Layered Model Research Articles

Surface-Related Multiples Elimination for Waterborne GPR Data

Ground-penetrating radar (GPR) is a well-respected, effective, and efficient geophysical technique. However, for underwater engineering detection and underwater archaeology, the measured B-scan profiles typically contain surface-related multiple waves, which can reduce the signal to noise ratio and interfere with the interpretation of results. SRME is a feedback iteration method based on wave equation, which is frequently utilized in marine seismic explorations but very rarely in GPR underwater engineering detection. To fill this gap, we applied SRME to suppress multiples that appear in GPR underwater images. When we compared the effectiveness of the underwater horizontal layered model and the underwater undulating interface model, we found a high match rate between the predicted and the real-world multiples. In addition, the addition of the Gaussian random noise level with a 4% maximum amplitude to the B-scan profile of the horizontal stratified model yielded satisfactory multiple suppression results. Finally, we applied this method to the B-scan GPR section of actual underwater archaeological images to achieve multiple suppression, which can more effectively weaken and inhibit the surface-related multiples. Both numerical simulations and actual field data show that the SRME method is highly suitable for interpreting waterborne GPR data, and more accurate interpretation can be obtained from the GPR profile after multiples suppression.

Application of The Triple Layered Business Model Canvas in Corporate Social Responsibility: Systematic Literature Review

Application of The Triple Layered Business Model Canvas in Corporate Social Responsibility: Systematic Literature Review

Electronic Interpretation of Interlayer Energy Landscape in Layered Materials

AbstractThe interlayer energy landscape of layered materials is essential to disassemble their structure–property relationships. However, a clear definition of interlayer electronic coupling that generally rules the interlayer energy landscape for their outstanding electronic and tribological properties, remains a matter of debate. Herein, diverse methods for electron coupling are evaluated to discriminate their feasibility to interpret interlayer sliding energy landscape for frictional sliding or stacking faults, by using density functional theory calculation of the layered models in the case of transition metal dichalcogenides (TMDs). It is discovered that the charge density evolution in dynamic stacking configurations dictates the interlayer energy landscape along the sliding pathway, challenging the prevailing belief that the energy corrugation arises from the nonuniform distribution of charge density or the charge density in the interface region. The present studies may open the way to disassemble the electron coupling principle underlying interlayer energy landscape for structure–property relationships as stacking faults, registry effects, even superlubric behavior in layered structures.

Classification of colorectal cancer consensus molecular subtypes using attention-based multi-instance learning network on whole-slide images

Colorectal cancer (CRC) is the third most common and second most lethal cancer globally. It is highly heterogeneous with different clinical-pathological characteristics, prognostic status, and therapy responses. Thus, the precise diagnosis of CRC subtypes is of great significance for improving the prognosis and survival of CRC patients. Nowadays, the most commonly used molecular-level CRC classification system is the Consensus Molecular Subtypes (CMSs). In this study, we applied a weakly supervised deep learning method, named attention-based multi-instance learning (MIL), on formalin-fixed paraffin-embedded (FFPE) whole-slide images (WSIs) to distinguish CMS1 subtype from CMS2, CMS3, and CMS4 subtypes, as well as distinguish CMS4 from CMS1, CMS2, and CMS3 subtypes. The advantage of MIL is training a bag of the tiled instance with bag-level labels only. Our experiment was performed on 1218 WSIs obtained from The Cancer Genome Atlas (TCGA). We constructed three convolutional neural network-based structures for model training and evaluated the ability of the max-pooling operator and mean-pooling operator on aggregating bag-level scores. The results showed that the 3-layer model achieved the best performance in both comparison groups. When compared CMS1 with CMS234, max-pooling reached the ACC of 83.86 % and the mean-pooling operator reached the AUC of 0.731. While comparing CMS4 with CMS123, mean-pooling reached the ACC of 74.26 % and max-pooling reached the AUC of 0.609. Our results implied that WSIs could be utilized to classify CMSs, and manual pixel-level annotation is not a necessity for computational pathology imaging analysis.

