Realistic Model Research Articles

Multiscale modeling of neuronal dynamics in hippocampus CA1.

The development of biologically realistic models of brain microcircuits and regions constitutes currently a very relevant topic in computational neuroscience. One of the main challenges of such models is the passage between different scales, going from the microscale (cellular) to the meso (microcircuit) and macroscale (region or whole-brain level), while keeping at the same time a constraint on the demand of computational resources. In this paper we introduce a multiscale modeling framework for the hippocampal CA1, a region of the brain that plays a key role in functions such as learning, memory consolidation and navigation. Our modeling framework goes from the single cell level to the macroscale and makes use of a novel mean-field model of CA1, introduced in this paper, to bridge the gap between the micro and macro scales. We test and validate the model by analyzing the response of the system to the main brain rhythms observed in the hippocampus and comparing our results with the ones of the corresponding spiking network model of CA1. Then, we analyze the implementation of synaptic plasticity within our framework, a key aspect to study the role of hippocampus in learning and memory consolidation, and we demonstrate the capability of our framework to incorporate the variations at synaptic level. Finally, we present an example of the implementation of our model to study a stimulus propagation at the macro-scale level, and we show that the results of our framework can capture the dynamics obtained in the corresponding spiking network model of the whole CA1 area.

Plasmonic structurally colored surfaces with metal film over microsphere lattices

Structural coloring through plasmonic nanostructures involves the manipulation of light interaction with nanostructured metallic surfaces to selectively reflect specific spectral ranges within the visible spectrum. Unlike conventional pigments that absorb light based on their chemical properties, plasmonic nanostructures achieve color through their physical configuration. This study investigates the potential of generating plasmonic structural colors by utilizing self-assembled colloidal microsphere lattices that are coated with thin metal films. Finite-Difference Time-Domain (FDTD) simulations are employed on realistic models to analyze the optical reflectance of dielectric microsphere lattices ranging in sizes from 300 to 700 nm, coated with varying thicknesses (20–200 nm) of different metals (Al, Ag, Au). The reflectance spectra are then translated into specific colors using a software algorithm, with the color representations plotted on CIE1931 diagrams. Furthermore, to validate the theoretical findings, two-dimensional polystyrene microsphere arrays coated with Au and Ag films are prepared, and their reflectance spectra and color images are examined. The resulting plasmonic colors can be adjusted by altering the sphere size, the type of metal used, and the thickness of the coating, demonstrating their potential for diverse color-based applications.

Post-fire structural material behaviour of high- and ultra-high-strength steels – Experimental study and aids for assessment for further use and potential reuse after fires

A thorough understanding and realistic modelling of the essential post-fire material behaviour is crucial for a safe assessment of the residual structural performance of steel components and the reliable further usage of steel structures after fires. This paper presents a comprehensive experimental study of the constitutive material behaviour after heating-cooling cycles of two quenched and tempered high-strength steels (S690QL, S960QL) as well as two thermomechanically rolled steels (S960M, S1100M). The results are compared to both the behaviour of grade S355J2+N mild steels and a comprehensive database of existing post-fire tests. Except for high- and ultra-high-strength steels, which are exposed to very high temperatures above the A1-phase-transformation-temperature during fires, the assumption of reversibility of the mechanical properties for structural designs of steel structures has been confirmed. At high and very high steel temperatures, the microstructure changes and the strength properties after fire are significantly lower than those of virgin high-strength steel specimens. The study thus provides the basis for reliable structural designs and future normative guidance of the post-fire structural steel designs.

The Impact of Foreshore Slope on Cross-Shore Sediment Transport and Sandbar Formation in Beach Berm Nourishment

Foreshore slope is crucial in designing beach berm nourishment schemes and understanding coastal responses to wave forces. Beach berm nourishment often suffers from a high loss rate, necessitating theoretical research and design parameter comparison to mitigate these losses early on. This study uses Bagnold’s energy conservation method and the small-angle approximation method to establish a relationship between cross-shore sediment transport and foreshore slope. The feedback mechanism between these factors shows that when the foreshore slope is fewer than 10 degrees, a smaller initial slope results in a reduced rate of sediment transport. Over time, the foreshore slope decreases and eventually reaches equilibrium, promoting the formation of an offshore sandbar, which helps reduce sediment loss. Using data from Guanhu Beach in Dapeng Bay, this study constructs a realistic numerical beach model to simulate the dynamic behavior of beach profiles with varying foreshore slopes under the influence of monsoon waves and storm surges. The simulation results support the feedback mechanism findings, demonstrating that profiles with minimal foreshore slopes experience the least initial sediment loss, thus facilitating sandbar formation more effectively. These insights can inform beach berm nourishment strategies, emphasizing early-stage efforts to expand beach areas and reduce sediment loss.

