few AE events. When α = 90° ± 15°, the interaction between the HF and CCPFs includes deflection II and penetration patterns. The HF mainly extends in the rock matrix and is accompanied by significant AE events. When α = 45° ± 15°, the interaction is complicated and includes composite and deflection I patterns. The accumulated AE energy of composite interaction pattern shows a ladder-type increase. Under the same in-situ stress conditions, the HF geometry is the most complicated with the largest number of communicated natural fractures when the angle between the maximum principal horizontal stress direction and CCPF is 30°–60°. The experimental model designed in this paper can reproduce the complex propagation patterns of HFs in fractured tight sandstone formations, and the results provide a reliable basis for follow-up theoretical studies and engineering applications.

Electrocardiographic imaging including intracardiac information to achieve accurate global mapping during atrial fibrillation

Atrial fibrillation (AF) is characterized by complex and irregular propagation patterns. Noninvasive electrocardiographic imaging (ECGI) has been tested during AF conditions with promising results. However, current regularization methods face important challenges in this type of unstable electrical activity scenarios. Combination of intracardiac and non-invasive simultaneous recordings could improve ECGI performance and allow real-time global mapping of complex AF patterns. In this work, we propose an ECGI method that incorporates intracardiac measurements as a constraint in a reformulation of the classical Tikhonov method. We used realistic mathematical models of atria and torso that simulates a wide number of epicardial electrical activity patterns. Body surface potentials were obtained from simulated electrograms (EGMs) by using Boundary Element Method and corrupted with Gaussian noise. Epicardial potentials were estimated using inverse problem with Tikhonov regularization, including intracavitary information as a second constraint. Results showed that first-order Constrained Tikhonov formulation provided more reliable reconstructions than the classical Tikhonov approach in AF conditions using at least 32 uniformly distributed endocardial EGMs (CC between 0.87 and 0.28, depending on the AF complexity). Constrained Tikhonov provided more accurate spatial mass functions (SMF) of PS locations (CCSMF between 0.24 and 0.86). This methodology was tested on real patient data, obtaining a mean DF RMSE of 0.85 Hz, outperforming the classical Tikhonov approach. Limitations of this study include the fact that the model considered endocardium and epicardium as a single layer. Further research will include endocardium–epicardium bilayer model approximations and validation using more real patient data.

Topological Determinants of Perturbation Spreading in Networks.

Spreading phenomena essentially underlie the dynamics of various natural and technological networked systems, yet how spatiotemporal propagation patterns emerge from such networks remains largely unknown. Here we propose a novel approach that reveals universal features determining the spreading dynamics in diffusively coupled networks and disentangles them from factors that are system specific. In particular, we first analytically identify a purely topological factor encoding the interaction structure and strength, and second, numerically estimate a master function characterizing the universal scaling of the perturbation arrival times across topologically different networks. The proposed approach thereby provides intuitive insights into complex propagation patterns as well as accurate predictions for the perturbation arrival times. The approach readily generalizes to a wide range of networked systems with diffusive couplings and may contribute to assess the risks of transient influences of ubiquitous perturbations in real-world systems.

P1389Periodicity and Spatial Stability of Complex Propagation Patterns in Atrial Fibrillation

Abstract Introduction Non-contact charge density mapping identifies complex wavefront propagation including localised rotational activation (LRA), localised irregular activation (LIA) and focal firing (FF). However, the duration of mapping required to reveal underlying patterns and their temporal stability is unknown. Purpose We sought to evaluate the variability in propagation patterns over increasing durations of recordings up to 30 seconds and examine the stability of these patterns between 2 separate maps with the aim of identifying the minimum duration required to reveal underlying patterns and how they represent the stable arrhythmia substrate. Methods Patients undergoing first time AcQMap guided catheter ablation were studied. 30s recordings of left atrial propagation were analysed. LIA, LRA, and FF were quantified for frequency, percentage time present and percentage surface area affected (for FF only frequency was assessed) at increasing durations up to 30s in 1s increments. At each incremental recording duration the percentage change in each variable was calculated. For occurrence frequency the results for every possible combination of maps of increasing duration within the 30s recording were compared whilst for occurrence time and surface area a 5s moving average at 1s increments was calculated. The point at which variability was seen to plateau represents the minimum optimal mapping duration. Spatial stability was assessed by correlating the frequency of patterns at each vertex of the anatomy over 2 separate 30s recordings. Stability of regions with the most repetitive patterns were compared using Cohen’s kappa statistic. Results 15 patients were analysed (age 63 ± 9, 10 male, BMI 30 ± 5, CHA2DS2Vasc 1 ± 1.3, ejection fraction 54 ± 12%, left atrial diameter 46 ± 7mm, paroxysmal 1, persistent 14) with 11 included in the spatial stability analysis due to availability of recordings of sufficient duration. LRA demonstrated most variability followed by LIA and FF. Variability in LIA, LRA and FF decrease at increasing durations. LIA and FF variability plateau by 13 and 17s respectively. LRA plateaus at 23s. Variability of <10% is reached in all parameters at 18s. LIA demonstrated the greatest stability with average R2 of 0.76 ± 0.14 (figure). Average R2 for LRA and FF were 0.45 ± 0.16 and 0.47 ± 0.12. Low frequency focal firings were widely distributed across the atrial surface. For FF occurring at a frequency ≥10 over the 30s, average R2 value was 0.65 ± 0.14. Cohen kappa statistic was 0.70 for LIA and 0.45 for LRA. Conclusion Mapping durations of ≥23s are required to identify all temporally variable propagation patterns although shorter durations will identify less variable LIA and FF. LIA demonstrates high spatiotemporal stability and may best reflect disrupted conduction caused by the underlying atrial substrate and tissue architecture. Regions of high frequency FF are temporally stable and may represent important targets for ablation. Abstract Figure 1

