Search Results (432)

Artificial intelligence has garnered significant attention in recent years as a rapidly advancing field of computer technology. With the continual advancement of computer hardware, deep learning has made breakthrough developments within the realm of artificial intelligence. Over the past few years, applying deep learning architecture in medicine and industrial anomaly inspection has significantly contributed to solving numerous challenges related to efficiency and accuracy. For excellent results in radiological, pathological, endoscopic, ultrasonic, and biochemical examinations, this paper utilizes deep learning combined with image processing to identify spinal canal and vertebral foramen dimensions. In existing research, technologies such as corrosion and expansion in magnetic resonance image (MRI) processing have also strengthened the accuracy of results. Indicators such as area and Intersection over Union (IoU) are also provided for assessment. Among them, the mean Average Precision (mAP) for identifying intervertebral foramen (IVF) and intervertebral disc (IVD) through YOLOv4 is 95.6%. Resnet50 mixing U-Net was employed to identify the spinal canal and intervertebral foramen and achieved IoU scores of 79.11% and 80.89%. Full article

Background: Patients with scoliosis often require multiple imaging modalities. The aim of this study was to find out whether primary diagnosis, including surgical planning, could be carried out entirely without computed tomography (CT) scans and whether follow-up could be replaced with alternative methods without the use of X-rays. In order to reduce the radiation exposure in the diagnosis and treatment of severe scoliosis, we expect to replace X-rays with radiation-free or less-intensive radiation examinations. This study protocol is interdisciplinary. Methods: A total of 50 male and female patients (children and adolescents, aged 7–18 years) treated for scoliosis will be analyzed. In addition to routine projection radiographs, preoperative CT, and/or X-ray stereoradiography (EOS) examinations, thin-slice 3D magnetic resonance imaging (MRI) sequences will be retrospectively reformatted during the preoperative MRI examination. A three-dimensional back scan (video-raster stereography) and an intraoral scan will also be obtained. The following questions should be answered at the end of the project: (1) Can MRI examination with additional thin-slice 3D reconstruction answer all relevant questions for preoperative planning instead of CT? (2) Are EOS or whole-spine X-ray examinations in combination with MRI data sufficient for the evaluation of the pedicles and spinal deformity? (3) Does the Cobb angle in the radiograph correlate with the calculations from the back scanner image and can follow-up checks be replaced? (4) Are there any correlations between dental anomalies and scoliosis? Conclusions: Until now, pediatric patients with scoliosis have been diagnosed, monitored, and treated with numerous independent specialist disciplines, such as pediatricians, orthopedic surgeons, neurosurgeons, and general practitioners with different radiological issues. The aim of this project is to reduce radiation and lower perioperative risks by creating a preoperative and follow-up-related standard protocol in close interdisciplinary and targeted cooperation between all the specialist disciplines involved. In line with the holistic examination approach, the associated accompanying diseases and developmental disorders such as dental and neuronal malformations will also be examined. On the one hand, CT-based questions could be replaced with the reconstruction of thin-slice MRI sequences. In addition, it may be possible to use the three-dimensional back scan as an intermediate diagnostic procedure instead of X-rays in the monitoring of severe scoliosis. Insofar as correlations or causalities between scoliosis and occlusal anomalies, early orthodontic intervention could positively benefit the duration of therapy at a later stage. Full article

The electrical resistivity of subsurface rocks is one of the important sensitive parameters characterizing the internal physics of the Earth. Currently, research on subsurface electrical structures using geomagnetic sounding methods primarily focuses on two approaches: the first is based on observations from a few geomagnetic stations, which have low spatial resolution and cannot effectively describe the distribution of anomalies; the second is based on mobile geomagnetic observations, which have low temporal resolution and cannot promptly reflect anomalies. To address these issues, this study deployed a dense geomagnetic array for long-term observation in the southern segment of the Xiaojiang Fault Zone in the Yuxi area of southern Yunnan. This setup aims to promptly capture seismic magnetic anomalies, providing more data support and fundamental information for short-term earthquake prediction. Based on the long-term observation data from the dense array, the study of the subsurface electrical structure is carried out. The results indicate that during the observation period, which was seismically quiet, the regional subsurface electrical structure remained stable. A large-scale subsurface low-resistivity body was observed in the region, and the electrical structures at the two ends of the southern segment of the Xiaojiang Fault Zone were found to be completely different. Full article