Full-waveform automatic location of small seismic events in an underground mine using synthetic strain Greens tensors

A reliable method to locate microseismic evets is an important objective for routine mine seismic monitoring. We developed an algorithm that can automatically and reliably locate an event from a single uniaxial trace. Signals created by microseismic events are recorded as seismograms that consist of direct P- and S-waves as well as the waves reflected off the underground excavations. We take advantage of the extra complexity these reflections introduce as they make the signal more unique. In our investigation we cross-correlated unaltered synthetic seismograms against trial waveforms created from a linear combination of appropriate waveforms from a library of numerically calculated strain Green's tensors. We use a single uniaxial synthetic seismogram to invert for the source location, six moment tensor components, and frequency. The resulting cost functions are constructed as maximal correlations at each node in the mine grid through the true source x-planes. This function is maximized by differential evolution to simultaneously yield the source parameters. Sensitivity tests such as shifting the mine plans and altering the background velocities of the media are investigated to test the robustness of the method. We contaminate the data with 40% white noise to test the resolution against simulated real recorded seismograms. The method is demonstrated using synthetic data calculated with a realistic underground 3D velocity model.

Neural mass modelling for the masses: Democratising access to whole-brain biophysical modelling with FastDMF

Abstract Different whole-brain computational models have been recently developed to investigate hypotheses related to brain mechanisms. Among these, the Dynamic Mean Field (DMF) model is particularly attractive, combining a biophysically realistic model that is scaled up via a mean-field approach and multimodal imaging data. However, an important barrier to widespread usage of the DMF model is that current implementations are computationally expensive, supporting only simulations on brain parcellations that consider less than 100 brain regions. Here, we introduce an efficient and accessible implementation of the DMF model: the FastDMF. By leveraging analytical and numerical advances – including a novel estimation of the feedback inhibition control parameter, and a Bayesian optimization algorithm – the FastDMF circumvents various computational bottlenecks of previous implementations, improving interpretability, performance and memory use. Furthermore, these advances allow the FastDMF to increase the number of simulated regions by one order of magnitude, as confirmed by the good fit to fMRI data parcellated at 90 and 1000 regions. These advances open the way to the widespread use of biophysically grounded whole-brain models for investigating the interplay between anatomy, function, and brain dynamics, and to identify mechanistic explanations of recent results obtained from fine-grained neuroimaging recordings.

Flexible-Center Hat Complete Electrode Model for EEG Forward Problem.

This study aims to develop a more realistic electrode model by incorporating the non-uniform distribution of electrode contact conductance (ECC) and the shunting effects, to accurately solve EEG forward problem (FP). Firstly, a hat function is introduced to construct a more realistic hat-shaped distribution (HD) for ECC. Secondly, this hat function is modified by applying two parameters - offset ratio and offset direction - to account for the variability in ECC's center and to develop the flexible-center HD (FCHD). Finally, by integrating this FCHD into the complete electrode model (CEM) with the shunting effects, a novel flexible-center hat complete electrode model (FCH-CEM) is proposed and used to solve FP. Simulation experiments using a realistic head model demonstrate the necessity of FCH-CEM and its potential to improve the accuracy of the FP solution compared to current models, i.e., the point electrode model (PEM) and CEM. And compared to PEM, it has better performance under coarse mesh conditions (2 mm). Further experiments indicate the significance of considering shunting effects, as ignoring them results in larger errors than coarse mesh when the average contact conductance is large (101S/m2). The proposed FCH-CEM has better accuracy and performance than PEM and complements CEM in finer meshes, making it necessary for coarse meshes. This study proposes a novel model that enhances electrode modeling and FP accuracy, and provides new ideas and methods for future research.

