Global Propagation Research Articles

Global scale underwater sound modeling and data analysis

Underwater low-frequency sound can travel great distances in the oceans, and sound triggered in the sea by the mechanical energy transfer from the Earth's crust (e.g., earthquakes or volcanoes) and by the energy transfer occurring at the water surface (e.g., wave storms or ice-quakes) can be detected at thousands of kilometers from the source. However, source characterization based on recorded sound data analysis involves significant scientific challenges and uncertainties. A variety of geological and physical oceanographic features can cause horizontal refraction, reflection, and diffraction on global scale sound propagation. In this regard, three-dimensional underwater sound models are required for accurately predicting global scale sound propagation. In this work, based on a Southern Mid-Atlantic Ridge earthquake event, we show the importance of geological and physical oceanographic features in the long range propagation of oceanic sound. A three-dimensional sound propagation model using the parabolic equation (PE) approximation and the split-step Fourier (SSF) method is used. Numerical results are compared with field data recorded by hydrophones at great distances from the source. Based on the case study, a discussion and recommendation on the global scale underwater sound modeling and data analysis are presented.

Three-dimensional modeling in global acoustic propagation

The ocean is nearly transparent for acoustic propagation at low frequencies (<100 Hz), leading to the detection of signals (seismic events, volcanoes, and man-made signals) at distances as large as the ocean basin. Historically, basin acoustic modeling has neglected out-of-plane effects and has been performed with the model computed in the range/depth plane for multiple radials following geodesics (Nx2D). Both oceanographic and bathymetric features can lead to out-of-plane effects. In this paper, a summary of computational approaches to this problem will be presented, including vertical-mode, horizontal ray hybrid approaches, and full-3D Parabolic Equation modeling. Out-of-plane effects include refraction and diffraction—which have different effects as well as different approaches to modeling. Experiments where 3D propagation effects were significant will be presented within this context, including Perth-Bermuda (1960), the Heard Island Feasibility Test (1993), and a recent seismic tomography test off the coast of Japan (2015). Three physics mechanisms will be addressed: horizontal deflection due to mesoscale eddies and fronts, reflection from islands (refraction), and diffraction behind bathymetric edges.

Global propagation of seismic body waves and correlation

We discuss the nature of retrieved body waves at teleseismic distances from correlation of records in two separate bands T<10 s and T>30 s. The short period correlations indicate the presence of deep phases that appear as correct reconstructions of actual phases. We present an example of application to the reflectivity of the core-mantle boundary region. Careful tests show the reliability of the images produced with ambient noise records. On the opposite, we analyze long period records and show that the correlations are dominated by strong coherent phases (with time close to actual ScS or P'P'df) that are the signatures of high quality factor normal modes. By using array analysis and spectral analysis, we identify the dominant constituents. We then make use of geometrical quantization to derive the ballistic reverberations of rays that contributes to the emergence of signals at times close to body wave arrivals. Our study indicates that the signals measured in the long period correlations have a physical significance, but their interpretation as station to station seismic ray is nontrivial.

Wave propagation in magneto-electro-elastic multilayered plates with nonlocal effect

In this paper, analytical solutions for propagation of time-harmonic waves in three-dimensional, transversely isotropic, magnetoelectroelastic and multilayered plates with nonlocal effect are derived. We first convert the time-harmonic wave problem into a linear eigenvalue system, from which we obtain the general solutions of the extended displacements and stresses. The solutions are then employed to derive the propagator matrix which connects the field variables at the upper and lower interfaces of each layer. Making use of the continuity conditions of the physical quantities across the interface, the global propagator relation is assembled by propagating the solutions in each layer from the bottom to the top of the layered plate. From the global propagator matrix, the dispersion equation is obtained by imposing the traction-free boundary conditions on both the top and bottom surfaces of the layered plate. Dispersion curves and mode shapes in layered plates made of piezoelectric BaTiO3 and magnetostrictive CoFe2O4 materials are presented to show the influence of the nonlocal parameter, stacking sequence, as well as the orientation of incident wave on the time-harmonic field response.