With the increasing demand for power supply reliability, online monitoring techniques for cable health condition assessments are gaining more attention. Most prevailing techniques lack the sensitivity needed to detect minor insulation defects. A new monitoring technique based on the harmonic anomaly feature analysis of the shield-to-ground current is introduced in this paper. The sensor installation and data acquisition are convenient and intrinsically safe, which makes it a preferred online monitoring technique. This study focuses on the single-core 10 kV distribution cable type. The research work includes the theoretical analysis of the cable defect’s impact on the current harmonic features, which are then demonstrated by simulation and lab experiments. It has been found that cable insulation defects cause magnetic field distortion, which introduces various harmonic current components, principally, the third-, fifth-, and seventh-order harmonic. The harmonic anomaly features are load current-, defect type-, and aging time-dependent. The K-means algorithm was selected as the data analysis algorithm and was used to achieve insulation defect prediction. The research outcome establishes a solid basis for the field application of the shield-to-ground harmonic current monitoring technique. Full article

We present the results of a self-consistent analysis of the magnetic silicon star BD+00°1659, based on its high-resolution spectra taken from the ESPaDOnS archive (R = 68,000). This narrow-lined star shows the typical high Si abundance and Si ii– iii anomaly, making it an ideal prototype for investigating the vertical distribution of Si and Fe in the stellar atmosphere. The derived abundances, ranging from helium to lanthanides, confirm the star’s classification as a silicon Bp spectral type. Silicon and iron are represented by lines of different ionisation stages (Fe i– iii, Si i– iii), indicating an ionisation imbalance interpreted as evidence of atmospheric stratification. Our stratification analysis reveals that there is a jump in iron and silicon abundances of 1.5 dex at atmospheric layers with an optical depth of $log{\tau }_{5000}$ = −0.85–−1.00. Non-LTE calculations for iron in this stratified atmosphere show minor non-LTE effects. Our results can be applied to studying the impact of stratification on the emergent flux in rapidly rotating Si stars with similar atmospheric parameters and abundance anomalies (for example, MX TrA), where direct stratification analysis is challenging due to line blending. Full article

This paper presents the results of precise measurements of temperature and pore pressure in the “reservoir–well” system during the development of iron ore deposits of the Kursk Magnetic Anomaly (KMA) via blasting. For the observation period from October 2021 to June 2024, variations in compressibility, permeability and temperature in the upper Albian-Cenomanian confined aquifer, which is used for district water supply, were determined. The general trend in a decrease in water temperature was traced (from 12 °C to 11.4 °C). It was accompanied by an increase in the hydrostatic head (from 3.7 m to 7.4 m). Water temperature in the upper aquifer was measured for 9 industrial explosions in the mine and for 30 explosions in the quarry. For one explosion in the mine and five explosions in the quarry the coseismic changes in water temperature with amplitudes of 0.06–0.09 °C were established, while changes in pore pressure in the “reservoir–well” system were 0.4–2.2 kPa. Local changes in the permeability of the reservoir in the vicinity of the well (the skin effect) are considered to be the main factor that controls the coseismic response of temperature during industrial explosions. As the reservoir permeability increases, the water temperature in the “reservoir–well” system can decrease and vice versa. The same pattern was observed according to regime measurements performed in 2022–2023. The recorded coseismic responses of water temperature in the upper aquifer in the high-frequency range are similar to the effects observed during propagation of seismic waves originated from earthquakes in the low-frequency range at different sites all over the world for the seismic energy density of 0.05–0.45 J/m³. The observed variations in aquifer temperature in the “reservoir–well” system under episodic dynamic impacts are of particular interest from the point of view of activating hydrogeochemical processes that accompany the development of iron ore deposits. Full article

