Induced electric fields in MRI settings and electric vestibular stimulations: same vestibular effects?

In Magnetic Resonance Imaging scanner environments, the continuous Lorentz Force is a potent vestibular stimulation. It is nowadays so well known that it is now identified as Magnetic vestibular stimulation (MVS). Alongside MVS, some authors argue that through induced electric fields, electromagnetic induction could also trigger the vestibular system. Indeed, for decades, vestibular-specific electric stimulations (EVS) have been known to precisely impact all vestibular pathways. Here, we go through the literature, looking at potential time varying magnetic field induced vestibular outcomes in MRI settings and comparing them with EVS-known outcomes. To date, although theoretically induction could trigger vestibular responses the behavioral evidence remains poor. Finally, more vestibular-specific work is needed.

Monolithic Catalyst of Ni Foam-Supported MnOx for Boosting Magnetocaloric Oxidation of Toluene.

Catalytic oxidation has been considered an effective technique for volatile organic compound degradation. Development of metal foam-based monolithic catalysts coupling electromagnetic induction heating (EMIH) with efficiency and low energy is critical yet challenging in industrial applications. Herein, a Mn18.2-NF monolithic catalyst prepared by electrodeposition exhibited superior toluene catalytic activity under EMIH conditions, and the temperature of 90% toluene conversion decreased by 89 °C compared to that in resistance furnace heating. Relevant characterizations proved that the skin effect induced by EMIH encouraged activation of gaseous oxygen, leading to superior low-temperature redox properties of Mn18.2-NF under the EMIH condition. In situ Fourier transform infrared spectroscopy results showed that skin effect-induced activation of oxidizing species further accelerated the conversion of intermediates. As a result, the Mn18.2-NF monolithic catalyst under EMIH demonstrated remarkable performance for the toluene oxidation, surpassing the conventional nonprecious metal catalyst and other reported monolithic catalysts.

Is activation of the vestibular system by electromagnetic induction a possibility in an MRI context?

In recent years, an increasing number of studies have discussed the mechanisms of vestibular activation in strong magnetic field settings such as occur in a magnetic resonance imaging scanner environment. Amid the different hypotheses, the Lorentz force explanation currently stands out as the most plausible mechanism, as evidenced by activation of the vestibulo-ocular reflex. Other hypotheses have largely been discarded. Nonetheless, both human data and computational modeling suggest that electromagnetic induction could be a valid mechanism which may coexist alongside the Lorentz force. To further investigate the induction hypothesis, we provide, herein, a first of its kind dosimetric analysis to estimate the induced electric fields at the vestibular system and compare them with what galvanic vestibular stimulation would generate. We found that electric fields strengths from induction match galvanic vestibular stimulation strengths generating vestibular responses. This review examines the evidence in support of electromagnetic induction of vestibular responses, and whether movement-induced time-varying magnetic fields should be further considered and investigated.

Assessment of Triboelectric Nanogenerators for Electric Field Energy Harvesting.

Electric-field energy harvesters (EFEHs) have emerged as a promising technology for harnessing the electric field surrounding energized environments. Current research indicates that EFEHs are closely associated with Tribo-Electric Nano-Generators (TENGs). However, the performance of TENGs in energized environments remains unclear. This work aims to evaluate the performance of TENGs in electric-field energy harvesting applications. For this purpose, TENGs of different sizes, operating in single-electrode mode were conceptualized, assembled, and experimentally tested. Each TENG was mounted on a 1.5 HP single-phase induction motor, operating at nominal parameters of 8 A, 230 V, and 50 Hz. In addition, the contact layer was mounted on a linear motor to control kinematic stimuli. The TENGs successfully induced electric fields and provided satisfactory performance to collect electrostatic charges in fairly variable electric fields. Experimental findings disclosed an approximate increase in energy collection ranging from 1.51% to 10.49% when utilizing TENGs compared to simple EFEHs. The observed correlation between power density and electric field highlights TENGs as a more efficient energy source in electrified environments compared to EFEHs, thereby contributing to the ongoing research objectives of the authors.