A comprehensive mechanistic model of adipocyte signaling with layers of confidence

Adipocyte signaling, normally and in type 2 diabetes, is far from fully understood. We have earlier developed detailed dynamic mathematical models for several well-studied, partially overlapping, signaling pathways in adipocytes. Still, these models only cover a fraction of the total cellular response. For a broader coverage of the response, large-scale phosphoproteomic data and systems level knowledge on protein interactions are key. However, methods to combine detailed dynamic models with large-scale data, using information about the confidence of included interactions, are lacking. We have developed a method to first establish a core model by connecting existing models of adipocyte cellular signaling for: (1) lipolysis and fatty acid release, (2) glucose uptake, and (3) the release of adiponectin. Next, we use publicly available phosphoproteome data for the insulin response in adipocytes together with prior knowledge on protein interactions, to identify phosphosites downstream of the core model. In a parallel pairwise approach with low computation time, we test whether identified phosphosites can be added to the model. We iteratively collect accepted additions into layers and continue the search for phosphosites downstream of these added layers. For the first 30 layers with the highest confidence (311 added phosphosites), the model predicts independent data well (70–90% correct), and the predictive capability gradually decreases when we add layers of decreasing confidence. In total, 57 layers (3059 phosphosites) can be added to the model with predictive ability kept. Finally, our large-scale, layered model enables dynamic simulations of systems-wide alterations in adipocytes in type 2 diabetes.

Seismic wave propagation analysis in the framework of generalized continuum mechanics theory

For the problems of seismic wave propagation, scale effects will appear while considering the microstructures of medium. Scale effects mean that new components of wave fields appear in the seismograms due to the microstructure interactions in the medium and vary with the change of the characteristic length scale parameters. The generalized continuum mechanics (GCM) theory which introduces the intrinsic length scales of the microstructures is suitable for analyzing the scale effects of seismic wave propagation. We adopt the concept of multi-scale microstructure interactions, that is, the modified couple stress theory, and the one-parameter second strain gradient theory, as two branches of the GCM theory, have the same definition characteristic length scale parameters of medium, to describe the microstructure interactions at different scales. Through the quantitative relationship between the characteristic length scale parameters of the medium and the micropore, the layered model of the characteristic length scale parameters of the micropore is constructed for numerical modeling in a unified framework, and the scale effects of seismic wave propagation is analyzed. More specifically, the asymmetric elastic wave equations under a unified framework are derived, and the physical definition of the characteristic length scale parameters of medium is given. And the influence of the characteristic length scale parameter of the micropore on the seismic wave propagation is focused on. Finally, the scale effects of seismic waves excited by high-speed trains under the viaduct system are analyzed, and some conclusions are drawn.

Analysis of layered information dissemination model and caching strategy in Social Internet of Things

In recent years, the social Internet of Things (SIoT) and its applications have developed rapidly and introduced convenience to people’s lives. In view of the massive amount of information generated by the SIoT, it is necessary to model and analyze the communication among smart devices and study the impact of social attributes of smart devices on information dissemination. Therefore, in this study, we propose a layered information dissemination model for SIoT that abstracts the communication process in SIoT as the information dissemination process among nodes, describes the process of wireless communication in SIoT using the microscopic Markov chain method, and derives the information dissemination threshold based on theoretical analyses. In addition, this study proposes a dynamic cache strategy considering the influence of social attributes, such as user interestingness, information popularity, and the interaction between messages on communication. Finally, the correctness of the model and propagation threshold and the effectiveness of the caching strategy are verified by simulation experiments in artificial networks and real networks.

Mechanistic Code for Asphalt Pavements Loaded by Farming Vehicles

Farming vehicles are relatively heavy and slow-moving machines, typically equipped with rubber tracks or flotation tires (or both). The objective of this study was to develop, validate, and openly share a new mechanistic code for calculating asphalt pavement responses under the loading conditions of such vehicles. For a given farming vehicle, the loading geometry was modeled by exploiting symmetry considerations and representing tread contact areas as groups of rotated rectangular patches. For the purpose of calculating responses, the pavement system was modeled as a layered elastic half-space, loaded vertically by many small identical circular areas—collectively approximating the patches. Computational efficiency was sought by solving the layered model for one circular area and executing a series of coordinate transformations, interpolations, and translations, to represent the entire vehicle loading. The new code is named LynFarm; it was validated through its ability to reproduce mechanical responses generated by farming vehicles as they were driven over an instrumented asphalt pavement section. LynFarm is openly shared on GitHub for further verification, validation, and improvement by the pavement engineering community.