LncRNAs2Pathways: Identifying the pathways influenced by a set of lncRNAs of interest based on a global network propagation method

Long non-coding RNAs (lncRNAs) have been demonstrated to play essential roles in diverse cellular processes and biological functions. Exploring the functions associated with lncRNAs may help provide insight into their underlying biological mechanisms. The current methods primarily focus on investigating the functions of individual lncRNAs; however, essential biological functions may be affected by the combinatorial effects of multiple lncRNAs. Here, we have developed a novel computational method, LncRNAs2Pathways, to identify the functional pathways influenced by the combinatorial effects of a set of lncRNAs of interest based on a global network propagation algorithm. A new Kolmogorov–Smirnov-like statistical measure weighted by the network propagation score, which considers the expression correlation among lncRNAs and coding genes, was used to evaluate the biological pathways influenced by the lncRNAs of interest. We have described the LncRNAs2Pathways methodology and illustrated its effectiveness by analyzing three lncRNA sets associated with glioma, prostate and pancreatic cancers. We further analyzed the reproducibility and robustness and compared our results with those of two other methods. Based on these analyses, we showed that LncRNAs2Pathways can effectively identify the functional pathways associated with lncRNA sets. Finally, we implemented this method as a freely available R-based tool.

Saline-Induced Coronary Hyperemia: Mechanisms and Effects on Left Ventricular Function.

During thermodilution-based assessment of volumetric coronary blood flow, we observed that intracoronary infusion of saline increased coronary flow. This study aims to quantify the extent and unravel the mechanisms of saline-induced hyperemia. Thirty-three patients were studied; in 24 patients, intracoronary Doppler flow velocity measurements were performed at rest, after intracoronary adenosine, and during increasing infusion rates of saline at room temperature through a dedicated catheter with 4 lateral side holes. In 9 patients, global longitudinal strain and flow propagation velocity were assessed by transthoracic echocardiography during a prolonged intracoronary saline infusion. Taking adenosine-induced maximal hyperemia as reference, intracoronary infusion of saline at rates of 5, 10, 15, and 20 mL/min induced 6%, 46%, 111%, and 112% of maximal hyperemia, respectively. There was a close agreement of maximal saline- and adenosine-induced coronary flow reserve (intraclass correlation coefficient, 0.922; P<0.001). The same infusion rates given through 1 end hole (n=6) or in the contralateral artery (n=6) did not induce a significant increase in flow velocity. Intracoronary saline given on top of an intravenous infusion of adenosine did not further increase flow. Intracoronary saline infusion did not affect blood pressure, systolic, or diastolic left ventricular function. Heart rate decreased by 15% during saline infusion (P=0.021). Intracoronary infusion of saline at room temperature through a dedicated catheter for coronary thermodilution induces steady-state maximal hyperemia at a flow rate ≥15 mL/min. These findings open new possibilities to measure maximal absolute coronary blood flow and minimal microcirculatory resistance.

Leaders and followers: quantifying consistency in spatio-temporal propagation patterns

Repetitive spatio-temporal propagation patterns are encountered in fields as wide-ranging as climatology, social communication and network science. In neuroscience, perfectly consistent repetitions of the same global propagation pattern are called a synfire pattern. For any recording of sequences of discrete events (in neuroscience terminology: sets of spike trains) the questions arise how closely it resembles such a synfire pattern and which are the spike trains that lead/follow. Here we address these questions and introduce an algorithm built on two new indicators, termed SPIKE-order and spike train order, that define the synfire indicator value, which allows to sort multiple spike trains from leader to follower and to quantify the consistency of the temporal leader-follower relationships for both the original and the optimized sorting. We demonstrate our new approach using artificially generated datasets before we apply it to analyze the consistency of propagation patterns in two real datasets from neuroscience (giant depolarized potentials in mice slices) and climatology (El Niño sea surface temperature recordings). The new algorithm is distinguished by conceptual and practical simplicity, low computational cost, as well as flexibility and universality.

Impact of anthropogenic activities on the dissemination of antibiotic resistance across ecological boundaries

Antibiotics are considered to be one of the major medical breakthroughs in history. Nonetheless, over the past four decades, antibiotic resistance has reached alarming levels worldwide and this trend is expected to continue to increase, leading some experts to forecast the coming of a 'post-antibiotic' era. Although antibiotic resistance in pathogens is traditionally linked to clinical environments, there is a rising concern that the global propagation of antibiotic resistance is also associated with environmental reservoirs that are linked to anthropogenic activities such as animal husbandry, agronomic practices and wastewater treatment. It is hypothesized that the emergence and dissemination of antibiotic-resistant bacteria (ARB) and antibiotic-resistant genes (ARGs) within and between environmental microbial communities can ultimately contribute to the acquisition of antibiotic resistance in human pathogens. Nonetheless, the scope of this phenomenon is not clear due to the complexity of microbial communities in the environment and methodological constraints that limit comprehensive in situ evaluation of microbial genomes. This review summarizes the current state of knowledge regarding antibiotic resistance in non-clinical environments, specifically focusing on the dissemination of antibiotic resistance across ecological boundaries and the contribution of this phenomenon to global antibiotic resistance.

