CutFEM-based MEG forward modeling improves source separability and sensitivity to quasi-radial sources: A somatosensory group study.

Source analysis of magnetoencephalography (MEG) data requires the computation of the magnetic fields induced by current sources in the brain. This so-called MEG forward problem includes an accurate estimation of the volume conduction effects in the human head. Here, we introduce the Cut finite element method (CutFEM) for the MEG forward problem. CutFEM's meshing process imposes fewer restrictions on tissue anatomy than tetrahedral meshes while being able to mesh curved geometries contrary to hexahedral meshing. To evaluate the new approach, we compare CutFEM with a boundary element method (BEM) that distinguishes three tissue compartments and a 6-compartment hexahedral FEM in an n = 19 group study of somatosensory evoked fields (SEF). The neural generators of the 20 ms post-stimulus SEF components (M20) are reconstructed using both an unregularized and a regularized inversion approach. Changing the forward model resulted in reconstruction differences of about 1 centimeter in location and considerable differences in orientation. The tested 6-compartment FEM approaches significantly increase the goodness of fit to the measured data compared with the 3-compartment BEM. They also demonstrate higher quasi-radial contributions for sources below the gyral crowns. Furthermore, CutFEM improves source separability compared with both other approaches. We conclude that head models with 6 compartments rather than 3 and the new CutFEM approach are valuable additions to MEG source reconstruction, in particular for sources that are predominantly radial.

Hidden functional complexity in the flora of an early land ecosystem.

The first land ecosystems were composed of organisms considered simple in nature, yet the morphological diversity of their flora was extraordinary. The biological significance of this diversity remains a mystery largely due to the absence of feasible study approaches. To study the functional biology of Early Devonian flora, we have reconstructed extinct plants from fossilised remains in silico. We explored the morphological diversity of sporangia in relation to their mechanical properties using finite element method. Our approach highlights the impact of sporangia morphology on spore dispersal and adaptation. We discovered previously unidentified innovations among early land plants, discussing how different species might have opted for different spore dispersal strategies. We present examples of convergent evolution for turgor pressure resistance, achieved by homogenisation of stress in spherical sporangia and by torquing force in Tortilicaulis-like specimens. In addition, we show a potential mechanism for stress-assisted sporangium rupture. Our study reveals the deceptive complexity of this seemingly simple group of organisms. We leveraged the quantitative nature of our approach and constructed a fitness landscape to understand the different ecological niches present in the Early Devonian Welsh Borderland flora. By connecting morphology to functional biology, these findings facilitate a deeper understanding of the diversity of early land plants and their place within their ecosystem.

A Self-Temperature Compensation Barometer Based on All-Quartz Resonant Pressure Sensor.

This paper reports a self-temperature compensation barometer based on a quartz resonant pressure sensor. A novel sensor chip that contains a double-ended tuning fork (DETF) resonator and a single-ended tuning fork (SETF) resonator is designed and fabricated. The two resonators are designed on the same diaphragm. The DETF resonator works as a pressure sensor. To reduce the influence of the temperature drift, the SETF resonator works as a temperature compensation sensor, which senses the instantaneous temperature of the DETF resonator. The temperature compensation method based on polynomial fitting is studied. The experimental results show that the accuracy is 0.019% F.S. in a pressure range of 200~1200 hPa over a temperature range of -20 °C~+60 °C. The absolute errors of the barometer are within ±23 Pa. To verify its actual performance, a drone flight test was conducted. The test results are consistent with the actual flight trajectory.

A Combined Magnetoelectric Sensor Array and MRI-Based Human Head Model for Biomagnetic FEM Simulation and Sensor Crosstalk Analysis.