Numerical Simulations of Carbon Dioxide Storage Efficiency in Heterogeneous Reservoir Models

The U.S. Department of Energy’s National Energy Technology Laboratory (DOE-NETL) has been developing methods and tools (the online Carbon Dioxide Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN) tool) to estimate carbon dioxide (CO2) storage potential in subsurface reservoirs. The CO2 storage efficiency terms are input in the tool to calculate storage potential in targeted reservoirs. In this effort, two CO2 storage efficiency terms were evaluated: volumetric displacement ( E V ) and microscopic displacement ( E d ). The first term deals with efficiency of CO2 propagation into an accessible reservoir volume, while the second term evaluates effectiveness of native fluid displacement with CO2. The interpreted well logs and core sample measurements were applied to create the heterogeneous reservoir models including geostatistical realizations of porosity and intrinsic permeability fields. Supercritical CO2 was injected over the course of 30 years into brine-saturated reservoir models for clastics, limestone, and dolomite lithologies and deltaic fluvial, aeolian, shallow marine, and reef depositional environments by means of varying reservoir parameters and injection scenarios. The reservoir models providing vertically heterogeneous petrophysical properties and designated as “layered reservoir models” (with homogeneous parameters along each layer of the model) were not determined to be a transition between the homogeneous and heterogeneous models in respect to storage efficiency. Another finding shows that high-efficiency factors do not necessarily mean increased CO2 storage; they rather indicate that the available volume and pore space are more fully utilized. The CO2 storage efficiency factors were evaluated dynamically at the select time points using P 10 ‐ P 50 ‐ P 90 percentiles. The results of this study show that the P 10 ‐ P 90 distribution for volumetric efficiency is wider when compared to the microscopic efficiency. It was found that where dominant buoyancy forces drive the plume to the top of a target formation, the volumetric efficiency is low. Tighter sandstone and carbonate formations show prevalence of capillary forces and better utilization of reservoir volume.

Suppressing the Eddy Current Damping of the Permanent Magnet Linear Synchronous Motor by Setting the Toothed Cooling Plate

To enhance the linear motor thrust density, scholars have focused extensively on cooling systems. Conventional cooling plates induce eddy current damping in the time-varing magnetic field, decreasing the dynamic characteristics of the motor. Therefore, a toothed cooling plate is proposed, which effectively reduces the metal water-cooled plate’s eddy current damping and has good heat dissipation capacity. The layered model is used to determine the damping of the cooling plate covered on the armature, and the factors affecting the damping are concluded. Eddy currents on the cooling plate are vectorized in this structure via laser cutting. On the basis of the model, a scheme with a secant spacing of 1/3 pole pitch is chosen, then a comparison of three different structural types follows. The variation characteristics of their damping are described in detail. Finally, the thermal network model analysis and the temperature rise experiment are conducted to summarize the heat dissipation characteristics of the toothed cooling structure.

Characteristics of Internal Solitary Waves in the Timor Sea Observed by SAR Satellite