Cable Eccentricity Detection Method Based on Magnetic Field.

Amid the rapid advancement of electronic information technology, the need for cable eccentricity measurement in the industry is increasing both in China and across the globe. Current detection methods have several flaws, including high costs, insufficient accuracy, and instability. In this paper, we introduce a magnetic field-based detection method for cable eccentricity that provides high precision and cost-effectiveness. We position three pairs of magnetic field-collection modules in a circular array to gather magnetic flux density information induced by the electrified cable. We apply the law of electromagnetic induction to calculate the cable eccentricity. Our method is non-contact, preserving the cable's integrity. Our method outperforms traditional detection methods, not only in achieving greater accuracy and stability but also in significantly lowering the detection cost. Simulations and experiments show that our method's error rate under specified conditions is 0~4%, with a maximum standard deviation of 0.11, confirming its precision and stability in detecting cable eccentricity. The effectiveness of our method is influenced by two factors: lift-off value and loading current intensity. Our method presents a novel concept and a dependable strategy for the progress of cable eccentricity-detection technology.

Eddy Current Sensor Array for Electromagnetic Sensing and Crack Reconstruction with High Lift-Off in Railway Tracks.

A reliable and efficient rail track defect detection system is essential for maintaining rail track integrity and avoiding safety hazards and financial losses. Eddy current (EC) testing is a non-destructive technique that can be employed for this purpose. The trade-off between spatial resolution and lift-off should be carefully considered in practical applications to distinguish closely spaced cracks such as those caused by rolling contact fatigue (RCF). A multi-channel eddy current sensor array has been developed to detect defects on rails. Based on the sensor scanning data, defect reconstruction along the rails is achieved using an inverse algorithm that includes both direct and iterative approaches. In experimental evaluations, the EC system with the developed sensor is used to measure defects on a standard test piece of rail with a probe lift-off of 4-6 mm. The reconstruction results clearly reveal cracks at various depths and spacings on the test piece.

Design, Development and Application of a Modular Electromagnetic Induction (EMI) Sensor for Near-Surface Geophysical Surveys.

Low-frequency electromagnetic induction (EMI) is a non-invasive geophysical method that is based on the induction of electromagnetic (EM) waves into the subsurface to quantify changes in electrical conductivity. In this study, we present an open (design details and software are accessible) and modular system for the collection of EMI data. The instrument proposed allows for the separations between the transmitter to be adjusted and up to four receiving antennas as well as the acquisition frequency (in the range between 3 and 50 kHz) to permit measurements with variable depth of investigation. The sensor provides access to raw data and the software described in this study allows control of the signal processing chain. The design specifications permit apparent conductivity measurements in the range of between 1 mS/m and 1000 mS/m, with a resolution of 1.0 mS/m and with a sampling rate of up to 10 samples per second. The sensor allows for a synchronous acquisition of a time stamp and a location stamp for each data sample. The sensor has a mass of less than 5 kg, is portable and suitable for one-person operation, provides 4 h of operation time on one battery charge, and provides sufficient rigidity for practical field operations.

Recycling of Ti and Si from Ti-bearing blast furnace slag and diamond wire saw silicon waste by flux alloying technique.

Two industrial solid wastes, Ti-bearing blast furnace slag (TBFS) and diamond wire saw silicon waste (DWSSW), contain large amounts of Ti and Si, and their accumulation wastes resources and intensifies environmental pollution. In the present study, DWSSW was used as the silicon source to reduce titanium oxide in TBFS by electromagnetic induction smelting, and meanwhile Na3AlF6 was added as a flux to improve the recycling of the wastes. Ti and Si of the two wastes were simultaneously recovered in the form of alloy. The effects of different addition amount of Na3AlF6 flux in the mixture of DWSSW and TBFS on chemical composition, viscosity, basicity and structure of slag were investigated. The dissolution behavior of SiO2 in Na3AlF6 flux was theoretically deduced and experimentally verification. The optimized recovery rate of Ti and Si were obtained, and the research realizes the efficient recycling of DWSSW and TBFS simultaneously.