Defect-controlled transverse localization of light in triangular optical lattices.

We present a detailed analysis of the transverse localization of light in a triangular optical lattice with a negative defect of different depths and positions. The analysis allows us to explore some essentials of the localization behavior. We characterize the localization strength by global propagation of the signal beam and its properties on the output plane. It is demonstrated that the enhancement of the localization is dependent on the defect depth. Additionally, the calculation of the ray trace of the signal beam shows that the position of the defect has a crucial influence on the localization.

A Hybrid Riemann Solver for Large Hyperbolic Systems of Conservation Laws

This paper presents a Riemann solver for nonlinear hyperbolic systems of conservation laws based on a Krylov subspace approximation of the upwinding dissipation vector. In the general case, the solver does not require any detailed information of the eigensystem, except an estimate of the global maximal propagation speed. It uses successive flux function evaluations to obtain a numerical flux which is almost equivalent to that of a Godunov scheme with complete upwinding. The new Krylov--Riemann solver is particularly efficient when used for large systems with many nonlinear equations such that typically no explicit expression for the eigensystem is available. Also, no numerical procedures are necessary to compute the eigensystem. Numerical examples demonstrate the excellent performance of the solver with respect to other solvers.

Stereoscopic image recoloring

Image recoloring is the process of modification and adjustment of color appearance in images. Existing methods address the recoloring of a single image. We propose a method for recoloring stereoscopic images. Naively recoloring each image independently will require a pair of strokes in the source stereoscopic image pair. However, it is difficult to require consistent strokes on both the left and right views. We show how to extend a single image recoloring to work on stereoscopic images. Our method requires only a few user strokes on the left view and automatically transfers the corresponding strokes to the right view. Then a nonlocal color linear model optimization assumption is designed. Our nonlocal color linear model inherits the advantages of global and local color propagation methods. Our approach can propagate color cues in a global manner which can propagate color relatively far from the provided color constraints, while it provides the user with good local control. The experimental results show that the recolorized image pair is geometrically consistent with the original one.

Effects of pressure on cellular flame structure of high hydrogen content lean premixed syngas spherical flames: A DNS study

The structure and propagation of turbulent lean premixed high hydrogen content syngas flames at pressure values of 1 bar, 2 bar and 4 bar are studied using three-dimensional direct numerical simulations. Simulations for each pressure considered were performed for three different initial turbulence levels at the turbulent Reynolds numbers of 50, 100 and 150. The DNS of expanding spherical flames has taken into account detailed chemical kinetics and preferential diffusion effects. The mixture-averaged transport model has been employed. Effects of pressure on flame structures, heat release rate and radical species distributions under low to high initial turbulent conditions are examined. The results show that elevated pressures greatly influence the cellular flame structure of syngas spherical flames under different initial turbulent conditions. At the atmospheric pressure, the flame shows weakly wrinkling structures due to the initial turbulence level imposed in the simulation. At elevated pressures under turbulence conditions, the flame develops cellular burning structures, superimposed by flame wrinkles due to turbulence. It is shown that highly wrinkled cells that develop over the surface of a spherical flame increase its area and thereby the global propagation speed at elevated pressures. Results show noticeable increases in the local heat release rate with increasing pressure. The analysis also reveals the formation of cusped structures with low heat release rate values in areas of negative curvatures at elevated pressures, in agreement with previous studies. The joint probability density functions of OH radical mass fraction and temperature show broadening OH values in the high temperature zone at elevated pressures compared to its distribution at the atmospheric pressure. Comparisons of mean species distributions of OH and HO2 over temperature between laminar and turbulent flames show that pressure elevation has a major influence on the flame structure in the composition space.

