Search Results (448)

To study the mechanical properties and displacement evolution of rock masses near coal-seam normal faults under mining disturbances; this paper utilizes fiber optic monitoring and distributed strain measurement techniques to achieve the fine monitoring of the entire process of stress–displacement–strain during mining. The experimental design adopts a stepwise mining approach to systematically reproduce the evolution of fault formation; slip; and instability. The results show that the formation of normal faults can be divided into five stages: compressive deformation; initiation; propagation; slip; and stabilization. The strength of the fault plane is significantly influenced by the dip angle. As the dip angle increases from 30° to 70°, the peak strength decreases by 23%, and the failure mode transitions from tensile failure to shear failure. Under mining disturbances, the stress field in the overlying rock shifts from concentration to dispersion, with a stress mutation zone appearing in the fault-adjacent area. During unloading, vertical stress decreases by 45%, followed by a rebound of 10% as mining progresses. The rock layers above the goaf show significant subsidence, with the maximum vertical displacement reaching 150 mm. The displacement between the hanging wall and footwall differs, with the maximum horizontal displacement reaching 78 mm. The force chain distribution evolves from being dominated by compressive stress to a compressive–tensile stress coupling state. The fault zone eventually enters a stress polarization state and tends toward instability. A large non-uniform high-speed zone forms at the fault cutting point in the velocity field, revealing the mechanisms of fault instability and the initiation of dynamic disasters. These experimental results provide a quantitative understanding of the multi-physics coupling evolution characteristics of coal-seam normal faults under mining disturbances. The findings offer theoretical insights into the instability of coal-seam normal faults and the mechanisms behind the initiation of dynamic disasters. Full article

The Cimabanshuo deposit, situated in the western Gangdese Belt, is a recently discovered porphyry Cu deposit formed in a post-collisional setting, approximately 10 km from the giant Zhunuo porphyry Cu deposit. Despite its proximity to Zhunuo, Cimabanshuo remains poorly studied, and the current exploration depth of 600 m leaves the potential for deeper resources uncertain. In this study, 840 samples from four drill holes along the NW-SE section (A-A′) were analyzed using portable X-ray fluorescence (pXRF). Based on the geochemical characteristics of primary halos, the deep mineralization potential of Cimabanshuo was evaluated. The results show that Co, Pb, and Ag are near-ore indicator elements; Zn, Cs, Hg, Sb, As, and Ba represent the frontal elements; and Te, Sn, and Bi occur as tail elements. Based on these distributions, a 14-element zoning sequence is defined along the A-A′ profile according to Gregorian’s zoning index, showing Mo-Co-Cu-Pb-Bi-Ag-Sn-Te-Sb-Hg-Cs-Zn-Ba-As from shallow to deep. This sequence shows a distinct reverse zonation pattern, in which tail elements occur in the middle and frontal elements appear at depth, suggesting the existence of a concealed ore body in the lower part of the deposit. Horizontally, the geochemical ratios Ag/Mo and Ag/Cu decrease from northwest to southeast along the profile, implying hydrothermal flow from southeast to northwest. Vertically, the ratios As/Bi, (As × Cs)/(Bi × Te), (As × Ba)/(Bi × Sn), and (As × Ba × Cs)/(Bi × Sn × Te) display a downward-decreasing then upward-increasing trend, further indicating hidden mineralization at depth. This inference is supported by the predominance of propylitic alteration and the deep polarization anomaly revealed by audio-magnetotelluric imaging. pXRF analysis provides a fast, efficient, and environmentally friendly approach, showing strong potential for rapid geochemical evaluation in porphyry Cu exploration. Full article

