EM Data Research Articles

High-resolution imaging of sedimentary bauxite deposits and structural controls on mineralization in western Guangxi province based on efficient 3-D TEM observation and inversion

Bauxite plays a crucial role in metallic and non-metallic industry. The surface-exposed salento-type bauxite deposits have been largely exploited and developed. With the increasing demand of these resources, it is important but very challenging to explore the potential bauxite deposits in the deep earth. In this paper, based on new developments in transient electromagnetic (TEM) technologies, we conducted explorations of the sedimentary bauxite in Dengli-Tianyanggumei and Dajia mining areas in western Guangxi province. To achieve a fast and high-resolution inversion, we adopt an array-based observation strategy for large-scale 3-D TEM and collect EM data inside and outside the transmitting loop. Compared to traditional TEM surveys, the observation strategy can quickly acquire the data for large-scale surveys and improve the data acquisition efficiency by more than 25 times. We then use a 3-D inversion algorithm to estimate the underground conductivity structure and analyze the distribution of the sedimentary bauxite. To do that, we discretize the undulating surface and transmitter-receiver locations with unstructured grids and employ the finite-element and quasi-Newton methods to achieve high-resolution imaging of subsurface electrical structures. Since the observation strategy greatly reduces the number of transmitters, the efficiency of 3-D EM inversions can be significantly improved. Experiments over two mining areas show that our inversions can clearly recover the underground resistivities. The inferred burial depth and spatial distribution of the sedimentary bauxite are in agreement with the drilling data. By combining ERT results and geological data, we illustrate the impact of faults on the spatial distribution of potential sedimentary bauxite deposits.

AI-based optimization of EM radiation estimates from GSM base stations using traffic data

The fast expansion of mobile networks has sparked worries regarding base station EM radiation's health impacts. Traffic load is commonly ignored when evaluating EM radiation levels using maximum power output. This study proposes utilizing AI and ML on real network traffic data to optimize GSM base station EM radiation estimations. We obtained EM radiation measurements and traffic data from selecting GSM base stations by location and configuration. To predict EM radiation levels, traffic patterns were used to train linear regression, random forests, and neural networks. Base stations were clustered by radiation profile using unsupervised learning. Considering regulatory restrictions and measurement feasibility, an optimization methodology was created to minimize EM radiation estimate inaccuracy. The results show better prediction accuracy than power-based estimations and high generalisability across base station types. Site-specific factors influenced daily EM radiation patterns after clustering. EM radiation levels can be monitored using traffic data and the optimized AI/ML model. This research helps telecom operators and regulators analyze EM radiation more accurately and efficiently. Future projects should include 5G and small cell network extensions and intelligent city platform integration. The suggested method develops data-driven, AI-powered Public Safety and mobile network trust solutions.

Bridging the Gap between Electronic Monitoring Policy and Practice: From the Perspective of Chinese Tuna Longliners

Electronic monitoring systems (EMSs) have been widely used in global fishing vessels as an effective tool to obtain reliable information about catches and fishing operations in order to verify compliance with national and international regulations. Though EMS implementation in tuna vessels has not yet been made a mandatory requirement by tuna regional fisheries management organizations, many Chinese longliners have the system on board for traceability and safety purposes. Based on interviews with managers and skippers on Chinese tuna longliners, this paper firstly identifies the challenges in electronic monitoring management that have hindered fishermen’s confidence to implement EMS at a larger scale. Then this paper proposes a work plan to facilitate EMS implementation from the perspective of Chinese tuna longliners, in which the adoption of EM standards, specifications, and procedures, and identification of EM data fields are the top priorities. To fully address concerns raised by tuna longliners, a cloud computing platform for EMS data storage, transmission, and review could help to protect data safety and confidentiality. Artificial intelligence technology is recommended to increase cost-efficiency in data review procedures, in addition to compliance incentives and financial incentives from policy makers.

Contrasting packing modes for tubular assemblies in chlorosomes

The largest light-harvesting antenna in nature, the chlorosome, is a heterogeneous helical BChl self-assembly that has evolved in green bacteria to harvest light for performing photosynthesis in low-light environments. Guided by NMR chemical shifts and distance constraints for Chlorobaculum tepidum wild-type chlorosomes, the two contrasting packing modes for syn-anti parallel stacks of BChl c to form polar 2D arrays, with dipole moments adding up, are explored. Layered assemblies were optimized using local orbital density functional and plane wave pseudopotential methods. The packing mode with the lowest energy contains syn-anti and anti-syn H-bonding between stacks. It can accommodate R and S epimers, and side chain variability. For this packing, a match with the available EM data on the subunit axial repeat and optical data is obtained with multiple concentric cylinders for a rolling vector with the stacks running at an angle of 21° to the cylinder axis and with the BChl dipole moments running at an angle ß ∼ 55° to the tube axis, in accordance with optical data. A packing mode involving alternating syn and anti parallel stacks that is at variance with EM appears higher in energy. A weak cross-peak at -6 ppm in the MAS NMR with 50 kHz spinning, assigned to C-181, matches the shift of antiparallel dimers, which possibly reflects a minor impurity-type fraction in the self-assembled BChl c.