A framework for simulating genotype-by-environment interaction using multiplicative models

Key messageThe simulation of genotype-by-environment interaction using multiplicative models provides a general and scalable framework to generate realistic multi-environment datasets and model plant breeding programmes.Plant breeding has been historically shaped by genotype-by-environment interaction (GEI). Despite its importance, however, many current simulations do not adequately capture the complexity of GEI inherent to plant breeding. The framework developed in this paper simulates GEI with desirable structure using multiplicative models. The framework can be used to simulate a hypothetical target population of environments (TPE), from which many different multi-environment trial (MET) datasets can be sampled. Measures of variance explained and expected accuracy are developed to tune the simulation of non-crossover and crossover GEI and quantify the MET-TPE alignment. The framework has been implemented within the R package FieldSimR, and is demonstrated here using two working examples supported by R code. The first example embeds the framework into a linear mixed model to generate MET datasets with low, moderate and high GEI, which are used to compare several popular statistical models applied to plant breeding. The prediction accuracy generally increases as the level of GEI decreases or the number of environments sampled in the MET increases. The second example integrates the framework into a breeding programme simulation to compare genomic and phenotypic selection strategies over time. Genomic selection outperforms phenotypic selection by ∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim $$\\end{document}50–70% in the TPE, depending on the level of GEI. These examples demonstrate how the new framework can be used to generate realistic MET datasets and model plant breeding programmes that better reflect the complexity of real-world settings, making it a valuable tool for optimising a wide range of breeding methodologies.

Contribution of the cadaveric recirculation system in the anatomical study of lymphatic drainage of the ovary: applications in the management of ovarian cancer.

The present knowledge about lymphatic drainage of the ovary is based on carcinological studies, but it has only rarely been studied under physiological conditions. However, it is one of the preferential routes of dissemination in ovarian cancer, and understanding it is therefore vital for optimal carcinological management.Our purpose was to evaluate the feasibility of an innovative technique to study the lymphatic drainage territories of the ovary using a recirculation module on the cadaveric model. We injected patent blue into the cortex of twenty "revascularised" cadaver ovaries with the Simlife recirculation model. We observed the migration of the dye live and described the drainage territories of each ovary. We observed a staining of the lymphatic vessels and migration of the dye in all the subjects, systematically ipsilateral to the injected ovary. We identified a staining of the lumbo-aortic territory in 65% of cases, with a preferential lateral-caval involvement (60%) for the right ovary and lateral-aortic territory (40%) for the left ovary. A common iliac involvement was observed in only 10% of cases. In 57% of cases, the staining of the lumbo-aortic territory was associated with a staining of the suspensory ligament. The pelvic territory was involved in 50% of cases, with an external iliac staining in 25% of cases and internal in 20%. Our study provides for a better understanding of lymphatic drainage of the ovary using a new detection method, and allows the possibility of improving the teaching for operators with a realistic model. Continuation of this work could lead to considering more targeted and thus less morbid lymph node sampling for lymph node staging in early-stage ovarian cancer.

YOLO-based object detection performance evaluation for automatic target aimbot in first-person shooter games

First-person shooter (FPS) focuses on first-person perspective action gameplay, with gunfights usually giving the player a choice of weapons, significantly impacting how the player approaches or strategies. General military-themed FPS games have realistic models with actual weapons’ shapes and characteristics. This type of game requires high aiming accuracy while using a mouse on a PC. However, not all players have a fast response time in knowing the surrounding situation. New players may need aid when targeting enemies in the FPS world. One popular yet underhanded method is injecting a program code using a dynamic-link library (DLL) to manipulate memory and asset data from the game. Instead of DLL, we promote a novel approach using the player’s real-time game screen, detecting the person without injecting program code into the game. The you only look once (YOLO) algorithm is used as an object detector model since it can process images in real time for up to 45 frames per second. The proposed object detection has an outstanding performance with 65% accuracy, 98% precision, and 61% recall of 51 tests for each game. YOLO’s fastest detection speed produces an average of 35 FPS on the YOLO tiny variant using a mixed precision (half) graphics processing unit (GPU).