Topological turbulence in the membrane of a living cell

Topological defects determine the structure and function of physical and biological matter over a wide range of scales, from the turbulent vortices in planetary atmospheres, oceans or quantum fluids to bioelectrical signalling in the heart1–3 and brain4, and cell death5. Many advances have been made in understanding and controlling the defect dynamics in active6–9 and passive9,10 non-equilibrium fluids. Yet, it remains unknown whether the statistical laws that govern the dynamics of defects in classical11 or quantum fluids12–14 extend to the active matter7,15,16 and information flows17,18 in living systems. Here, we show that a defect-mediated turbulence underlies the complex wave propagation patterns of Rho-GTP signalling protein on the membrane of starfish egg cells, a process relevant to cytoskeletal remodelling and cell proliferation19,20. Our experiments reveal that the phase velocity field extracted from Rho-GTP concentration waves exhibits vortical defect motions and annihilation dynamics reminiscent of those seen in quantum systems12,13, bacterial turbulence15 and active nematics7. Several key statistics and scaling laws of the defect dynamics can be captured by a minimal Helmholtz–Onsager point vortex model21 as well as a generic complex Ginzburg–Landau22 continuum theory, suggesting a close correspondence between the biochemical signal propagation on the surface of a living cell and a widely studied class of two-dimensional turbulence23 and wave22 phenomena. Activity in certain living systems can lead to swirling flows akin to turbulence. Here, the authors connect the dynamics of topological defects in starfish oocyte membranes to vortex dynamics in 2D Bose–Einstein condensates.

Numerical Investigation of Hydraulic Fracture Propagation Based on Cohesive Zone Model in Naturally Fractured Formations

Complex propagation patterns of hydraulic fractures often play important roles in naturally fractured formations due to complex mechanisms. Therefore, understanding propagation patterns and the geometry of fractures is essential for hydraulic fracturing design. In this work, a seepage–stress–damage coupled model based on the finite pore pressure cohesive zone (PPCZ) method was developed to investigate hydraulic fracture propagation behavior in a naturally fractured reservoir. Compared with the traditional finite element method, the coupled model with global insertion cohesive elements realizes arbitrary propagation of fluid-driven fractures. Numerical simulations of multiple-cluster hydraulic fracturing were carried out to investigate the sensitivities of a multitude of parameters. The results reveal that stress interference from multiple-clusters is responsible for serious suppression and diversion of the fracture network. A lower stress difference benefits the fracture network and helps open natural fractures. By comparing the mechanism of fluid injection, the maximal fracture network can be achieved with various injection rates and viscosities at different fracturing stages. Cluster parameters, including the number of clusters and their spacing, were optimal, satisfying the requirement of creating a large fracture network. These results offer new insights into the propagation pattern of fluid driven fractures and should act as a guide for multiple-cluster hydraulic fracturing, which can help increase the hydraulic fracture volume in naturally fractured reservoirs.

Transfer Learning From Simulations on a Reference Anatomy for ECGI in Personalized Cardiac Resynchronization Therapy.

Noninvasive cardiac electrophysiology (EP) model personalisation has raised interest for instance in the scope of predicting EP cardiac resynchronization therapy (CRT) response. However, the restricted clinical applicability of current methods is due in particular to the limitation to simple situations and the important computational cost. We propose in this manuscript an approach to tackle these two issues. First, we analyze more complex propagation patterns (multiple onsets and scar tissue) using relevance vector regression and shape dimensionality reduction on a large simulated database. Second, this learning is performed offline on a reference anatomy and transferred onto patient-specific anatomies in order to achieve fast personalized predictions online. We evaluated our method on a dataset composed of 20 dyssynchrony patients with a total of 120 different cardiac cycles. The comparison with a commercially available electrocardiographic imaging (ECGI) method shows a good identification of the cardiac activation pattern. From the cardiac parameters estimated in sinus rhythm, we predicted five different paced patterns for each patient. The comparison with the body surface potential mappings (BSPM) measured during pacing and the ECGI method indicates a good predictive power. We showed that learning offline from a large simulated database on a reference anatomy was able to capture the main cardiac EP characteristics from noninvasive measurements for fast patient-specific predictions. The fast CRT pacing predictions are a step forward to a noninvasive CRT patient selection and therapy optimisation, to help clinicians in these difficult tasks.