Internal solitary waves (ISWs) with features such as large amplitude, short period, and fast speed have great influence on underwater thermohaline structure, nutrient transport, and acoustic signal propagation. The characteristics of ISWs in hotspot areas have been revealed by satellite images combined with mooring observation. However, the ISWs in the Timor Sea, which is located in the outflow of the ITF, have not been studied yet and the characteristics are unrevealed. In this study, by employing the Synthetic Aperture Radar (SAR) images taken by the Sentinel-1 satellite from 2017 to 2022, the temporal and spatial distribution characteristics of ISWs in the Timor Sea are analyzed. The results show that most of ISWs appear in Bonaparte basin and its vicinity. The average wavelength of the ISWs is 248 m, and most of the wave lengths are less than 400 m. The peak line of ISWs is longer in deeper water. The underwater structures of two typical ISWs are reconstructed based on the Korteweg–de Vries (KdV) equation combined with mooring observation. This shows that, compared with the two-layer model, the continuous layered model is more suitable for reconstructing the underwater structures of ISWs. Further analysis shows that both the rough topography and the spring-neap tides contribute to the generation of ISWs in the Timor Sea. This study fills a gap in knowledge of ISWs in regional seas, such as the Timor Sea.

Modeling Crustal Structure in the Permian Basin by Waveform‐Matching P Receiver Functions and Autocorrelograms With Particle Swarm Optimization

AbstractWe model basin and Moho structure in the Permian Basin region of west Texas and southeastern New Mexico using a method for waveform matching via global optimization of P‐to‐S receiver functions, vertical autocorrelograms, and horizontal autocorrelograms. The algorithm is driven by Particle Swarm Optimization, whose search history can be used to assess the strength of data constraints on model parameters. A common drawback in receiver function modeling is the need to assume a value for Vp before Vs and layer thickness can be estimated. But constraints on Vp can be provided by vertical autocorrelograms of teleseismic arrivals, which detect reverberating P waves, because the phase delay times depend only on Vp and interface depth. P‐to‐S receiver functions and vertical and radial autocorrelograms are computed for M > 5.5 events at 30°–100° epicentral distance, then edited and binned by ray parameter. Synthetic seismograms are computed for layered models using a 1D reflectivity method. The free parameters in the algorithm include basin depth, basin Vp, basin Vp/Vs, and thickness and Vp/Vs of the crystalline crust. Where vertical autocorrelograms prove insufficient for determining basin Vp, Vp is assumed from nearby stations that were modeled successfully. We find an average basin Vp of 4.57 km/s and basin depths to ∼8 km. Moho depths are generally 40–48 km. A basin depth of at least 3.5 km is typically needed to produce sufficient phase separation to allow an average Vp to be determined with confidence. Modeling autocorrelograms jointly with receiver functions therefore improves constraints on deep basin structure.

Optimization framework for splitting DNN inference jobs over computing networks

Ubiquitous artificial intelligence (AI) is considered one of the key services in 6G systems. AI services typically rely on deep neural network (DNN) requiring heavy computation. Hence, in order to support ubiquitous AI, it is crucial to provide a solution for offloading or distributing computational burden due to DNN, especially at end devices with limited resources. We develop an optimization framework for assigning the tasks of DNN layer computations to computing resources in the network, so as to reduce the inference latency. To this end, we propose a layered graph model with which simple conventional routing jointly solves the problem of selecting nodes for computation and paths for data transfer between nodes. We show that using our model, the existing approaches to splitting DNN layer computations can be equivalently reformulated as a routing problem that possesses better numerical properties. We also apply the proposed framework to derive algorithms for minimizing the end-to-end inference latency. We show through numerical evaluations that our new formulation can find a solution for DNN inference job distribution much faster than the existing formulation, and that our algorithms can select computing nodes and data paths adaptively to the computational attributes of given DNN inference jobs.

Periodic surface loading using GRACE data for a layered viscoelastic earth model based on a direct relationship between geoid and displacement