Magnetoelectric (ME) magnetic field sensors are novel sensing devices of great interest in the field of biomagnetic measurements. We investigate the influence of magnetic crosstalk and the linearity of the response of ME sensors in different array and excitation configurations. To achieve this aim, we introduce a combined multiscale 3D finite-element method (FEM) model consisting of an array of 15 ME sensors and an MRI-based human head model with three approximated compartments of biological tissues for skin, skull, and white matter. A linearized material model at the small-signal working point is assumed. We apply homogeneous magnetic fields and perform inhomogeneous magnetic field excitation for the ME sensors by placing an electric point dipole source inside the head. Our findings indicate significant magnetic crosstalk between adjacent sensors leading down to a 15.6% lower magnetic response at a close distance of 5 mm and an increasing sensor response with diminishing crosstalk effects at increasing distances up to 5 cm. The outermost sensors in the array exhibit significantly less crosstalk than the sensors located in the center of the array, and the vertically adjacent sensors exhibit a stronger crosstalk effect than the horizontally adjacent ones. Furthermore, we calculate the ratio between the electric and magnetic sensor responses as the sensitivity value and find near-constant sensitivities for each sensor, confirming a linear relationship despite magnetic crosstalk and the potential to simulate excitation sources and sensor responses independently.

A Dual-Mode Surface Acoustic Wave Delay Line for the Detection of Ice on 64°-Rotated Y-Cut Lithium Niobate.

Ice accumulation on infrastructure poses severe safety risks and economic losses, necessitating effective detection and monitoring solutions. This study introduces a novel approach employing surface acoustic wave (SAW) sensors, known for their small size, wireless operation, energy self-sufficiency, and retrofit capability. Utilizing a SAW dual-mode delay line device on a 64°-rotated Y-cut lithium niobate substrate, we demonstrate a solution for combined ice detection and temperature measurement. In addition to the shear-horizontal polarized leaky SAW, our findings reveal an electrically excitable Rayleigh-type wave in the X+90° direction on the same cut. Experimental results in a temperature chamber confirm capability for reliable differentiation between liquid water and ice loading and simultaneous temperature measurements. This research presents a promising advancement in addressing safety concerns and economic losses associated with ice accretion.

Outcome measures for electric field modeling in tES and TMS: A systematic review and large-scale modeling study.

BACKGROUND: Electric field (E-field) modeling is a potent tool to estimate the amount of transcranial magnetic and electrical stimulation (TMS and tES, respectively) that reaches the cortex and to address the variable behavioral effects observed in the field. However, outcome measures used to quantify E-fields vary considerably and a thorough comparison is missing. OBJECTIVES: This two-part study aimed to examine the different outcome measures used to report on tES and TMS induced E-fields, including volume- and surface-level gray matter, region of interest (ROI), whole brain, geometrical, structural, and percentile-based approaches. The study aimed to guide future research in informed selection of appropriate outcome measures. METHODS: Three electronic databases were searched for tES and/or TMS studies quantifying E-fields. The identified outcome measures were compared across volume- and surface-level E-field data in ten tES and TMS modalities targeting two common targets in 100 healthy individuals. RESULTS: In the systematic review, we extracted 308 outcome measures from 202 studies that adopted either a gray matter volume-level (n = 197) or surface-level (n = 111) approach. Volume-level results focused on E-field magnitude, while surface-level data encompassed E-field magnitude (n = 64) and normal/tangential E-field components (n = 47). E-fields were extracted in ROIs, such as brain structures and shapes (spheres, hexahedra and cylinders), or the whole brain. Percentiles or mean values were mostly used to quantify E-fields. Our modeling study, which involved 1,000 E-field models and > 1,000,000 extracted E-field values, revealed that different outcome measures yielded distinct E-field values, analyzed different brain regions, and did not always exhibit strong correlations in the same within-subject E-field model. CONCLUSIONS: Outcome measure selection significantly impacts the locations and intensities of extracted E-field data in both tES and TMS E-field models. The suitability of different outcome measures depends on the target region, TMS/tES modality, individual anatomy, the analyzed E-field component and the research question. To enhance the quality, rigor, and reproducibility in the E-field modeling domain, we suggest standard reporting practices across studies and provide four recommendations.

An investigation of the effect of brain atrophy on brain injury in multiple sclerosis.

