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.

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.

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.

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.

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.

Dynamical effects of memristive electromagnetic induction on a 2D Wilson neuron model.

Electromagnetic induction plays a crucial impact on the firing activity of biological neurons, since it exists along with the mutual effect between membrane potential and ions transport. Flux-controlled memristor is an available candidate in characterizing the electromagnetic induction effect. Different from the previously reported literature, a non-ideal flux-controlled memristor with cosine mem-conductance function is employed to determine the periodic magnetization and leakage flux processes in neurons. Thereafter, a three-dimensional (3D) memristive Wilson (m-Wilson) neuron model is constructed under the consideration of this kind of electromagnetic induction. Numerical simulations are performed by multiple numerical tools, which demonstrate that the 3D m-Wilson neuron model can generate abundant firing activities. Interestingly, coexisting firing activities, antimonotonicity, and firing frequency regulation are discovered under special parameter settings. Furthermore, a PCB-based analog circuit is designed and hardware measurements are executed to verify the numerical simulations. These explorations in numerical and hardware surveys might provide insights to regulate the firing activities by appropriate electromagnetic induction.

Research on the Mechanical, Thermal and Induction Healing Properties of Asphalt Wearing Course with Steel Fibers.

Induction healing technology can effectively repair microcracks in asphalt mixtures and is a promising maintenance technology for asphalt pavements. However, it requires the addition of steel wool fibers to asphalt mixtures and cannot be directly used to repair existing pavements. In order to improve the practicality of the induction healing technology, this article designs a wearing course asphalt mixture with induction healing function that is going to be paved above the existing road surface. The AC-10 asphalt wearing course for induction heating was prepared by adding steel fiber (SF). Analysis of the overall temperature of the surface revealed the unevenness of the temperature distribution, and the healing properties were investigated through protective heating that controlled the maximum temperature of the upper surface. The results show that the addition of SF can improve the high-temperature stability, low-temperature and intermediate-temperature crack resistance, and moisture stability of asphalt wearing courses; however, it has adverse effects on volumetric performance and skid resistance. The heating temperature increases with the increase in SF content, but higher maximum temperature heating rate causes worse heating uniformity and lower healing effect. The maximum heating rate of the sample with 10% SF reaches 3.92 °C/s, while its heating rate at minimum temperature is similar to that of the sample with 6% SF, which is only 0.7 °C/s, indicating the worst heating uniformity. The best healing effect occurs when the maximum temperature of the upper surface reaches 160 °C. The recommended optimal SF content is 6% of the asphalt volume. The asphalt mixture with 6% SF has an appropriate volume performance, moisture stability, and skid resistance; additionally, it has the best high-temperature stability, as well as low-temperature and intermediate-temperature crack resistance. Meanwhile, it also has uniform temperature distribution and efficient healing efficiency.

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.

"Tumor Treating Fields" delivered via electromagnetic induction have varied effects across glioma cell lines and electric field amplitudes.

Previous studies reported that alternating electric fields (EFs) in the intermediate frequency (100-300 kHz) and low intensity (1-3 V/cm) regime - termed "Tumor Treating Fields" (TTFields) - have a specific, anti-proliferative effect on glioblastoma multiforme (GBM) cells. However, the mechanism(s) of action remain(s) incompletely understood, hindering the clinical adoption of treatments based on TTFields. To advance the study of such treatment in vitro, we developed an inductive device to deliver EFs to cell cultures which improves thermal and osmolar regulation compared to prior devices. Using this inductive device, we applied continuous, 200 kHz electromagnetic fields (EMFs) with a radial EF amplitude profile spanning 0-6.5 V/cm to cultures of primary rat astrocytes and several human GBM cell lines - U87, U118, GSC827, and GSC923 - for a duration of 72 hours. Cell density was assessed via segmented pixel densities from GFP expression (U87, U118) or from staining (astrocytes, GSC827, GSC923). Further RNA-Seq analyses were performed on GSC827 and GSC923 cells. Treated cultures of all cell lines exhibited little to no change in proliferation at lower EF amplitudes (0-3 V/cm). At higher amplitudes (> 4 V/cm), different effects were observed. Apparent cell densities increased (U87), decreased (GSC827, GSC923), or showed little change (U118, astrocytes). RNA-Seq analyses on treated and untreated GSC827 and GSC923 cells revealed differentially expressed gene sets of interest, such as those related to cell cycle control. Up- and down-regulation, however, was not consistent across cell lines nor EF amplitudes. Our results indicate no consistent, anti-proliferative effect of 200 kHz EMFs across GBM cell lines and thus contradict previous in vitro findings. Rather, effects varied across different cell lines and EF amplitude regimes, highlighting the need to assess the effect(s) of TTFields and similar treatments on a per cell line basis.