Combined effect of stimulation and electromagnetic induction on absence seizure inhibition in coupled thalamocortical circuits.

Deep brain stimulation (DBS) and electromagnetic induction are new techniques that are increasingly used in modern epilepsy treatments; however, the mechanism of action remains unclear. In this study, we constructed a bidirectional-coupled cortico-thalamic model, based on which we proposed three regulation schemes: isolated regulation of DBS, isolated regulation of electromagnetic induction and combined regulation of the previous two. In particular, we introduced DBS with a lower amplitude and considered the influence of electromagnetic induction caused by the transmembrane current on the membrane potential. The most striking finding of this study is that the three therapeutic schemes could effectively control abnormal discharge, and combined regulation could reduce the occurrence of epileptic seizures more effectively. The present study bridges the gap between the bidirectional coupling model and combined control. In this way, the damage induced by electrical stimulation of the patient's brain tissue could be reduced, and the abnormal physiological discharge pattern of the cerebral cortex was simultaneously regulated by different techniques. This work opens new avenues for improving brain dysfunction in patients with epilepsy, expands ideas for promoting the development of neuroscience and is meaningful for improving the health of modern society and developing the field of science.

Dynamical response of Autaptic Izhikevich Neuron disturbed by Gaussian white noise.

Using the improved memristive Izhikevich neuron model, the effects of autaptic connection as well as electromagnetic induction are studied on the dynamical behavior of neuronal spiking. Using bifurcation analysis for membrane potentials, the effects of autaptic and electromagnetic parameters on the mode transition in electrical activities of the neuron model are investigated. Furthermore, white Gaussian noise is considered in the neuron model, to evaluate the effect of electromagnetic disturbance on the firing pattern of the neuron using the coefficient of variation. The bifurcation diagram versus autaptic conductance and time delay has been extensively studied. The results show that the effects of autaptic connection as well as electromagnetic induction on the spiking behavior of neurons can be well demonstrated by using the Izhikevich model. The electrical activities of the Izhikevich neuron model become more complex when the effects of autaptic connection and electromagnetic induction are considered in the neuron model. Using the Izhikevich neuron model, the high variety of spiking/bursting patterns is represented in the bifurcation diagram of inter-spike interval versus autaptic or electromagnetic parameters. Noise can have distinct effects on the spiking activity of the neuron, for the subthreshold input current, increasing the intensity of the electromagnetic noise increases the regularity of the neuron spiking, but for the suprathreshold input current, the regularity of spiking decreases with noise.

Unveiling the Position Effect of Ce within Layered MnO2 to Prolong the Ambient Removal of Indoor HCHO.

The position of Ce doping has a significant effect on ambient HCHO storage and catalytic oxidation on layered MnO2. By associating structure and performance, it is unveiled that doping Ce into the in-layered lattice of MnO2 is favorable to the generation of high-valence Mn cations, enhancing the oxidizing ability and capacity, but an opposite influence is displayed by interlayered Ce doping. From the aspect of energy minimization calculated by DFT, in-layered Ce doping is also recommended due to the decreased energies for molecule adsorption and oxygen vacancy formation. As a result, in-layered Ce-doped MnO2 displays exceptional activity in catalyzing the deep oxidation of HCHO and a fourfold higher capacity of ambient HCHO storage than pristine MnO2. The optimal oxide is combined with electromagnetic induction heating to complete the "storage-oxidation" cycle as a promising approach absolutely depending on non-noble oxides and household appliances to realize the long-acting removal of indoor HCHO at room temperature.

Characterizing Soil Profile Salinization in Cotton Fields Using Landsat 8 Time-Series Data in Southern Xinjiang, China.