Multiple sclerosis (MS) is a disease of the central nervous system (CNS) that affects the brain and spinal cord. It is estimated that the average prevalence of MS is 35.9 cases per 100,000 and a total of 2.8 million people worldwide have MS. Brain atrophy is usually seen in the early stages of MS, and its progress is faster than healthy people. The present study was a numerical study that uses the Fluid-structure interaction (FSI) model to investigate the effect of brain atrophy on brain injury in MS. Firstly, a healthy model was constructed from MRI images and validated by experimental data. Then three models with different degrees of brain atrophy, which showed the rate of brain atrophy in different years in MS patients, were developed to model the brain atrophy in MS. The models were subjected to two different types of impact conditions. Type I, which only produced a translational motion and the HIC value of 744, was applied to each model. Type II produced both translational and rotational motion. In this type of impact, the experimental kinematics, with peaks of 450 g for the translational acceleration and 26.2 krad/s2 for the rotational acceleration, were applied to the nodes that located in the center of gravity of the head models and the results were extracted from each one. According to the results of impact type I, the pressure of the frontal lobe of the brain is 149,647 Pa in the health model and 137,690 Pa in the model with severe atrophy.

Thermo-mechano-chemical modeling and computation of thermosetting polymers used in post-installed fastening systems in concrete structures.

As thermoset polymers find frequent implementation in engineering design, their application in structural engineering is rather limited. One key reason relies on the ongoing curing process in typical applications such as post-installed adhesive anchors, joints by structural elements or surface-mounted laminates glued by adhesive polymers. Mechanochemistry including curing and aging under thermal as well as mechanical loading causes a multiphysics problem to be discussed. For restricting the variety of material models based on empirical observations, we aim at a thermodynamically sound strategy for modeling thermosets. By providing a careful analysis and clearly identifying the assumptions and simplifications, we present the general framework for modeling and computational implementation of thermo-mechano-chemical processes by using open-source codes.

Biomechanical effects of joint disc perforation on the temporomandibular joint: a 3D finite element study.

BACKGROUND: Disc perforation (DP) is a severe type of Temporomandibular Disorder (TMD). DP may induce changes in the internal stresses of the temporomandibular joint (TMJ). Herein, this study attempts to investigate the biomechanical effects of different positions and sizes of DP on the TMJ using a biomechanical approach, to explore the mechanical pathogenesis of TMD. METHODS: Eleven three-dimensional finite element (FE)models of the TMJ were constructed based on CBCT imaging files of a patient with DP on the left side. These models included the disc with anterior displacement and discs with different locations and sizes of perforations on the affected disc. FE methods were conducted on these models. RESULTS: Anterior displacement of the disc leads to a significant increase in the maxim von Mises stress (MVMS) in both TMJs, with the affected side exhibiting a more pronounced effect. DP occurring at the posterior band and the junction between the disc and the bilaminar region has a greater impact on the MVMS of both TMJs compared to perforations at other locations. As the size of the perforation increases, both sides of the TMJs exhibit an increase in the magnitude of MVMS. CONCLUSIONS: Unilateral disc anterior displacement results in an increased stress on both TMJs. Unilateral DP further affects the stress on both sides of the TMJs. TMD is a progressive condition, and timely intervention is necessary in the early stages to prevent the worsening of the condition.

Patient-specific solution of the electrocorticography forward problem in deforming brain.

Invasive intracranial electroencephalography (iEEG), or electrocorticography (ECoG), measures electric potential directly on the surface of the brain and can be used to inform treatment planning for epilepsy surgery. Combined with numerical modeling it can further improve accuracy of epilepsy surgery planning. Accurate solution of the iEEG forward problem, which is a crucial prerequisite for solving the iEEG inverse problem in epilepsy seizure onset zone localization, requires accurate representation of the patient's brain geometry and tissue electrical conductivity after implantation of electrodes. However, implantation of subdural grid electrodes causes the brain to deform, which invalidates preoperatively acquired image data. Moreover, postoperative magnetic resonance imaging (MRI) is incompatible with implanted electrodes and computed tomography (CT) has insufficient range of soft tissue contrast, which precludes both MRI and CT from being used to obtain the deformed postoperative geometry. In this paper, we present a biomechanics-based image warping procedure using preoperative MRI for tissue classification and postoperative CT for locating implanted electrodes to perform non-rigid registration of the preoperative image data to the postoperative configuration. We solve the iEEG forward problem on the predicted postoperative geometry using the finite element method (FEM) which accounts for patient-specific inhomogeneity and anisotropy of tissue conductivity. Results for the simulation of a current source in the brain show large differences in electric potential predicted by the models based on the original images and the deformed images corresponding to the brain geometry deformed by placement of invasive electrodes. Computation of the lead field matrix (useful for solution of the iEEG inverse problem) also showed significant differences between the different models. The results suggest that rapid and accurate solution of the forward problem in a deformed brain for a given patient is achievable.