Multiphysics framework for cost-effective, long-term monitoring of carbon storage in a carbonate reservoir

We evaluate an effective and cost-efficient multiphysics approach for long-term monitoring of carbon storage in carbonate reservoirs. A key focus of our study is to advocate for a cost-effective, long-term monitoring strategy for carbon storage projects through the integration of surface and borehole multiphysics measurements. By leveraging technologies related to electromagnetic (EM) and gravity methods, we present a framework that addresses the monitoring of the dynamic behavior of injected CO2 over an extended period. The modeling setup integrates realistic static reservoir models with simulated dynamic saturation models to provide results as close as possible to real experimental conditions. Results demonstrate the high sensitivity of EM fields to changes in reservoir CO2 saturation, especially when surface-to-reservoir acquisition configurations are adopted. Additionally, gravity simulations, employing three-axis vector surface gravity measurements and borehole vector gravity, effectively capture density variations over time. Our proposed framework highlights the sequential use of seismic imaging for preinjection site characterization and the transition to EM and gravity surveys for continuous monitoring during and after the injection phases. The multiphysics simulation results performed on realistic carbon storage conditions contribute to the evolving landscape of effective geophysical CO2 monitoring technology for reliable long-term reservoir management.

Ex Vivo Porcine Model for Ureteral Stent Placement Training

Realistic simulation models for interventional radiology procedures are limited, including for placement of double-J ureteral stents (DJSs). Using a porcine kidney and empty saline bag (bladder), an ex vivo model aiming to improve operators’ knowledge and confidence in performing a DJS procedure was developed. Six faculty (J.W., J.L.) and 14 trainees (C.B.O.) successfully operated on the model. Mean results for faculty versus trainees were as follows: 2.2 (SD ± 1.5) versus 2.4 (SD ± 1.5) puncture attempts to access the collecting system (P = .78), 14.5 minutes (SD ± 4.8) versus 15.1 minutes (SD ± 6.0) for insertion time (P = .84), 7.3 minutes (SD ± 2.8) versus 10.3 minutes (SD ± 2.6) for exchange time (P = .04), 8.48 minutes (SD ± 2.0) versus 8.01 minutes (SD ± 2.6) for fluoroscopy time (P = .70), and 5.7 mGy (SD ± 1.6) versus 5.4 mGy (SD ± 2.0) for absorbed air kerma (P = .77). Self-assessed knowledge and confidence with DJS placement increased for all participants following model use.

The Influence of Realistic Mathematics Education on the Mathematical Problem-Solving Ability and Learning Independence of Class V Students at Jarakan State Elementary Schools

<p>This research aims to describe the influence of the realistic mathematic education approach model on students' mathematical problem-solving abilities and define the impact of the realistic mathematic education approach on students' learning independence. The sample used in this research was the VA and VB classes of Jarakan State Elementary School, with 35 students in each class. This type of research is quasi-experimental research. The instruments used in this research were test questions on students' mathematical problem-solving abilities and learning independence questionnaires. The research test carried out by the researcher used a significance level of 5% so that if the significance value is less than 0.05, it can be concluded that the realistic mathematic education approach positively affects students' mathematical problem-solving abilities. The learning independence test can be seen by comparing the total score, mean value, and percentage of the level of student response contained in the descriptive statistical analysis. If the score, mean, and percentage of student response level percentage of the experimental class are higher than the control class, it can be concluded that the realistic mathematic education approach has a positive influence on student learning independence.</p>

Black-box modeling of PMSG-based wind energy conversion systems based on neural ODEs

Abstract Integrating renewable energy sources like wind power into the power grid enhances the dynamic interactions among renewable energy-producing equipment, leading to new technological issues for the power grid. Modeling and simulation are essential to ensure the stability of the emerging power grid, but they require precise dynamic component modeling, which is often unavailable due to technical confidentiality and other factors. Conventional hardware-in-the-loop (HIL) simulation can accurately simulate the dynamics of a single renewable energy device, but not the complex dynamics of multiple devices. This research introduces a method that combines classical mechanism modeling and differential neural network modeling to create accurate wind turbine models utilizing equipment measurement data or HIL simulation data. A realistic wind turbine electromagnetic transient simulation model of a specific type is developed and validated by connecting it to the IEEE-39 node system, confirming the model’s accuracy.