Impacts of Terrain Conductivity Survey for Groundwater Investigation in a Typical Sedimentary Formation; A Case Study of Itori, South-West Nigeria

A geophysical investigation for groundwater development involving conductivity measurement using Electromagnetic profiling was conducted to locate fractured and fissured zones and associated groundwater containing media at Itori communities, Southwestern Nigeria. The area is underlain by the typical sedimentary rocks of South-West, Nigeria with the local geology predominantly clay, shale, clay sand, limestone and Sandstone. Measurements of the ground conductivity were carried out with Geonics EM 34-3 along 5 traverses whose profile lengths varied between 160 and 200 m. Intensive geophysical fieldworks were performed utilizing Frequency Domain Electromagnetic Method (FDEM) using Geonics-EM-34 to determine the vertical and lateral variations of subsurface conductivity probing depths of 20 m, 40 m and 60 m. The EM data were acquired at 500 m intervals along 10 profiles. The Vertical Dipole Moment in the first layer exhibited the highest true conductivity and lowest true conductivity of 42.65 mS/m and 29.1 mS/m for EMITO1 and EMITO2 respectively and the corresponding Horizontal Dipole Moment exhibited the highest true conductivity of 36.0 mS/m and 25.41 mS/m for EMITO1 alongside EMITO2 and EMITO8 respectively while the Vertical Dipole Moment in the second layer exhibited the highest true conductivity of 45.62 mS/m and lowest true conductivity of 34.76 mS/m for EMITO1 and EMITO8 respectively and the corresponding Horizontal Dipole Moment exhibited the highest true conductivity of 44.0 mS/m and lowest true conductivity of 36.3 mS/m for EMITO3 and EMITO8 respectively. The qualitative interpretation of EM results identified areas of hydrogeologic importance and forms a predictive and suggestive basis for Vertical Electrical Sounding (VES) investigation; points of positive EM anomalies were considered as priority area for electrical resistivity sounding and prospective groundwater development, since they suggest lithological variations within the unconsolidated overburden and/or water–filled fissures in the bedrock. The identified major geological interfaces were suspected to be of weathered zones

Study on the space field reconstruction method of the radial basis function of electromagnetic radiation under optimal parameters

ABSTRACT Electromagnetic radiation (EM) pollution has a certain impact on human life and health, and the reconstruction of the EM space field in this paper is of great practical significance for EM analysis and research. The radial basis function (RBF) sufficiently considers the influence of each sampling point and is more suitable for reconstructing the EM space field than other spatial interpolation methods. Currently, when RBF is used to reconstruct the EM space field, the optimal determination of the basis function and shape parameter (SP) is rarely considered. This ultimately leads to low reconstruction accuracy of the EM space field. Therefore, in this paper, the particle swarm optimization (PSO) is used to calculate the optimal SP of the RBF. On this basis, reliable EM space field reconstruction is performed, which helps people understand the EM distribution characteristics in actual situations from a visual perspective. The EM sampling data of a region on the Yunnan Normal University campus are used as the data source, and the RBF under the optimal parameters is used for EM reconstruction. The accuracy of its interpolation results is evaluated and compared and analyzed with inverse distance weighting (IDW) after distance index optimization. The results show that the RBF under optimal parameters reconstructs the EM space field with high accuracy and good effect, which can truly reflect the actual distribution of EM.

Bayesian Inversion of Frequency-Domain Airborne EM Data With Spatial Correlation Prior Information

Bayesian Inversion of Frequency-Domain Airborne EM Data With Spatial Correlation Prior Information

Generation and study of the synthetic brain electron microscopy dataset for segmentation purpose

Advanced microscopy technologies such as electron microscopy have opened up a new field of vision for biomedical researchers. The use of artificial intelligence methods for processing EM data is largely difficult due to the small amount of annotated data at the training stage. Therefore, we add synthetic images to an annotated real EM dataset or use a fully synthetic training dataset. In this work, we present an algorithm for the synthesis of 6 types of organelles. Based on the EPFL dataset, a training set of 1161 real fragments 256×256 (ORG) and 2000 synthetic ones (SYN), as well as their combination (MIX), were generated. The experiment of training models for 6, 5-classes and binary segmentation showed that, despite the imperfections of synthetics, training on a mixed (MIX) dataset gave a significant increase (about 0.1) in the Dice metric for 6 and 5 and same results at binary. The synthetic data strategy gives annotations for free, but shifts the effort to producing sufficiently realistic images.