Modeling of High-Power Tonpilz Terfenol-D Transducer Using Complex Material Parameters.

The loss effect in smart materials, the active part of a transducer, is of significant importance to acoustic transducer designers, as it directly affects the important characteristics of the transducer, such as the impedance spectra, frequency response, and the amount of heat generated. It is therefore beneficial to be able to incorporate energy losses in the design phase. For high-power low-frequency transducers requiring more smart materials, losses become even more appreciable. In this paper, similar to piezoelectric materials, three losses in Terfenol-D are considered by introducing complex quantities, representing the elastic loss, piezomagnetic loss, and magnetic loss. The frequency-dependent eddy current loss is also considered and incorporated into the complex permeability of giant magnetostrictive materials. These complex material parameters are then successfully applied to improve the popular plane-wave method (PWM) circuit model and finite element method (FEM) model. To verify the accuracy and effectiveness of the proposed methods, a high-power Tonpilz Terfenol-D transducer with a resonance frequency of around 1 kHz and a maximum transmitting current response (TCR) of 187 dB/1A/µPa is manufactured and tested. The good agreement between the simulation and experimental results validates the improved PWM circuit model and FEA model, which may shed light on the more predictable design of high-power giant magnetostrictive transducers in the future.

Mixing Rules for an Exact Determination of the Dielectric Properties of Engine Soot Using the Microwave Cavity Perturbation Method and Its Application in Gasoline Particulate Filters.

In recent years, particulate filters have become mandatory in almost all gasoline-powered vehicles to comply with emission standards regarding particulate number. In contrast to diesel applications, monitoring gasoline particulate filters (GPFs) by differential pressure sensors is challenging due to lower soot masses to be deposited in the GPFs. A different approach to determine the soot loading of GPFs is a radio frequency-based sensor (RF sensor). To facilitate sensor development, in previous work, a simulation model was created to determine the RF signal at arbitrary engine operating points. To ensure accuracy, the exact dielectric properties of the soot need to be known. This work has shown how small samples of soot-loaded filter are sufficient to determine the dielectric properties of soot itself using the microwave cavity perturbation method. For this purpose, mixing rules were determined through simulation and measurement, allowing the air and substrate fraction of the sample to be considered. Due to the different geometry of filter substrates compared to crushed soot samples, a different mixing rule had to be derived to calculate the effective filter properties required for the simulation model. The accuracy of the determined mixing rules and the underlying simulation model could be verified by comparative measurements on an engine test bench.

Design and Shape Optimization of Strain Gauge Load Cell for Axial Force Measurement for Test Benches.

The load cell is an indispensable component of many engineering machinery and industrial automation for measuring and sensing force and torque. This paper describes the design and analysis of the strain gauge load cell, from the conceptional design stage to shape optimization (based on the finite element method (FEM) technique) and calibration, providing ample load capacity with low-cost material (aluminum 6061) and highly accurate force measurement. The amplifier circuit of the half Wheatstone bridge configuration with two strain gauges was implemented experimentally with an actual load cell prototype. The calibration test was conducted to evaluate the load cell characteristics and derive the governing equation for sensing the unknown load depending on the measured output voltage. The measured sensitivity of the load cell is approximately 15 mV/N and 446.8 µV/V at a maximum applied load of 30 kg. The findings are supported by FEM results and experiments with an acceptable percentage of errors, which revealed an overall error of 6% in the worst situation. Therefore, the proposed load cell meets the design considerations for axial force measurement for the laboratory test bench, which has a light weight of 20 g and a maximum axial force capacity of 300 N with good sensor characteristics.