Polarized neutron reflectometry (PNR) analyzes surface and interfacial structures of materials. For the SHARAKU reflectometer at the Materials and Life Science Experimental Facility in the Japan Proton Accelerator Research Complex, precise measurements under weak magnetic fields, which are critical for modern spintronics, have long been challenging. To address this issue, we developed a precise weak-field sample environment equipped with a newly designed coil system. The magnetic field at the sample position can be applied within the surface/interface plane, either in the scattering plane (horizontal configuration) or perpendicular to it (vertical configuration). The horizontal configuration achieved high polarization efficiency across a stable field range, whereas the vertical configuration enabled the experiments to cross zero into negative fields. We demonstrated the instrument’s capability by resolving the remanent magnetic structure of an Fe film. Its applicability to soft matter was proven through analysis of a cellulose thin film with roughness using magnetic contrast variation PNR. In this case, precise weak-field control is essential to tune the magnetic contrast from the reference layer beneath the soft film. These results establish the system as a versatile platform for future PNR and polarized off-specular scattering experiments across a wide range of materials. Full article

Toxin–antitoxin (TA) modules represent sophisticated regulatory networks that have evolved from simple plasmid maintenance factors into multifunctional genetic modules orchestrating bacterial stress responses, pathogenesis, and ecological adaptation. This review highlights a compelling correlation between the abundance of toxin–antitoxin (TA) modules and bacterial pathogenicity, as exemplified by Mycobacterium tuberculosis (M.tb), which encodes 118 TA loci—significantly more than the fewer than 10 found in closely related saprophytic species. The clinical significance of TA modules extends beyond traditional stress response roles to encompass antimicrobial persistence, where systems like VapBC and MazEF facilitate dormant subpopulations that survive antibiotic therapy while maintaining chronic infections. Recent discoveries have revealed TA modules as sophisticated bacterial defense mechanisms against bacteriophage infection, with DarTG and ToxIN systems representing novel antiviral immunity components that complement CRISPR-Cas and restriction–modification systems. The immunomodulatory capacity of TA modules demonstrates their role in host–pathogen interactions, where systems such as VapC12 in M.tb promote macrophage polarization toward permissive M2 phenotypes while inducing anti-inflammatory cytokine production. Large-scale genomic analyses reveal that TA modules function as drivers of horizontal gene transfer networks, with their signatures enabling accurate prediction of plasmid community membership and serving as determinants of microbial community structure. The biotechnological applications of TA modules have expanded to include genetic circuit stabilization, biocontainment device construction, and multi-species microbial community engineering, while therapeutic strategies focus on developing multi-target inhibitors against conserved TA protein families as promising approaches for combating drug-resistant bacterial infections. The evolutionary conservation of TA modules across diverse bacterial lineages underscores their fundamental importance as central organizing principles in bacterial adaptation strategies, where their multifunctional nature reflects complex selective pressures operating across environmental niches and host-associated ecosystems. This review provides an integrated perspective on TA modules as dynamic regulatory elements that support bacterial persistence, immune evasion, and ecological versatility, establishing them as genetic elements with truly “many faces and functions” in prokaryotic biology. Full article

The target detection method based on a constant false alarm rate (CFAR) and feature space is commonly used in remote sensing for detecting maritime targets within sea clutter. However, the performance of traditional CFAR techniques heavily relies on the signal-to-clutter ratio (SCR) in a single observational channel, while feature space methods are overly sensitive to the number of pulse accumulations and rigidly apply outlier classifiers to define detection regions, without theoretical derivation. To address these limitations, this paper proposes a two-dimensional (2D) CFAR target detection method based on echo data from dual-polarization observational channels. First, statistical models of the amplitude distribution for horizontal–horizontal (HH) and vertical–vertical (VV) polarization sea clutter radar echoes are validated under identical observation conditions using measured data, and their correlations are analyzed. Then, the Copula function is introduced as a theoretical foundation to rigorously derive and extend the cell-averaging CFAR detector through strict mathematical formulations, transitioning from single statistics to 2D detection statistics. This leads to the proposed target detection method. Testing with measured data from publicly available datasets demonstrates that the proposed method effectively achieves adaptive false alarm control and significantly improves the detection performance compared to existing single-pulse one-dimensional CFAR detection methods. Full article