Seismic-electromagnetic projection attribute: Application in integrating seismic quantitative interpretation and 3D controlled-source electromagnetic-magnetotelluric broadband data inversion for robust ranking and sweet spotting of hydrocarbon prospects in offshore northwest Borneo

We introduce a new seismic-electromagnetic (EM) projection (SEMP) attribute to improve the characterization of pay sands by integrating seismic P impedance and S impedance with electrical resistivity measurements leveraging on the high sensitivity of resistivity to fluid saturation and the capability of seismic data to delineate thin beds. Porosity is predicted using an extended elastic impedance (EEI) approach to reduce the risk of encountering SEMP anomalies related to low porosity. First, we determine the seismic-EM integration concept using well logs from a well that encountered hydrocarbons in a deepwater fold belt in offshore Borneo. The SEMP logs supported by the EEI log successfully delineate the pay zones in the well. Second, we extend the approach in three dimensions and evaluate its effectiveness using large-size seismic controlled-source EM (CSEM) and magnetotelluric (MT) data from the same area. The seismic data are inverted to produce P- and S-impedance volumes. EEI volume calibrated to total porosity also is produced. We then perform 3D anisotropic cross-gradient joint CSEM and MT inversion of a large-size survey comprising 647 receivers with receiver spacing of 1.5–3 km at prospect to regional scale. The SEMP volumes computed using the seismic and CSEM-MT inversion results are then interpreted with the EEI volume to identify possible geobodies of pay sand. Resistive geobodies with low porosity are assigned higher risks because they are likely due to compaction rather than hydrocarbon presence, whereas geobodies with high porosity are assigned lower risks and identified as potential sweet spots. The geobodies need to be corroborated with independent geologic studies to mature them into exploration prospects and assess their associated risk and potential. Although a vertical transverse isotropy approximation is used in our CSEM-MT study, the SEMP concept also is applicable to cases considering tilted transverse isotropy or arbitrary anisotropy where available and operational for such large-size exploration data.

Regulation of Interfacial Anchoring Orientation of Anisotropic Nanodumbbells.

Nanoparticles exhibiting geometrical and chemical anisotropies hold promise for environmentally responsive materials with tunable mechanical properties. However, a comprehensive understanding of their interfacial behaviors remains elusive. In this paper, we control the interfacial anchoring orientation of polystyrene nanodumbbells by adjusting interparticle forces. The film nanostructure is characterized by the orientation angle analysis of individual dumbbells from cross-sectional EM data: dumbbells undergo orientation transitions from a distinctive horizontal bilayer to an isotropic anchoring when electrostatic repulsion is suppressed by either an ionic strength increase or surface amine-modification. This anchoring orientation influences the film's mechanical properties and foam stability, as investigated by a 2D isotherm and dark/bright-field microscopy measurements. Our findings highlight the potential for precise control of supra-colloidal structures by modulating particle alignment, paving the way for smart delivery systems.

Screening Morphological Characteristics of Large Populations of Synaptic Vesicle Clouds and Active Zones from 3D EM Data.

Screening Morphological Characteristics of Large Populations of Synaptic Vesicle Clouds and Active Zones from 3D EM Data.

Joint analysis of gravitational-wave and electromagnetic data of mergers: breaking an afterglow model degeneracy in GW170817 and in future events

ABSTRACT On 2017 August 17, Advanced LIGO and Virgo observed GW170817, the first gravitational-wave (GW) signal from a binary neutron star merger. It was followed by a short-duration gamma-ray burst, GRB 170817A, and by a non-thermal afterglow emission. In this work, a combined simultaneous fit of the electromagnetic (EM, specifically, afterglow) and GW domains is implemented, both using the posterior distribution of a GW standalone analysis as prior distribution to separately process the EM data, and fitting the EM and GW domains simultaneously. These approaches coincide mathematically, as long as the actual posterior of the GW analysis, and not an approximation, is used as prior for the EM analysis. We treat the viewing angle, θv, as shared parameter across the two domains. In the afterglow modelling with a Gaussian structured jet this parameter and the jet core angle, θc, are correlated, leading to high uncertainties on their values. The joint EM + GW analysis relaxes this degeneracy, reducing the uncertainty compared to an EM-only fit. We also apply our methodology to hypothetical GW170817-like events occurring in the next GW observing run at ∼140 and 70 Mpc. At 70 Mpc the existing EM degeneracy is broken, thanks to the inclusion of the GW domain in the analysis. At 140 Mpc, the EM-only fit cannot constrain θv nor θc because of the lack of detections in the afterglow rising phase. Folding the GW data into the analysis leads to tighter constraints on θv, still leaving θc unconstrained, requiring instruments with higher sensitivities, such as Athena.