Soil salinization is a major obstacle to land productivity, crop yield and crop quality in arid areas and directly affects food security. Soil profile salt data are key for accurately determining irrigation volumes. To explore the potential for using Landsat 8 time-series data to monitor soil salinization, 172 Landsat 8 images from 2013 to 2019 were obtained from the Alar Reclamation Area of Xinjiang, northwest China. The multiyear extreme dataset was synthesized from the annual maximum or minimum values of 16 vegetation indices, which were combined with the soil conductivity of 540 samples from soil profiles at 0~0.375 m, 0~0.75 m and 0~1.00 m depths in 30 cotton fields with varying degrees of salinization as investigated by EM38-MK2. Three remote sensing monitoring models for soil conductivity at different depths were constructed using the Cubist method, and digital mapping was carried out. The results showed that the Cubist model of soil profile electrical conductivity from 0 to 0.375 m, 0 to 0.75 m and 0 to 1.00 m showed high prediction accuracy, and the determination coefficients of the prediction set were 0.80, 0.74 and 0.72, respectively. Therefore, it is feasible to use a multiyear extreme value for the vegetation index combined with a Cubist modeling method to monitor soil profile salinization at a regional scale.

Low-Pass Filters for a Temperature Drift Correction Method for Electromagnetic Induction Systems.

Electromagnetic induction (EMI) systems are used for mapping the soil's electrical conductivity in near-surface applications. EMI measurements are commonly affected by time-varying external environmental factors, with temperature fluctuations being a big contributing factor. This makes it challenging to obtain stable and reliable data from EMI measurements. To mitigate these temperature drift effects, it is customary to perform a temperature drift calibration of the instrument in a temperature-controlled environment. This involves recording the apparent electrical conductivity (ECa) values at specific temperatures to obtain a look-up table that can subsequently be used for static ECa drift correction. However, static drift correction does not account for the delayed thermal variations of the system components, which affects the accuracy of drift correction. Here, a drift correction approach is presented that accounts for delayed thermal variations of EMI system components using two low-pass filters (LPF). Scenarios with uniform and non-uniform temperature distributions in the measurement device are both considered. The approach is developed using a total of 15 measurements with a custom-made EMI device in a wide range of temperature conditions ranging from 10 °C to 50 °C. The EMI device is equipped with eight temperature sensors spread across the device that simultaneously measure the internal ambient temperature during measurements. To parameterize the proposed correction approach, a global optimization algorithm called Shuffled Complex Evolution (SCE-UA) was used for efficient estimation of the calibration parameters. Using the presented drift model to perform corrections for each individual measurement resulted in a root mean square error (RMSE) of <1 mSm-1 for all 15 measurements. This shows that the drift model can properly describe the drift of the measurement device. Performing a drift correction simultaneously for all datasets resulted in a RMSE <1.2 mSm-1, which is considerably lower than the RMSE values of up to 4.5 mSm-1 obtained when using only a single LPF to perform drift corrections. This shows that the presented drift correction method based on two LPFs is more appropriate and effective for mitigating temperature drift effects.

Classification of Shredded Aluminium Scrap Metal Using Magnetic Induction Spectroscopy.

Recycling aluminium is essential for a circular economy, reducing the energy required and greenhouse gas emissions compared to extraction from virgin ore. A 'Twitch' waste stream is a mix of shredded wrought and cast aluminium. Wrought must be separated before recycling to prevent contamination from the impurities present in the cast. In this paper, we demonstrate magnetic induction spectroscopy (MIS) to classify wrought from cast aluminium. MIS measures the scattering of an oscillating magnetic field to characterise a material. The conductivity difference between cast and wrought makes it a promising choice for MIS. We first show how wrought can be classified on a laboratory system with 89.66% recovery and 94.96% purity. We then implement the first industrial MIS material recovery solution for sorting Twitch, combining our sensors with a commercial-scale separator system. The industrial system did not reflect the laboratory results. The analysis found three areas of reduced performance: (1) metal pieces correctly classified by one sensor were misclassified by adjacent sensors that only captured part of the metal; (2) the metal surface facing the sensor can produce different classification results; and (3) the choice of machine learning algorithm is significant with artificial neural networks producing the best results on unseen data.