This paper investigates the impact characteristics of the 4 November 2021 magnetic storm across different frequency bands based on the electric field data (EFD) from the China Seismo-Electromagnetic Satellite (CSES), categorized into four frequency bands: ULF (Ultra-Low-Frequency, DC to 16 Hz), ELF (Extremely Low-Frequency, 6 Hz to 2.2 kHz), VLF (Very Low-Frequency, 1.8 to 20 kHz), and HF (High-Frequency, 18 kHz to 3.5 MHz). The study reveals that in the ULF band, magnetic storm-induced electric field disturbances are primarily in the range of 0 to 5 Hz, with a significant disturbance frequency at 3.9 ± 1.0 Hz. Magnetic storms also enhance Schumann waves in the ULF band, with 8 Hz Schumann waves dominating in the southern hemisphere and 13 Hz Schumann waves dominating in the northern hemisphere. In the ELF band, the more pronounced anomalies occur at 300 Hz–900 Hz and above 1.8 kHz, with the 300 Hz–900 Hz band anomalies around 780 Hz being the most significant. In the VLF band, the electric field anomalies are mainly concentrated in the 3–15 kHz range. The ELF and VLF bands exhibit lower absolute and relative disturbance increments compared to the ULF band, with the relative perturbation growth rate in the ULF band being approximately 10% higher than in the ELF and VLF bands. Magnetic storm-induced electric field disturbances predominantly occur in the ULF, ELF, and VLF bands, with the most significant disturbances in the ULF band. The electric field perturbations in these three frequency bands exhibit hemispheric asymmetry, with strong perturbations in the northern hemisphere occurring earlier than in the southern hemisphere, corresponding to different Dst minima. No electric field disturbances were observed in the HF band (above 18 kHz). The conclusions of this paper are highly significant for future anti-jamming designs in spacecraft and communication equipment, as well as for the further study of magnetic storms. Full article

In practical application, existing two-point magnetic gradient tensor (MGT) localization methods have a maximum detection distance of only 2.5 m, and the magnetic moment vectors of measured targets are all unknown. In order to realize remote, real-time localization, a new two-point magnetic localization method based on self-developed, ultra-sensitive superconducting quantum interference device (SQUID) magnetometers and MGT invariants is proposed. Both the magnetic moment vector and the relative position vector can be directly calculated based on the linear positioning model, and a quasi-Newton optimization algorithm is adopted to further improve the interference suppression capability. The simulation results show that the detection distance of the proposed method can reach 500 m when the superconducting MGT measurement system is used. Compared with Nara’s single-point tensor (NSPT) method and Xu’s two-point tensor (XTPT) method, the proposed method produces the smallest relative localization error (i.e., significantly less than 1% in the non-positioning blind area) without sacrificing real-time characteristics. The causes of and solutions to the positioning blind area are also analyzed. The equivalent experiments, which were conducted with a detection distance of 10 m, validate the effectiveness of the localization method, yielding a minimum relative localization error of 4.5229%. Full article

As an effective physical field feature to perceive ferromagnetic targets, magnetic anomaly is widely used in covert marine surveillance tasks. However, its practical usability is affected by the complex marine magnetic noise interference, making robust magnetic anomaly detection (MAD) quite a challenging task. Recently, learning-based detectors have been widely studied for the discrimination of magnetic anomaly signal and achieve superior performance than traditional rule-based detectors. Nevertheless, learning-based detectors require abundant data for model parameter training, which are difficult to access in practical marine applications. In practice, target magnetic anomaly data are usually expensive to acquire, while rich marine magnetic noise data are readily available. Thus, there is an urgent need to develop effective models to learn discriminative features from the abundant marine magnetic noise data for newly appearing target anomaly detection. Motivated by this, in this paper we formulate MAD as a single-edge detection problem and develop a self-supervised marine noise learning approach for target anomaly classification. Specifically, a sparse autoencoder network is designed to model the marine noise and restore basis geomagnetic field from the collected noisy magnetic data. Subsequently, reconstruction error of the network is used as a statistical decision criterion to discriminate target magnetic anomaly from cluttered noise. Finally, we verify the effectiveness of the proposed approach on real sea trial data and compare it with seven state-of-the-art MAD methods on four numerical indexes. Experimental results indicate that it achieves a detection accuracy of 93.61% and has a running time of 21.06 s on the test dataset, showing superior MAD performance over its counterparts. Full article