Choosing the right electrode representation for modeling real bioelectronic interfaces: a comprehensive guide

Objective.Producing realistic numerical models of neurostimulation electrodes in contact with the electrolyte and tissue, for use in time-domain finite element method simulations while maintaining a reasonable computational burden remains a challenge. We aim to provide a straightforward experimental-theoretical hybrid approach for common electrode materials (Ti, TiN, ITO, Au, Pt, IrOx) that are relevant to the research field of bioelectronics, along with all the information necessary to replicate our approach in arbitrary geometry for real-life experimental applications.Approach.We used electrochemical impedance spectroscopy (EIS) to extract the electrode parameters in the AC regime under different DC biases. The pulsed electrode response was obtained by fast amperometry (FA) to optimize and verify the previously obtained electrode parameters in a COMSOL Multiphysics model. For optimization of the electrode parameters a constant phase element (CPE) needed to be implemented in time-domain.Main results.We find that the parameters obtained by EIS can be used to accurately simulate pulsed response only close to the electrode open circuit potential, while at other potentials we give corrections to the obtained parameters, based on FA measurements. We also find that for many electrodes (Au, TiN, Pt, and IrOx), it is important to implement a distributed CPE rather than an ideal capacitor for estimating the electrode double-layer capacitance. We outline and provide examples for the novel time-domain implementation of the CPE for finite element method simulations in COMSOL Multiphysics.Significance.An overview of electrode parameters for some common electrode materials can be a valuable and useful tool in numerical bioelectronics models. A provided FEM implementation model can be readily adapted to arbitrary electrode geometries and used for various applications. Finally, the presented methodology for parametrization of electrode materials can be used for any materials of interest which were not covered by this work.

Exploring the process-microstructure-thermal properties relationship of resin-reinforced Ag sintering material for high-power applications via 3D FIB-SEM nanotomography

Resin-reinforced Ag sintering materials represent a promising solution for die-attach applications in high-power devices requiring enhanced reliability and heat dissipation. However, the presence of resin and intricate microstructure poses challenges to its thermal performance, and improvement strategies remain unclear. This work utilizes 3D FIB-SEM nanotomography to reconstruct the microstructure of this material under various process conditions. The analysis reveals that, even with an Ag volume fraction as low as 47.3%, Ag particles form a robust 3D network. Geometric tortuosity quantifies the effect of different sintering conditions on the Ag particle network in all spatial directions. Effective thermal conductivity is simulated based on realistic microstructure models. Results show a significant negative correlation between tortuosity and effective thermal conductivity. Increasing sintering temperature in Model B notably reduces tortuosity and enhances effective thermal conductivity. Sensitivity analysis underscores the dominant role of Ag volume fraction in regulating effective thermal conductivity. Finally, transient thermal impedance measurement of this material as a thin die-attach layer in actual high-power devices demonstrated its application potential. This article strives to explore the relationship between process, microstructure, and thermal properties of this material to provide a reference for further development.

Auditory nerve fiber excitability for alternative electrode placement in the obstructed human cochlea: electrode insertion in scala vestibuli versus scala tympani

Objective. The cochlear implant (CI) belongs to the most successful neuro-prostheses. Traditionally, the stimulating electrode arrays are inserted into the scala tympani (ST), the lower cochlear cavity, which enables simple surgical access. However, often deep insertion is blocked, e.g. by ossification, and the auditory nerve fibers (ANFs) of lower frequency regions cannot be stimulated causing severe restrictions in speech understanding. As an alternative, the CI can be inserted into the scala vestibuli (SV), the other upper cochlear cavity. Approach. In this computational study, the excitability of 25 ANFs are compared for stimulation with ST and SV implants. We employed a 3-dimensional realistic human cochlear model with lateral wall electrodes based on a μ-CT dataset and manually traced fibers. A finite element approach in combination with a compartment model of a spiral ganglion cell was used to simulate monophasic stimulation with anodic (ANO) and cathodic (CAT) pulses of 50 μs. Main results. ANO thresholds are lower in ST (mean/std = μ/σ = 189/55 μA) stimulation compared to SV (μ/σ = 323/119 μA) stimulation. Contrary, CAT thresholds are higher for the ST array (μ/σ = 165/42 μA) compared to the SV array (μ/σ = 122/46 μA). The threshold amplitude depends on the specific fiber-electrode spatial relationship, such as lateral distance from the cochlear axis, the angle between electrode and target ANF, and the curvature of the peripheral process. For CAT stimulation the SV electrodes show a higher selectivity leading to less cross-stimulation of additional fibers from different cochlear areas. Significance. We present a first simulation study with a human cochlear model that investigates an additional CI placement into the SV and its impact on the excitation behavior. Results predict comparable outcomes to ST electrodes which confirms that SV implantation might be an alternative for patients with a highly obstructed ST.