Wireless electrochemiluminescent biosensors: Powering innovation with smartphone technology.

Energy supply and sensor response acquisition can be performed wirelessly, enabling biosensors as Internet of Thing (IoT) tools by linking wireless power supply and electrochemical sensors. Here, we used the electromagnetic induction method to clarify the conditions under which electrochemiluminescence is induced by a simple potential modulation circuit without an integrated circuit on the electrode chip that receives the power. Initially, the potential waveform obtained in a circuit with inductance and capacitance components that resonate with the transmission frequency and a diode for rectification was investigated to clarify the conditions inducing an electrochemiluminescence reaction at the printed electrode. A high-sensitivity complementary metal-oxide semiconductor camera built into the smartphone wirelessly detected the luminescence generated on the electrode chip. The images were quantitatively evaluated using open-source image analysis software which determine the sensitivity of detecting hydrogen peroxide. Glucose oxidase (GOD) encapsulated in a matrix of chitosan polymers and photocrosslinkable polymers was immobilized on a mass-producible and inexpensive printed electrode to maintain high activity. The immobilized membrane suppressed luminescence when immobilized on the working electrode; therefore, the enzyme was immobilized on the counter electrode for glucose measurement over a wide concentration. Thus, luminol electrochemiluminescence was induced on the electrode chip by wireless power supply from a smartphone. Human serum and artificial sweat samples were tested and indicated possibility for actual applications. In this way a fully wireless biosensor was developed with potential as an IoT biosensor.

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.

Effect of the electromagnetic induction in the electrical activity of the Kazantsev model of inferior Olive Neuron model.

In this paper, based on the four variables Kazantsev et al. inferior olive neuron (ION) dynamic equations, a five variables neuron model is designed to describe the effect of electromagnetic induction in ION activities. Within the new ION model, the effect of magnetic flow on membrane potential is described by imposing additive memristive current in the master block of the Kasantsev et al. neuron model. The impact of magnetic flux on the stability of equilibrium point is studied. Hopf bifurcation and bifurcation diagram indicated that, as the electromagnetic field strength parameter changes, the value of the critical point also changes. Furthermore, as the electromagnetic induction is increasing, there is appearance of bursting dynamic in the slave subsystem and an increase in the spike amplitude of the master subsystem. In addition, the analog circuit of the master block confirms the observed results from numerical simulation.

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.

Effect of electromagnetic induction drying on the drying-incineration process of dyeing sludge: focus on migration and conversion of sulfur.

Secondary sulfur pollution in dyeing sludge (DS) during drying and incineration is a major environmental problem necessitating in-situ control. To robustly immobilise sulfur during drying-incineration, the authors introduce an electromagnetic induction (EMI) drying method and reveal the corresponding migration and conversion of sulfur in DS. The EMI-drying efficiency reached 10.69%/min, five times that of thermal drying. EMI drying increases the relative sulfoxide ratio from that of thermal drying. In a sludge-sulfur model, the proposed treatment promoted the oxidation and decomposition of organic sulfur without noticeably affecting the inorganic sulfur. The selective oxidation process during EMI drying promotes sulfur stabilisation in dried DS, decreasing the performance and stability of DS combustion. The sulfur-containing pollutants released during the incineration of DS mainly contain H2S, followed by CH3SH and SO2. EMI drying increases the outputs of SO2 and CH3SH but decreases the outputs H2S and total sulfur compared with the outputs of thermal drying. Under the sulfur-model conditions, EMI promoted the conversion of inorganic sulfur to sulfur-containing gases (especially H2S) during incineration. In contrast, the sulfur stabilised by partial oxidation of organic sulfur in the EMI-dried DS was not easily converted to gaseous sulfur during subsequent combustion. Overall, EMI inhibits the release of sulfur during the combined drying-incineration process of DS.

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.

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.

Maximizing RDF recovery potential through the integration of electrical resistivity tomography and frequency-domain electromagnetic surveys for waste characterization in open dump mining.