The study of the physical properties of the topside ionosphere is fundamental to investigating the energy balance of the ionosphere and developing accurate models to predict relevant phenomena, which are often at the root of Space Weather effects in the near-Earth environment. One of the most important physical parameters characterising the ionospheric medium is electrical conductivity, which is crucial for the onset and amplification of ionospheric currents and for calculating the power density dissipated by such currents. We characterise, for the first time, electrical conductivity in the direction perpendicular to the geomagnetic field, namely Pedersen and Hall conductivities, in the topside ionosphere at an altitude of about 450 km. For this purpose, we use eight years of in situ simultaneous measurements of electron density, electron temperature and geomagnetic field strength acquired by the Swarm A satellite. We present global statistical maps of perpendicular electrical conductivity and study their variations depending on magnetic latitude and local time, seasons, and solar activity. Our findings indicate that the most prominent features of perpendicular electrical conductivity are located at low latitudes and are probably driven by the complex dynamics of the Equatorial Ionisation Anomaly. At higher latitudes, perpendicular conductivity is a few orders of magnitude lower than that at low latitudes. Nevertheless, conductivity features are modulated by solar activity and seasonal variations at all latitudes. Full article

The Beishan region is a vital fluorite metallogenic belt in northwest China, characterized by favorable geological conditions for fluorite mineralization. However, being located in the Gobi Desert and affected by shallow cover layers, only a few outcrops can be observed on the surface. Therefore, comprehensive geophysical research is necessary to locate and predict regional metallogenic potential and the spatial distribution of veins beneath the cover. This study conducted a combination of ground magnetic method (GM), induced polarization (IP) surveys, portable gamma-ray (PGR), portable X-ray fluorescence analyses (PXRF), and audio Magnetotelluric (AMT) to conduct comprehensive exploration. The IP and GM effectively identified concealed ore-bearing space distributions and ground PGR- and PXRF-constrained mineralization anomalies, while AMT surveys constructed deep electrical structure models for ore deposits. This approach delineated concealed fluorite deposit locations as well as potential magmatic–hydrothermal migration pathways. Engineering verification confirmed the effectiveness of this method combination. This study established a comprehensive geological–geophysical positioning prediction technique that can serve as a reference for locating and predicting fluorite deposits in shallow-covered areas within the Gobi Desert. Full article

To explore the deep geological structure of the Dongyang area in Fujian, China, gravity data from the area and its surroundings were collected and processed. Additionally, a high-precision magnetic survey was conducted in the Zhongxian region of this area, with subsequent analysis of the magnetic anomalies. Through the integration of regional geological data, a comprehensive analysis was carried out on the characteristics of gravity–magnetic anomalies and deep geological structures in the Dongyang area. The study indicates that the primary portion of the Dongyang area lies southwest of the expansive circular volcanic structure spanning Dehua to Yongtai. Two significant residual gravity anomalies were identified within the region, interpreted as the Xiaoban-Shuangqishan and Dongyang-Lingtouping residual gravity-positive anomalies. In the Zhongxian region, the magnetic field exhibits complexity with notable amplitude variations. Positive anomalies predominate in the western and northern sectors, while localized positive anomalies are prominent in the eastern region. The central area portrays a circular and disordered mix of positive and negative anomalies. Particularly distinctive are the band-shaped and fan-shaped negative anomalies curving from northeast to southeast through the central region. Various positive and negative anomalies of varying strengths, gradients, and orientations overlay both positive and negative magnetic backgrounds in specific locales. Moreover, the Dongyang area showcases well-developed fault structures, primarily oriented in northeast and northwest directions. Leveraging the regional magnetic attributes in conjunction with regional geological data, 39 faults were deduced in the Zhongxian region of the Dongyang area, delineating three promising mineralization zones. Full article