Experimental investigation on electromagnetic induction thermal desorption for remediation of petroleum hydrocarbons contaminated soil.

A novel electromagnetic induction low temperature thermal desorption treatment (EMI LTTD) for petroleum hydrocarbons contaminated soil was introduced in this work. The removal rate of total petroleum hydrocarbons (TPH) under various factors, the morphology changes of soils as well as removal mechanism were investigated. Results suggested that increasing the heating temperature significantly increased the removal rate of TPH. At the beginning of 20 min, most of hydrocarbons (93.44-96.91 wt%) was removed with the temperature ranged from 200 °C to 300 °C. Besides, the initial contaminants concentration, particle size and thickness of soil slightly influenced the removal rate of TPH. Desorption kinetic study demonstrated that first-order model was well-described for desorption behavior. Response surface methodology analysis showed the temperature of 216 °C, the residence time of 21 min and the moisture content of 18% was an optimum condition recommended for potentially practical application. Under this condition, the results for the composition of hydrocarbons based on carbon number fractions indicated that the fractions of C10∼C16, C17∼C22 still existed in soil, while C23∼C28 was not detected after EMI LTTD treatment. Proposed mechanism was both hydrocarbons removed by evaporation at any temperature, while parts of heavy hydrocarbons was cracked within the soil close to induction medium, resulting in re-adsorption of light hydrocarbons. A buckwheat germination and growth test indicated that soil treated by EMI LTTD was potential in reutilization for planting.

Dynamic effect of electromagnetic induction on epileptic waveform.

BACKGROUND: Electromagnetic induction has recently been considered as an important factor affecting the activity of neurons. However, as an important form of intervention in epilepsy treatment, few people have linked the two, especially the related dynamic mechanisms have not been explained clearly. METHODS: Considering that electromagnetic induction has some brain area dependence, we proposed a modified two-compartment cortical thalamus model and set eight different key bifurcation parameters to study the transition mechanisms of epilepsy. We compared and analyzed the application and getting rid of memristors of single-compartment and coupled models. In particular, we plotted bifurcation diagrams to analyze the dynamic mechanisms behind abundant discharge activities, which mainly involved Hopf bifurcations (HB), fold of cycle bifurcations (LPC) and torus bifurcations (TR). RESULTS: The results show that the coupled model can trigger more discharge states due to the driving effect between compartments. Moreover, the most remarkable finding of this study is that the memristor shows two sides. On the one hand, it may reduce tonic discharges. On the other hand, it may cause new pathological states. CONCLUSIONS: The work explains the control effect of memristors on different brain regions and lays a theoretical foundation for future targeted therapy. Finally, it is hoped that our findings will provide new insights into the role of electromagnetic induction in absence seizures.

Electrophysiology and the magnetic sense: a guide to best practice.

Magnetoreception, sensing the Earth's magnetic field, is used by many species in orientation and navigation. While this is established on the behavioural level, there is a severe lack in knowledge on the underlying neuronal mechanisms of this sense. A powerful technique to study the neuronal processing of magnetic cues is electrophysiology but, thus far, few studies have adopted this technique. Why is this the case? A fundamental problem is the introduction of electromagnetic noise (induction) caused by the magnetic stimuli, within electrophysiological recordings which, if too large, prevents feasible separation of neuronal signals from the induction artefacts. Here, we address the concerns surrounding the use of electromagnetic coils within electrophysiology experiments and assess whether these would prevent viable electrophysiological recordings within a generated magnetic field. We present calculations of the induced voltages in typical experimental situations and compare them against the neuronal signals measured with different electrophysiological techniques. Finally, we provide guidelines that should help limit and account for possible induction artefacts. In conclusion, if great care is taken, viable electrophysiological recordings from magnetoreceptive cells are achievable and promise to provide new insights on the neuronal basis of the magnetic sense.