Three-Dimensional Inversion of Induced Polarization Effects in Airborne Time Domain Electromagnetic Data Using the GEMTIP Model

This paper discusses the physical and mathematical principles of the airborne induced polarization (IP) method. The possibility of extracting information about the IP properties of rocks from airborne survey data has become a subject of active research recently. We introduce a method for the joint inversion of the airborne EM data into the electrical conductivity and IP parameters based on the generalized effective-medium theory of induced polarization (GEMTIP). We also present the results of the inversion of the airborne EM data collected over the Echum Project Area, in Northwestern Ontario, Canada, into 3D conductivity and chargeability models. Obtaining IP physical property models from an airborne geophysical survey may result in a paradigm change in mineral exploration by pulling more information and value from airborne EM surveys.

ON MODIFIED VARIANTS OF CLASSICAL TROJAN Y CHROMOSOME MODEL WITH GLOBAL SOLUTIONS

The Trojan Y Chromosome (TYC) strategy is a biological control method for controlling invasive populations with an XX–XY sex determinism, wherein a modified organism is introduced into an invasive population to skew the sex ratio over time, causing local extinction. However, the classical three compartment TYC model possesses blow-up solutions, for large initial conditions [Takyi EM, Beauregard MA, Griffin T, Bobo L, Parshad RD, On large and small data blow-up solutions in the Trojan Y Chromosome model, Axioms 11(3):120, 2022]. We investigate model improvements via accounting for a modified logistic term, female mating preference, competition between males and supermales and pair formation. Each one of these models is dynamically explored and is shown to possess global in-time non-negative solutions, in any parameter and initial data regime, and the models are also effective in facilitating extinction of the invasive wild type.

A study on the influence of the spread of Yangming Studies in Japan on the psychology of the Japanese people based on big data analysis

Abstract The analysis of the psychological impact of the spread of Yangming studies in Japan on the Japanese people is to enable Yangming studies to be better developed in Japan. Based on big data analysis technology, this paper constructs a hybrid data analysis model using the EM algorithm and proposes performance evaluation indexes for the model. Under the EM data analysis model constructed in this paper, the example indicators of the Japanese people’s psychological impact in disseminating Yangming studies by big data analysis are explored, i.e., the psychological acceptability of the dissemination method and the psychological and moral construction impact. Regarding the dissemination method, the Japanese people are more receptive to disseminating Yangming studies in Japan through “learning rules”, with an average percentage of 39.37%. Regarding psychological and moral construction, 90.22% of the Japanese people believe that disseminating Yangming studies can promote self-improvement of value standards and correct self-examination. Based on the big data analysis, we can effectively see from the data the impact of Yangming studies on the audience in the process of dissemination, and improve the scope of Yangming studies dissemination according to the data feedback, so that more people can recognize the idea of unity of knowledge and action.

Characterizing the porosity structure and gas hydrate distribution at the southern Hikurangi Margin, New Zealand from offshore electromagnetic data.

The dynamics of accretionary prisms and the processes that take place along subduction interfaces are controlled, in part, by the porosity and fluid overpressure of both the forearc wedge and the sediments transported to the system by the subducting plate. The Hikurangi Margin, located offshore the North Island of New Zealand, is a particularly relevant area to investigate the interplay between the consolidation state of incoming plate sediments, dewatering and fluid flow in the accretionary wedge and observed geodetic coupling and megathrust slip behaviour along the plate interface. In its short geographic extent, the margin hosts a diversity of properties that impact subduction processes and that transition from north to south. Its southernmost limit is characterized by frontal accretion, thick sediment subduction, the absence of seafloor roughness, strong interseismic coupling and deep slow slip events. Here we use seafloor magnetotelluric (MT) and controlled-source electromagnetic (CSEM) data collected along a profile through the southern Hikurangi Margin to image the electrical resistivity of the forearc and incoming plate. Resistive anomalies in the shallow forearc likely indicate the presence of gas hydrates, and we relate deeper forerarc resistors to thrust faulting imaged in colocated seismic reflection data. Because MT and CSEM data are highly sensitive to fluid phases in the pore spaces of seafloor sediments and oceanic crust, we convert resistivity to porosity to obtain a representation of fluid distribution along the profile. We show that porosity predicted by the resistivity data can be well fit by an exponential sediment compaction model. By removing this compaction trend from the porosity model, we are able to evaluate the second-order, lateral changes in porosity, an approach that can be applied to EM data sets from other sedimentary basins. Using this porosity anomaly model, we examine the consolidation state of the incoming plate and accretionary wedge sediments. A decrease in porosity observed in the sediments approaching the trench suggests that a protothrust zone is developing ∼25km seaward of the frontal thrust. Our data also imply that sediments deeper in the accretionary wedge are slightly underconsolidated, which may indicate incomplete drainage and elevated fluid overpressures of the deep wedge.