The Mesozoic subduction zone over the Dongsha Waters (DSWs) of the South China Sea (SCS) is a part of the westward subduction of the ancient Pacific plate. Based on the comprehensive interpretation of deep reflection seismic profile data and polar magnetic anomaly data, and the zircon dating results of igneous rocks drilled from well LF35-1-1, the Mesozoic subduction zone in the northeast SCS is accurately identified, and a Mesozoic subduction model is proposed. The accretion wedges, trenches, and igneous rock zones together form the Mesozoic subduction zone. The evolution of the Mesozoic subduction zone can be divided into two stages: continental subduction during the Late Jurassic and continental collision during the late Cretaceous. The Mesozoic subduction zone controlled the structural pattern and evolution of the Chaoshan depression (CSD) during the Mesozoic and Neogene eras. The gas source of the hydrate comes from thermogenic gas, which is accompanied by mud diapir activity and migrates along the fault. The gas accumulates to form gas hydrates at the bottom of the stable domain; BSR can be seen above the mud diapir structure; that is, hydrate deposits are formed under the influence of mud diapir structures, belonging to a typical leakage type genesis model. Full article

Congenital heart diseases (CHD) are one of the most common birth defects and the main leading cause of death in children. Many patients with CHD are reaching adulthood due to the success of improved contemporary surgical procedures. Understanding the etiology of CHD remains important for patient clinical management. Both genetic and environmental factors are involved in the development and progression of CHD. Variations in many different genes and chromosomal anomalies can be associated with CHD, by expression of different mechanisms. Sporadic cases are the most frequently encountered in these patients. Atrial septal defect is a common congenital heart disease that refers to direct communication between atrial chambers, found isolated or associated with other syndromes. Imaging techniques, especially transthoracic and transesophageal echocardiography (TOE) represent the key for diagnosis and management of ASD. The disease has a major incidence in adulthood, due to late symptomatology, but assessment and treatment are important to avoid time-related complications. Ebstein’s anomaly is a rare congenital disease, with a dominant genetic participation, characterized by an abnormal displacement of the tricuspid valve and right ventricular myopathy, often requiring surgical intervention. Alongside echocardiography, cardiac magnetic resonance (CMR) imaging is the gold standard tool for the assessment of ventricular volumes. Early diagnosis and adequate treatment are mandatory to avoid possible complications of CHD, and thus, ECG, as well as imaging techniques, are important diagnostic tools. However, patients with CHD need a special healthcare team for the entire monitorization in various life stages. Full article

Earthquake prediction is the holy grail of seismology and one of humanity’s greatest dreams. The Earth’s magnetic field appears to be one of the best possible precursors of earthquakes, although the topic is controversial. Recent advancements have made it possible to observe magnetic fields from satellites with great accuracy. We utilize magnetic measurements from Swarm satellites to explore the potential identification of anomalous magnetic signals preceding earthquakes. Focusing on 1077 major earthquakes that occurred in 2014–2023 in the Alpine–Himalayan belt, we apply an automatic algorithm to data recorded 10 days before each earthquake. This analysis reveals clear pre-earthquake anomalies in the magnetic field components. Notably, a robust correlation is established between the duration of these anomalies and the earthquake magnitude, indicating that as the earthquake magnitude increases, so does the duration of the anomaly. Here we show that this method has a great ability to make predictions (high accuracy 79%, precision 88%, F1-score and hit rate 84%), thus becoming the basis for an Operational Earthquake Prediction System (OEPS). Full article