Efficient global wave propagation adapted to 3-D structural complexity: a pseudospectral/spectral-element approach

We present a new, computationally efficient numerical method to simulate global seismic wave propagation in realistic 3-D Earth models. We characterize the azimuthal dependence of 3-D wavefields in terms of Fourier series, such that the 3-D equations of motion reduce to an algebraic system of coupled 2-D meridian equations, which is then solved by a 2-D spectral element method (SEM). Computational efficiency of such a hybrid method stems from lateral smoothness of 3-D Earth models and axial singularity of seismic point sources, which jointly confine the Fourier modes of wavefields to a few lower orders. We show novel benchmarks for global wave solutions in 3-D structures between our method and an independent, fully discretized 3-D SEM with remarkable agreement. Performance comparisons are carried out on three state-of-the-art tomography models, with seismic period ranging from 34 s down to 11 s. It turns out that our method has run up to two orders of magnitude faster than the 3-D SEM, featured by a computational advantage expanding with seismic frequency.

Global adjoint tomography: first-generation model

We present the first-generation global tomographic model constructed based on adjoint tomography, an iterative full-waveform inversion technique. Synthetic seismograms were calculated using GPU-accelerated spectral-element simulations of global seismic wave propagation, accommodating effects due to 3D anelastic crust & mantle structure, topography & bathymetry, the ocean load, ellipticity, rotation, and self-gravitation. Frechet derivatives were calculated in 3D anelastic models based on an adjoint-state method. The simulations were performed on the Cray XK7 named ‘Titan’, a computer with 18,688 GPU accelerators housed at Oak Ridge National Laboratory. The transversely isotropic global model is the result of 15 tomographic iterations, which systematically reduced differences between observed and simulated three-component seismograms. Our starting model combined 3D mantle model S362ANI (Kustowski et al. 2008) with 3D crustal model Crust2.0 (Bassin et al. 2000). We simultaneously inverted for structure in the crust and mantle, thereby eliminating the need for widely used ‘crustal corrections’. We used data from 253 earthquakes in the magnitude range 5.8~ ≤ ~Mw~ ≤ ~7.0. For the first 12 iterations, we combined ∼30 s body-wave data with ∼60 s surface-wave data. The shortest period of the surface waves was gradually decreased, and in the last three iterations we combined ∼17 s body waves with ∼45 s surface waves. We started using 180 min-long seismograms after the 12th iteration and assimilated minor- and major-arc body and surface waves. The 15th iteration model features enhancements of well-known slabs, an enhanced image of the Samoa/Tahiti plume, as well as various other plumes and hotspots, such as Caroline, Galapagos, Yellowstone, and Erebus. Furthermore, we see clear improvements in slab resolution along the Hellenic and Japan Arcs, as well as subduction along the East of Scotia Plate, which does not exist in the starting model. Point-spread function tests demonstrate that we are approaching the resolution of continental-scale studies in some areas, for example underneath Yellowstone. This is a consequence of our multi-scale smoothing strategy, in which we define our smoothing operator as a function of the approximate Hessian kernel, thereby smoothing gradients less wherever we have good ray coverage, such as underneath North America.

ITOUGH2: A multiphysics simulation-optimization framework for analyzing subsurface systems

iTOUGH2 is a simulation-optimization framework for the TOUGH suite of nonisothermal multiphase flow models and related simulators of geophysical, geochemical, and geomechanical processes. After appropriate parameterization of subsurface structures and their properties, iTOUGH2 runs simulations for multiple parameter sets and analyzes the resulting output for parameter estimation through automatic model calibration, local and global sensitivity analyses, data-worth analyses, and uncertainty propagation analyses. Development of iTOUGH2 is driven by scientific challenges and user needs, with new capabilities continually added to both the forward simulator and the optimization framework. This review article provides a summary description of methods and features implemented in iTOUGH2, and discusses the usefulness and limitations of an integrated simulation-optimization workflow in support of the characterization and analysis of complex multiphysics subsurface systems.

Vibrational energy flow analysis of coupled cylindrical thin shell structures

In this study, a method for energy flow analysis was developed to predict the vibrational responses of coupled cylindrical thin shell structures in the medium-to-high frequency ranges. To extend the application of the energy flow model for out-of-plane waves in the thin shell to coupled structures, the wave transmission analyses of general coupled cylindrical thin shell structures are performed. Power reflection and transmission coefficients on the coupled line were calculated using the coupling relationships established for coupled cylindrical thin shells. Using these coefficients, an energy flow analysis in which a junction was considered, was performed for coupled cylindrical thin shell structures. The junction consisted of an arbitrary number of cylindrical thin shells coupled along a junction line. Through numerical simulations, the energy flow solutions of coupled cylindrical thin shell structures were compared with those of classical displacement solutions, and they showed well-developed energy density global propagation and decay patterns.