SUMMARY Loading theory is fundamental in explaining deformation resulting from surface mass changes. Although various theoretical methods, including the classical elastic loading theory by W. E. Farrell and I. M. Longman, have been proposed, a viscoelasticity-based theory may be required to address long timescale loading problems, such as annual and interannual deformation, as well as longer timescale loading effects. In this study, we use a semi-analytical approach to simulate the continuous periodic loading deformation of a viscoelastic, spherical, layered earth model with linear rheology profiles. We provide a series of formulas in the spectral domain for the spatiotemporal displacement, which establish connections between mass, geoid and displacement solely through the utilization of complex Love numbers and Stokes coefficients, thereby circumventing the need for viscoelastic Green's function. Using our newly proposed method, we investigate the viscoelastic loading deformation caused by annual cyclic mass loading, considering both steady-state creep and additional transient creep with a wide range of viscosities. The results indicate that when utilizing steady-state viscosity values constrained by GIA data, the viscoelastic effect is not evident in the annual cyclic load deformation. However, incorporating the Burgers model with transient creep mainly constrained by post-seismic deformation influences the amplitude and phase of the annual cyclic loading, highlighting the role of rheology. Furthermore, we observe that the horizontal displacement in periodic load deformation exhibits a higher sensitivity to the viscosity of the model compared to the geoid and vertical displacement, regardless of the rheological model used.

An efficient algebraic multi-resolution sampling approach to 3-D magnetotelluric modelling

SUMMARY Since electromagnetic (EM) fields diffuse more smoothly to greater depth, it physically makes sense to apply fine discretization to model structure at near surface with an increasingly coarser grid both in horizontal and vertical directions as the depth increases for the numerical solution of EM fields. For finite-difference magnetotelluric (MT) forward modelling on regular staggered grids, this can lead to difficulties in discretizing the curl–curl equation governing the EM diffusion in the earth at regions, where the grid resolution changes. In this paper, we propose an efficient algebraic multi-resolution sampling (MRS) method for MT forward modelling. In this method, we do not require the generation of physical subgrids and merely subsample the field components. The coefficient matrix for the subsampled components can be obtained by matrix multiplication based on the initial linear system of equations and field interpolation. To guarantee divergence-free current during the iterative solution process at low frequencies, which is considered crucial for the development of efficient iterative solvers, our forward modelling is based a regularization equation obtained by augmenting the curl–curl equation with an equivalent scaled grad–div operator for electrical fields (explicitly enforcing the divergence-free condition). The correctness of our algebraic MRS algorithm is examined based on a layered model. Its stability and efficiency is exploited by comparing our results with the forward modelling on unsampled staggered grids for the Dublin Test Model 1 (DTM1) and a complex model with realistic topography, indicating a time reduction of about 42–82 per cent.

A collagen-based layered chronic wound biofilm model for testing antimicrobial wound products.

A new in vitro chronic wound biofilm model was recently published, which provided a layered scaffold simulating mammalian tissue composition on which topical wound care products could be tested. In this paper, we updated the model even further to mimic the dynamic influx of nutrients from below as is the case in a chronic wound. The modified in vitro model was created using collagen instead of agar as the main matrix component and contained both Staphylococcus aureus and Pseudomonas aeruginosa. The model was cast in transwell inserts and then placed in wound simulating media, which allowed for an exchange of nutrients and waste products across a filter. Three potential wound care products and chlorhexidine digluconate 2% solution as a positive control were used to evaluate the model. The tested products were composed of hydrogels made from completely biodegradable starch microspheres carrying different active compounds. The compounds were applied topically and left for 2-4 days. Profiles of oxygen concentration and pH were measured to assess the effect of treatments on bacterial activity. Confocal microscope images were obtained of the models to visualise the existence of microcolonies. Results showed that the modified in vitro model maintained a stable number of the two bacterial species over 6 days. In untreated models, steep oxygen gradients developed and pH increased to >8.0. Hydrogels containing active compounds alleviated the high oxygen consumption and decreased pH drastically. Moreover, all three hydrogels reduced the colony forming units significantly and to a larger extent than the chlorhexidine control treatment. Overall, the modified model expressed several characteristics similar to in vivo chronic wounds.