In vivo and dosimetric investigation on electrical vestibular stimulation with frequency- and amplitude-modulated currents

Objective. Normal function of the vestibular system can be disturbed using a noninvasive technique called electrical vestibular stimulation (EVS), which alters a person's sense of balance and causes false sensations of movement. EVS has been widely used to study the function of the vestibular system, and it has recently gained interest as a therapeutic tool to improve postural stability and help those suffering from vestibular dysfunction. Yet, understanding of how EVS stimulates the vestibular system, the current intensity needed to produce an effect and the frequencies at which it occurs have remained unclear.Approach. The effect of EVS on postural sway was examined in five participants using sinusoidal alternating current with time-varying amplitude from 0 to 1.5 mA and frequency from 0.1 to 10 Hz for three electrode configurations. Dosimetry of the current flow inside the head was conducted using anatomically realistic computational models created individually for each subject based on magnetic resonance imaging data. An estimate for the minimal field strength capable of affecting the vestibular system was calculated with the finite element method.Main results. Bipolar EVS at frequencies up to 10 Hz caused harmonic full-body swaying, and the frequency of the sway was the same as that of the stimulation current. The size of the sway was amplified by increasing the current intensity. Dosimetry modeling indicated that, for 0.2 mA current, the average electric field strength in the vestibular system was approximately 10-30 mV m-1, depending on the electrode montage. The size of the measured postural sway was proportional to the montage-specific electric field strength in the vestibular system.Significance. The results provide insight to EVS's working mechanisms and improve its potential as a tool to study the sense of balance.

A numerical study of the scattering in the He-Cu model with a Morse potential: Parabolic manifolds and exponentially small phenomena

We consider the classical approximation of a realistic model for the scattering of He atoms from Cu surfaces. For this problem, modeled by a two-degrees-of-freedom Hamiltonian system, the existence of chaos has been proven analytically very recently for sufficiently large values of the energy, if some quantity, known as the Stokes constant, is non-zero (Borondo et al., 2024). Taking two different and independent approaches, this paper provides numerical evidence that this is indeed the case. Both approaches provide the same value of the non-zero Stokes constant.

A software-agnostic benchmark for DEM simulation of cohesive and non-cohesive materials

Although DEM (Discrete Element Method) was introduced >40 years ago, there are still various challenges in applying it with a certain level of confidence. To develop a realistic material model, calibration, validation, particle shape representation and scaling are well-known challenges that have been studied by various researchers over the past two decades. In addition, once a realistic DEM material model is developed and published in line with open science principles, it is unknown to what extent the calibrated values can be used across software packages. Although a benchmark between 8 open source codes was recently published, it did not cover cohesive materials, rolling friction models, realistic calibrated material behaviour, and commercial software that is widely used in industries.The aim of this study is to investigate the portability of input parameters between different codes and to identify if software independent calibration is possible. We propose a framework to assist DEM users in industry and academia to reach a software independent DEM simulation when required.To compare the results between software packages, the framework considers the following aspects: 1) identical implementation of contact models, 2) single contact modelling, 3) bulk level simulation, and 4) identical post-processing. This framework is demonstrated for two contact models (Hertz-Mindlin and Edinburgh Elasto Plastic Adhesive) with rolling friction model and two commercial software packages (EDEM and PFC) but is applicable for any other (open-source) software. Moreover, two realistic calibrated material models are included to cover a range of material characteristics, from free-flowing incompressible materials to cohesive compressible materials. This study shows that individual particle level simulations give identical results, bulk level simulations show differences for both contact models. In general, users should use parameter values from other software packages with caution, especially where critical or sensitive applications are modelled. This paper also highlights the use of novel computation techniques, such as the GPU engine, to achieve practical computation times when modelling industrial applications.