Neural network classifier optimization using Differential Evolution with Global Information and Back Propagation algorithm for clinical datasets

A Computer-Aided Diagnostic (CAD) system that uses Artificial Neural Network (ANN) trained by drawing in the relative advantages of Differential Evolution (DE), Particle Swarm Optimization (PSO) and gradient descent based backpropagation (BP) for classifying clinical datasets is proposed. The DE algorithm with a modified best mutation operation is used to enhance the search exploration of PSO. The ANN is trained using PSO and the global best value obtained is used as a seed by the BP. Local search is performed using BP, in which the weights of the Neural Network (NN) are adjusted to obtain an optimal set of NN weights. Three benchmark clinical datasets namely, Pima Indian Diabetes, Wisconsin Breast Cancer and Cleveland Heart Disease, obtained from the University of California Irvine (UCI) machine learning repository have been used. The performance of the trained neural network classifier proposed in this work is compared with the existing gradient descent backpropagation, differential evolution with backpropagation and particle swarm optimization with gradient descent backpropagation algorithms. The experimental results show that DEGI-BP provides 85.71% accuracy for diabetes, 98.52% for breast cancer and 86.66% for heart disease datasets. This CAD system can be used by junior clinicians as an aid for medical decision support.

Digital quantum simulation of many-body non-Markovian dynamics

We present an algorithmic method for the digital quantum simulation of many-body locally indivisible non-Markovian open quantum systems. It consists of two parts: firstly, a Suzuki-Lie-Trotter decomposition of the global system propagator into the product of subsystem propagators, which may not be quantum channels, and secondly, an algorithmic procedure for the implementation of the subsystem propagators through unitary operations and measurements on a dilated space. By providing rigorous error bounds for the relevant Suzuki-Lie-Trotter decomposition, we are able to analyze the efficiency of the method, and connect it with an appropriate measure of the local indivisibility of the system. In light of our analysis, the proposed method is expected to be experimentally achievable for a variety of interesting cases.

Hybrid local FEM/global LISA modeling of damped guided wave propagation in complex composite structures

This paper presents a new hybrid modeling technique for the efficient simulation of guided wave generation, propagation, and interaction with damage in complex composite structures. A local finite element model is deployed to capture the piezoelectric effects and actuation dynamics of the transmitter, while the global domain wave propagation and interaction with structural complexity (structure features and damage) are solved utilizing a local interaction simulation approach (LISA). This hybrid approach allows the accurate modeling of the local dynamics of the transducers and keeping the LISA formulation in an explicit format, which facilitates its readiness for parallel computing. The global LISA framework was extended through the 3D Kelvin–Voigt viscoelasticity theory to include anisotropic damping effects for composite structures, as an improvement over the existing LISA formulation. The global LISA framework was implemented using the compute unified device architecture running on graphic processing units. A commercial preprocessor is integrated seamlessly with the computational framework for grid generation and material property allocation to handle complex structures. The excitability and damping effects are successfully captured by this hybrid model, with experimental validation using the scanning laser doppler vibrometry. To demonstrate the capability of our hybrid approach for complex structures, guided wave propagation and interaction with a delamination in a composite panel with stiffeners is presented.

A 1.8 trillion degrees-of-freedom, 1.24 petaflops global seismic wave simulation on the K computer

We present high-performance simulations of global seismic wave propagation with an unprecedented accuracy of 1.2 s seismic period for a realistic three-dimensional Earth model using the spectral element method on the K computer. Our seismic simulations use a total of 665.2 billion grid points and resolve 1.8 trillion degrees of freedom. To realize these large-scale computations, we optimize a widely used community software code to efficiently address all hardware parallelization, especially thread-level parallelization to solve the bottleneck of memory usage for coarse-grained parallelization. The new code exhibits excellent strong scaling for the time stepping loop, that is, parallel efficiency on 82,134 nodes relative to 36,504 nodes is 99.54%. Sustained performance of these computations on the K computer is 1.24 petaflops, which is 11.84% of its peak performance. The obtained seismograms with an accuracy of 1.2 s for the entire globe should help us to better understand rupture mechanisms of devastating earthquakes.