Eddy Current Measurement for Planar Structures.

Eddy current (EC) testing has become one of the most common techniques for measuring metallic planar structures in various industrial scenarios such as infrastructures, automotive, manufacturing, and chemical engineering. There has been significant progress in measuring the geometry, electromagnetic properties, and defects of metallic planar structures based on electromagnetic principles. In this review, we summarize recent developments in EC computational models, systems, algorithms, and measurement approaches for planar structures. First, the computational models including analytical models, numerical methods, and plate property estimation algorithms are introduced. Subsequently, the impedance measurement system and probes are presented. In plate measurements, sensor signals are sensitive to probe lift-off, and various algorithms for reducing the lift-off effect are reviewed. These approaches can be used for measureing thickness and electromagnetic properties. Furthermore, defect detection for metallic plates is also discussed.

Effectiveness of Electrostatic Shielding in High-Frequency Electromagnetic Induction Soil Sensing.

High-frequency electromagnetic induction (HFEMI) sensors, operating in the frequency range from 300 kHz to 30 MHz, have been proposed for the measurement of soil electrical conductivity and dielectric permittivity that are related to the physical and chemical properties of soil. Because of the high-frequency operation, the capacitive coupling between the sensor transmitter and receiver coils is comparable to inductive coupling, creating the need for electrostatic shielding. The remnant capacitive coupling after the implementation of shielding can lead to significant difficulties in the sensor signal interpretation, because both coupling mechanisms are highly dependent on the geometry of the HFEMI sensor and applied shield. In this paper, we introduce the discussion on the relationship between the sensor geometry, shielding and the coupling mechanisms for HFEMI soil sensing. We theoretically and experimentally evaluate a typical HFEMI sensor and its shielding in the frequency range of up to 20 MHz and propose a method for evaluating the effectiveness of a shield configuration. In the case study, we experimentally analyze the HFEMI sensor above a saline solution for two shield configurations. The results agree well with the results of a finite element method analysis.

Model-Based Correction of Temperature-Dependent Measurement Errors in Frequency Domain Electromagnetic Induction (FDEMI) Systems.

Data measured using electromagnetic induction (EMI) systems are known to be susceptible to measurement influences associated with time-varying external ambient factors. Temperature variation is one of the most prominent factors causing drift in EMI data, leading to non-reproducible measurement results. Typical approaches to mitigate drift effects in EMI instruments rely on a temperature drift calibration, where the instrument is heated up to specific temperatures in a controlled environment and the observed drift is determined to derive a static thermal apparent electrical conductivity (ECa) drift correction. In this study, a novel correction method is presented that models the dynamic characteristics of drift using a low-pass filter (LPF) and uses it for correction. The method is developed and tested using a customized EMI device with an intercoil spacing of 1.2 m, optimized for low drift and equipped with ten temperature sensors that simultaneously measure the internal ambient temperature across the device. The device is used to perform outdoor calibration measurements over a period of 16 days for a wide range of temperatures. The measured temperature-dependent ECa drift of the system without corrections is approximately 2.27 mSm-1K-1, with a standard deviation (std) of only 30 µSm-1K-1 for a temperature variation of around 30 K. The use of the novel correction method reduces the overall root mean square error (RMSE) for all datasets from 15.7 mSm-1 to a value of only 0.48 mSm-1. In comparison, a method using a purely static characterization of drift could only reduce the error to an RMSE of 1.97 mSm-1. The results show that modeling the dynamic thermal characteristics of the drift helps to improve the accuracy by a factor of four compared to a purely static characterization. It is concluded that the modeling of the dynamic thermal characteristics of EMI systems is relevant for improved drift correction.