Numerical investigation of blood flow and red blood cell rheology: the magnetic field effect.

In this study, the motion and deformation of a red blood cell in a Poiseuille flow through microvessels under the effect of a uniform transverse magnetic field is comprehensively investigated to get a better insight into blood hemorheology. The rheology of the RBC and the surrounding blood flow are examined numerically in two dimensions using a Finite Element Method. It is essential to know that the flow patterns of blood change in the presence of an RBC. The simulation results demonstrate that the magnetic field has significant influence on the flow stream and the behavior of the RBC, including the motion and the cells deformation.

Reconstructing subcortical and cortical somatosensory activity via the RAMUS inverse source analysis technique using median nerve SEP data.

This study concerns reconstructing brain activity at various depths based on non-invasive EEG (electroencephalography) scalp measurements. We aimed at demonstrating the potential of the RAMUS (randomized multiresolution scanning) technique in localizing weakly distinguishable far-field sources in combination with coinciding cortical activity. As we have shown earlier theoretically and through simulations, RAMUS is a novel mathematical method that by employing the multigrid concept, allows marginalizing noise and depth bias effects and thus enables the recovery of both cortical and subcortical brain activity. To show this capability with experimental data, we examined the 14-30 ms post-stimulus somatosensory evoked potential (SEP) responses of human median nerve stimulation in three healthy adult subjects. We aim at reconstructing the different response components by evaluating a RAMUS-based estimate for the primary current density in the nervous tissue. We present source reconstructions obtained with RAMUS and compare them with the literature knowledge of the SEP components and the outcome of the unit-noise gain beamformer (UGNB) and standardized low-resolution brain electromagnetic tomography (sLORETA). We also analyzed the effect of the iterative alternating sequential technique, the optimization technique of RAMUS, compared to the classical minimum norm estimation (MNE) technique. Matching with our previous numerical studies, the current results suggest that RAMUS could have the potential to enhance the detection of simultaneous deep and cortical components and the distinction between the evoked sulcal and gyral activity.

AC measurements and simulations of hepatic radiofrequency ablation.

INTRODUCTION: The radiofrequency ablation (RFA) of liver cancer is a desirable treatment option, as it is minimally invasive. An accurate numerical simulation can greatly help physicians better plan their surgical protocols. Previously, the displacement current in the RFA process was considered negligible, and therefore RFA simulation was modeled as a direct current (DC) system instead of an alternating current (AC) system. Our study investigated the hypothesis that the displacement current in the RFA process should not always be considered negligible. METHODS: AC measurements of ex vivo bovine liver ablation were performed, and numerical simulations were also conducted to test the hypothesis that the relative permittivity would significantly decrease after the liver tissue reached a high temperature. RESULTS: The displacement current was observed to be a sizable fraction of the conduction current, especially before the onset of the first pause. The simulation results indicated that the relative permittivity is likely to decrease to several hundred or lower at elevated temperatures. CONCLUSIONS: Our study results suggest that the DC model may be inadequate, especially before the first roll-off and that additional information could be available during RFA treatment by considering the AC nature of RFA, which could lead to improved numerical simulation. Additional measurements of tissue parameters are needed to reach the full potential of the AC model for further development of ablation control.

Water-cooled microwave ablation array for bloodless rapid transection of the liver.

BACKGROUND: Microwaves (MWs) deliver relatively high temperatures into biological tissue and cover a large ablation zone. This study aims to evaluate the efficacy and effectiveness of water-cooled double-needle MW ablation arrays in assisting the hepatic transection of an in vivo pig model. METHODS: Our research program comprised computer modeling, tissue-mimicking phantom experiments, and in vivo pig liver experiments. Computer modeling was based on the finite element method (FEM) to evaluate ablation temperature distributions. In tissue-mimicking phantom and in vivo pig liver ablation experiments, the performances of the water-cooled MW ablation array and conventional clamp crushing liver resection were compared. RESULTS: FEM showed that the maximum lateral ablation diameter at 100 W output and a duration of 60 s was 3 cm (assessed at 50 °C isotherm). In the phantom, the maximum transverse ablation diameter of the double-needle MW ablation increased rapidly to 3 cm in 60 s at 50 W. The blood loss and blood loss per transection area in Group A were significantly lower than those in Group B (18 (7-26) ml vs. 34 (19-57) ml, and 2.4 (2-3.1) ml/cm2 vs. 6.9 (3.2-8.3) ml/cm2, respectively) (p < 0.05). The transection speed in Group A (2.6(1.9-3.8) cm2/min) was significantly faster than that in Group B (1.7(1.1-2.2) cm2/min) (p < 0.05). CONCLUSION: In this experimental model, the new water-cooled MW array-assisted liver resection (LR) has the potential advantage of less blood loss and rapid removal than the conventional LR.