Psychometric Evaluation of the Migraine-Specific Quality of Life Questionnaire (MSQ v2.1) Using Data From Phase 3 Clinical Trials in Patients With Chronic Migraine (CM) and Episodic Migraine (EM) (P8-12.007)

Psychometric Evaluation of the Migraine-Specific Quality of Life Questionnaire (MSQ v2.1) Using Data From Phase 3 Clinical Trials in Patients With Chronic Migraine (CM) and Episodic Migraine (EM) (P8-12.007)

Three-Dimensional Dual-Mesh Inversions for Sparse Surface-to-Borehole TEM Data

The surface-to-borehole transient electromagnetic (SBTEM) method can provide images at higher resolution for deep earth because its receivers are close to targets. However, as usually the boreholes distribute sparsely, the limited EM data can result in an “equivalent trap” in SBTEM inversions, i.e., the data are well-fitted, but the model is not properly recovered. To overcome this non-unique problem, we propose a dual-mesh three-dimensional (3D) SBTEM inversion scheme. We first use a coarse mesh to obtain a rough resistivity distribution near the borehole, and then we map the coarse mesh attribute into a fine one and capture details from the fine mesh inversion. We test our method on both synthetic data and survey data acquired in Daye, Hubei Province, China. Numerical experiments show that our dual-mesh inversion strategy can better recover the location and resistivity of targets.

A Rapid Matching Network Layout Synthesis and Optimization Method for High-Performance MMIC PAs Using Modified Implicit Space Mapping

In this brief, a new systematic approach of matching network (MN) layout synthesis and optimization for power amplifiers (PAs) is proposed based on implicit space mapping (ISM). Commonly, the performance discrepancy between schematic and initial layout is huge, especially for millimeter wave (mmWave) PAs. To address this issue, the proposed modified ISM can shift the optimization work to the circuit schematic simulations by calibrating carefully-selected auxiliary parameters in the circuit based on EM data. To validate the proposed method, an eligible dual-band inter-stage MN layout is rapidly optimized with only 10 runs of EM-simulations, while a corresponding 16/26.5 GHz concurrent dual-band PA is implemented in a 0.15- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> GaAs pHEMT technology. It exhibits a measured small-signal gain of 21.7/14.1 dB, peak power-added efficiency of 30.2%/40.5%, and saturated output power of 24.8/28.1 dBm with a compact chip size of 2.4 mm2.

A fast 3-D inversion for airborne EM data using pre-conditioned stochastic gradient descent

SUMMARY Airborne electromagnetic (AEM) exploration produces large amounts of data due to its high sampling rate, so that the 3-D inversions take extremely big computation and time consumption. We present a fast 3-D inversion framework for large-scale AEM explorations using a pre-conditioned stochastic gradient descent combined with Gauss–Newton (PSG-GN) method. We adopt a compressed sensing (CS) in the 3-D forward modelling, in which a random undersampling is used to reduce the calculation, while the responses for all survey stations are obtained via a reconstruction technique. For our 3-D AEM inversions, a method of combining the stochastic gradient descent with Gauss–Newton (SG-GN) that requires only a small data set in each iteration instead of the conventional full-batch data (complete original data) inversion have been investigated. To further speed up the 3-D inversion, we develop a pre-conditioner considering the random sampling rate and gradient noise to achieve a fast convergence. We use two synthetic models to test the accuracy, convergence and efficiency of our algorithm. The results show that the conventional inversion with full-batch data and the PSG-GN method can both converge quickly, but our method can enhance the inversion efficiency up to 78 per cent. Finally, we invert a field data set acquired from a massive sulfide deposit in Ireland and obtain the results that agree well with the known geologies.