A layered beam-based model for analyzing the stress of rolling shear for the cross-laminated timber panels under out-of-plane bending

When used as horizontal components to carry vertical loads, such as floors and beams, the design of cross-laminated timber (CLT) panels is driven by out-of-plane bending. In this case, rolling shear is always one of the major concerns that governs the performances of ultimate limit state of CLT members. Analytical models are available for predicting the shear capacity of CLT panels, but they are computational extensive and cannot provide the longitudinal distribution of shear stress which is necessary to predict where the failure will happen. In this paper, a layered beam-based analytical model, for analyzing the stress of rolling shear for transversely loaded CLT members was developed. The model deems that the shear deformations of out-of-plane bending CLT members are carried by cross layers while the deformations of bending moment are carried by parallel layers. Based on the layered beam theory, the equation that governs the stress of rolling shear and its analytical solution were derived. It was found that the shear stress distribution in CLT longitudinal direction obeys exponential law and the maximum shear stress is located at the end of the CLT member. Formulas to predict the shear capacity for 3- and 5-layer CLT panels under out-of-plane bending were obtained. The proposed method was validated by the experimental data generated by the authors and by other researchers. Comparing to the shear analogy method and Gamma method, the proposed method requires less computational work and provides similar accuracy.

Asymptotic linearized inversion for acoustic variable-tilt transversely isotropic media through elliptic perturbation analysis

The linearized inverse scattering problem for acoustic variable-tilt transversely isotropic (TTI) media is studied. In depicting the acoustic anisotropy behavior of the TTI medium with the P-wave normal moveout velocity (NMO) Vn, density ρ, and anisotropic parameters δ and η, a single-scattering procedure of NMO pressure wavefields is developed through elliptical perturbation analysis. By high-frequency approximation, the singly scattered pressure field is naturally related with an acoustic TTI generalized Radon transform (GRT), in which the TTI scattering patterns are explicitly expressed. We asymptotically invert for the multiple material parameters of an acoustic TTI medium via constructing the GRT backprojection operator. The effectiveness of the proposed approach is demonstrated on the layered model, and its superiority over the traditional acoustic isotropic and VTI GRT inversion methods is illustrated on the overthrust model.

Using a mixed layered soil model to optimize the layout of coastal direct current (DC) grounding electrodes

Abstract In recent years, with the rapid development of the coastal economy and the large-scale development of marine resources, power demand has risen sharply. So it is urgent to promote the construction of UHVDC projects. Coastal saline areas often contain more chloride and other salts than other inland areas due to the high humidity, salinity and light intensity of the marine climatic and environmental conditions, which lead to the different electrical performance of grounding electrodes under different layouts. Therefore, one of the key issues to realizing the rapid development of UHVDC in coastal countries is how to choose the best layout of the coastal DC grounding electrode. It is intended to simulate the coastal environment and establish a mixed stratified soil model using CDEGS to verify the validity of the model through experiments in this paper. Based on the mixed soil model, the changes in grounding resistance, surface potentials and step voltage of grounding electrode sites under zigzag shape, two-row and circular shapes layouts are studied. The results show that when the zigzag shape layout is selected, the ground potential amplitude of the grounding electrode is reduced by 45.77% and 42.7%, the step voltage amplitude is decreased by 39.85% and 32.22%, and the grounding resistance is decreased by 28.45% and 27.68%, compared with the two-row and circular layout. In addition, its utilization rate of electrodes is better than the other two layout shapes.

SLF/ELF Fields From VED Solved by Normalized Spherical Harmonic Functions

AbstractElectromagnetic (EM) fields excited by a vertical electric dipole (VED) at the super‐low frequency and the extremely low frequency have been widely used in different studies such as space weather, earthquake predictions, geophysical investigations, and communications. Accurate and efficient algorithms are necessary for quick estimations of worldwide EM fields. This study proposes a recursive algorithm to calculate EM fields excited by a VED embedded in a layered spherical model. A set of local/general reflection and transmission coefficients is defined to describe propagations of EM fields in each spherical layer and the outgoing‐type waves and the standing‐type waves of EM fields are expressed by normalized spherical Bessel/Hankel functions. The normalized spherical Bessel/Hankel functions are not only useful to overcome the overflow problem in calculations of spherical Bessel/Hankel functions but also helpful to speed up the convergence of summation expressions of EM fields, because the normalized spherical Bessel/Hankel functions mitigate small oscillations terms. Calculating the primary fields and the secondary fields of the total EM fields, respectively, is also helpful to reach convergent summations, because their convergence radiuses are different.