Controlling light’s polarization through disordered media is crucial for advanced optical applications but remains challenging due to scattering and depolarization. Most existing approaches either require interferometric or multi-path measurements, or they recover only part of the polarization response. We present a comprehensive approach for spatially resolved polarization control by accurately retrieving the vector transmission matrix (VTM) of a scattering system from intensity-only, full-Stokes polarimetric measurements. Using a simple single-path setup comprising a liquid-crystal spatial light modulator (SLM) with a tunable retarder after it, we achieve spatial polarization modulation at the input, thereby enabling probing of the medium’s polarization–scattering characteristics. The VTM is retrieved with an adapted Gerchberg–Saxton procedure that enforces not only the measured output amplitudes but also the relative phase between the two orthogonal output polarization components obtained from the Stokes parameters. We show that a single retarder setting results in inter-block correlations in the retrieved VTM due to input coupling, while two linearly independent retarder settings decouple the intrinsic blocks and recover the full VTM. In our experiment, for a $16\times 16$ set of input–output spatial modes, the VTM is retrieved with about $90\%$ accuracy, enabling polarization-resolved focusing with up to $10\times$ enhancement for horizontal, vertical, arbitrary linear, and circular states. This work offers a compact framework for active polarization shaping and for polarimetric characterization of complex media, advancing our understanding of vectorial light–matter interactions. Full article

Integrating metasurface-based polarizing filters atop photodetectors enables the expansion of detection capabilities from intensity to polarization, offering significant potential for applications requiring high-precision discrimination in scientific, industrial, and defense sectors. However, such metasurfaces often introduce optical efficiency losses. Here, we present a long-wave infrared (8.6 μm) circularly polarized photodetector capable of direct chiral discrimination, eliminating the need for additional optical components. The polarization selectivity arises from Guided-Mode resonances (GMRs) excited by two horizontally offset right-trapezoidal unit cells within a chiral metasurface. This design exhibits a pronounced transmittance contrast (~100%) between left circularly polarized light (LCP) and right circularly polarized light (RCP) while maintaining fabrication simplicity via a conventional single-step lithographic process. The proposed detector is expected to achieve high-dimensional physical characterization by resolving polarization-encoded vectorial information, demonstrating enhanced performance in complex environments. Full article

On 22–23 April 2025, a seismic noise survey was conducted at the Maccalube di Aragona, a mud volcano field located in Sicily (southern Italy), with the aim of characterizing the background signal associated with vent activity and the shallow subsurface structure. The experiment, named DEMETRA (DEnse MaccalubE TRomino Acquisition), was carried out within the framework of the multidisciplinary INGV-PROMUD research project, which aims to identify key indicators of mud volcano activity and potential precursors of paroxysmal events. Ambient seismic noise was recorded at 21 sites using a three-component, 24-bit digital tromograph. Measurements were conducted with a dense spatial sampling scheme covering both vent areas and peripheral zones. Preliminary data analyses included spectral estimates, computation of horizontal-to-vertical spectral ratio (HVSR) curves and evaluation of the polarization patterns. The HVSR curves do not display clear amplification peaks but rather show deamplification at specific sites. The polarization patterns exhibit spatial consistency across the vent areas. In addition, transient signals were identified in the background noise at some sites; based on their spectral and polarization characteristics, these signals are possibly associated with degassing, mud emissions, or bubbling phenomena. The dense spatial coverage of the DEMETRA experiment provides a valuable dataset for investigating subsurface properties and dynamic processes in an active mud volcano environment. Full article

Brass components are widely used in heat dissipation and thermal emission devices due to their high thermal conductivity and ease of processing. However, these applications demand good thermal oxidation resistance, high emissivity, and excellent corrosion resistance. In this study, nickel coatings were deposited on brass substrates by direct current electroplating, and the effects of current density and cathode configuration on the microstructure, emissivity, and corrosion resistance of the coatings were systematically investigated. The results show that the emissivity of the coatings first increased and then decreased with increasing current density. Optimal performance was achieved when the cathode and anode were positioned perpendicular to the horizontal plane at a current density of 3.0 A·dm⁻². Under these conditions, the coatings exhibited a smooth, uniform, and dense microstructure, with evenly distributed metallic grains. Electrochemical polarization and impedance measurements further confirmed the superior corrosion resistance of this coating, with a minimum corrosion current density of 0.259 μA·cm⁻², a maximum polarization resistance of 6381.55 Ω·cm², and a minimum corrosion rate of 0.023 mm/a. These findings demonstrate a simple and effective approach to enhancing both the emissivity and corrosion resistance of brass substrates, offering practical value for thermal management applications. Full article