Open dumping is a widespread waste management technique used in developing countries. This approach is simple and economical but has numerous environmental and health impacts. Open dump mining (ODM) can reduce waste in both open and controlled dumpsites by converting waste into refuse-derived fuel (RDF) for energy generation; however, before ODM implementation, the waste's characteristics and composition must be assessed. Geophysical surveys are widely used to characterize waste. The electrical resistivity tomography (ERT) method is a particularly common technique for determining waste composition, but it has several limitations. Therefore, a frequency-domain electromagnetic (FDEM) survey was used in this study as a pre-screening tool to evaluate the waste composition and overcome the limitations of ERT surveys. This study aimed to determine the relationship between geophysical data types (i.e., ERT and FDEM) and the optimal waste composition for RDF production and assess the ability of FDEM surveys to identify areas with RDF recovery potential. This study combined ERT and FDEM surveys with waste sample analysis in old/new controlled dumpsites in Thailand. The quantitative and qualitative correlations between the geophysical data (i.e., resistivity, conductivity, waste composition, and moisture content (MC)) were then assessed using linear and multiple linear regression analysis. Integrating geophysical surveys was found to have the potential to locate optimal RDF recovery areas, with low conductivity (0-100 mS/m) and high resistivity (>55 Ω·m) characteristics associated with areas of high RDF content (>40 % by weight). An unexpected finding was that increased waste age resulted in increased resistivity and decreased conductivity. Additionally, the MC depended on factors affecting spatial variability (e.g., precipitation and biodegradation). Overall, this study demonstrates that integrating ERT and FDEM surveys is a suitable pre-screening tool to evaluate waste characteristics and composition, mitigate ERT survey limitations, and improve waste investigation before ODM.

Wireless Electrical Signals Induce Functional Neuronal Differentiation of BMSCs on 3D Graphene Framework Driven by Magnetic Field.

Bone marrow mesenchymal stem cells (BMSCs) are suggested as candidates for neurodegeneration therapy by autologous stem cells to overcome the lack of neural stem cells in adults. However, the differentiation of BMSCs into functional neurons is a major challenge for neurotherapy. Herein, a methodology has been proposed to induce functional neuronal differentiation of BMSCs on a conductive three-dimensional graphene framework (GFs) combined with a rotating magnetic field. A wireless electrical signal of about 10 µA can be generated on the surface of GFs by cutting the magnetic field lines based on the well-known electromagnetic induction effect, which has been proven to be suitable for inducing neuronal differentiation of BMSCs. The enhanced expressions of the specific genes/proteins and apparent Ca2+ intracellular flow indicate that BMSCs cultured on GFs with 15 min/day rotating magnetic field stimulation for 15 days can differentiate functional neurons without any neural inducing factor. The animal experiments confirm the neural differentiation of BMSCs on GFs after transplantation in vivo, accompanied by stimulation of an external rotating magnetic field. This study overcomes the lack of autologous neural stem cells for adult neurodegeneration patients and provides a facile and safe strategy to induce the neural differentiation of BMSCs, which has potential for clinical applications of neural tissue engineering.

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.

Research on the Heating Process of CFRP Circular Tubes Based on Electromagnetic Induction Heating Method.

Based on the electromagnetic induction heating method, heating and curing of Carbon Fiber Reinforced Polymer (CFRP) have the advantages of high energy utilization and no pollution. However, in the heating process, both the material weaving structure and mold material can affect the temperature field. Therefore, in this study, an electromagnetic heating finite element analysis model for CFRP circular tubes was established based on the equivalent electromagnetic thermal characteristics of CFRP. The study investigated the temperature rise mechanism of the material weaving structure under the magnetic field, and explored in-depth the influence of molds made of 45# steel and glass fiber-reinforced plastic (FRP) on the heating process of CFRP. The CFRP circular tubes with weaving structures of 89-degree winding angle, 45-degree winding angle, and plain weave were studied. The study found that when the metal mold was heated, the CFRP structure had almost no effect on the temperature distribution. However, when the glass fiber-reinforced plastic mold was heated, the temperature field changed with the CFRP structure, and the more fiber cross points, the more uniform the temperature field. The accuracy of the finite element model was verified through experiments. The aim of this research is to provide theoretical guidance for actual industrial production.