Laser fabrication of structural bone: surface morphology and biomineralization assessment.

The current work explores the surface morphology of the laser-ablated bone using Yb-fiber coupled Nd:YAG laser (λ = 1064 nm) in continuous wave mode. As the laser-ablated region contains physiochemically modified carbonized and nonstructural region, it becomes unknown material for the body. Thus, biomineralization on such a laser-ablated region was assessed by in vitro immersion test in noncellular simulated body fluid. The presence of hydroxyapatite was detected in the precipitated mineral product using scanning electron microscopy equipped with energy dispersive spectroscopy, and X-ray diffraction analysis. The effect of varying laser parameters on distribution of surface morphology features was identified and its corresponding effect on biomineralization was studied.

Numerical Analysis and Experimental Verification of Damage Identification Metrics for Smart Beam with MFC Elements to Support Structural Health Monitoring.

This paper investigates damage identification metrics and their performance using a cantilever beam with a piezoelectric harvester for Structural Health Monitoring. In order to do this, the vibrations of three different beam structures are monitored in a controlled manner via two piezoelectric energy harvesters (PEH) located in two different positions. One of the beams is an undamaged structure recognized as reference structure, while the other two are beam structures with simulated damage in form of drilling holes. Subsequently, five different damage identification metrics for detecting damage localization and extent are investigated in this paper. Overall, each computational model has been designed on the basis of the modified First Order Shear Theory (FOST), considering an MFC element consisting homogenized materials in the piezoelectric fiber layer. Frequency response functions are established and five damage metrics are assessed, three of which are relevant for damage localization and the other two for damage extent. Experiments carried out on the lab stand for damage structure with control damage by using a modal hammer allowed to verify numerical results and values of particular damage metrics. In the effect, it is expected that the proposed method will be relevant for a wide range of application sectors, as well as useful for the evolving composite industry.

A Systematic Design Optimization Approach for Multiphysics MEMS Devices Based on Combined Computer Experiments and Gaussian Process Modelling.

This paper presents a systematic and efficient design approach for the two degree-of-freedom (2-DoF) capacitive microelectromechanical systems (MEMS) accelerometer by using combined design and analysis of computer experiments (DACE) and Gaussian process (GP) modelling. Multiple output responses of the MEMS accelerometer including natural frequency, proof mass displacement, pull-in voltage, capacitance change, and Brownian noise equivalent acceleration (BNEA) are optimized simultaneously with respect to the geometric design parameters, environmental conditions, and microfabrication process constraints. The sampling design space is created using DACE based Latin hypercube sampling (LHS) technique and corresponding output responses are obtained using multiphysics coupled field electro-thermal-structural interaction based finite element method (FEM) simulations. The metamodels for the individual output responses are obtained using statistical GP analysis. The developed metamodels not only allowed to analyze the effect of individual design parameters on an output response, but to also study the interaction of the design parameters. An objective function, considering the performance requirements of the MEMS accelerometer, is defined and simultaneous multi-objective optimization of the output responses, with respect to the design parameters, is carried out by using a combined gradient descent algorithm and desirability function approach. The accuracy of the optimization prediction is validated using FEM simulations. The behavioral model of the final optimized MEMS accelerometer design is integrated with the readout electronics in the simulation environment and voltage sensitivity is obtained. The results show that the combined DACE and GP based design methodology can be an efficient technique for the design space exploration and optimization of multiphysics MEMS devices at the design phase of their development cycle.