The rapid increase in production of small unmanned rotorcrafts (SURs) has made real-time drone surveillance critical for airspace security. Effective SUR detection is essential for maintaining aviation safety, protecting privacy, and ensuring public security. However, conventional radar systems struggle to detect hovering SURs due to their low velocity and small radar cross-section (RCS), which make them nearly indistinguishable from stationary clutter. To address this issue, this paper proposes a hovering SUR detection method through identifying the micro-Doppler signal (MDS). By applying the multiple reassignment squeeze processing and exhaustive Hough transform, the proposed approach effectively enhances the accumulation of micro-Doppler signal generated by the rotor blades, which enables the separation of hovering SUR signals from stationary clutter. Numerical simulations and field experiments validate the effectiveness of the proposed method, demonstrating its potential for micro-Doppler signal detection using a UHF-band horizontally co-polarized radar system. Full article

Background: This paper aims to provide an overview of corneal birefringence (CB), systematize the knowledge and current understanding of CB, and identify difficulties associated with introducing CB into mainstream clinical practice. Methods: Literature reviews were conducted, seeking articles focused on CB published between the early 19th century and the present time. Secondary-level searches were made examining relevant publications referred to in primary-level publications, ranging back to the early 17th century. The key search words were “corneal birefringence” and “non-invasive measurements”. Results: CB was first recorded by Brewster in 1815. Orthogonally polarized rays travel at different speeds through the cornea, creating a slow axis and a fast axis. The slow axis aligns with the pattern of most corneal stromal collagen fibrils. In vivo, it is oriented along the superior temporal–inferior nasal direction at an angle of about 25° (with an approximate range of −54° to 90°) from the horizontal. CB has been reported to (i) influence the estimation of retinal nerve fiber layer thickness; (ii) be affected by corneal interventions; (iii) be altered in keratoconus; (iv) vary along the depth of the cornea; and (v) be affected by intra-ocular pressure. Conclusions: Under precisely controlled conditions, capturing the CB pattern is the first step in a non-destructive process used to model the ultra-fine structure of the individual cornea, and changes thereof, in vivo. Full article

The severe ozone depletion over the Southern polar region, known as the “ozone hole,” is a stark example of global ozone depletion caused by human-made chemicals. This has implications for climate change and increased harmful surface solar UV. Several Chemistry–Climate models (CCMs) tend to underestimate total column ozone (TCO) against satellite measurements over the Southern polar region. This underestimation can reach up to 50% in monthly mean zonally averaged biases during cold seasons. The most significant discrepancies were found in the CCM SOlar Climate Ozone Links version 3 (SOCOLv3). We use SOCOLv3 to study the sensitivity of Antarctic TCO to three key factors: (1) stratospheric heterogeneous reaction efficiency, (2) meridional flux intensity into polar regions from sub-grid scale mixing, and (3) photodissociation rate calculation accuracy. We compared the model results with satellite data from Infrared Fourier Spectrometer-2 (IKFS-2), Microwave Limb Sounder (MLS), and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). The most effective processes for improving polar ozone simulation are photolysis and horizontal mixing. Increasing horizontal mixing improves the simulated TCO seasonal cycle but negatively impacts CH₄ and N₂O distributions. Using the Cloud-J v.8.0 photolysis module has improved photolysis rate calculations and the seasonal ozone cycle representation over the Southern polar region. This paper outlines how different processes impact chemistry–climate model performance in the southern polar stratosphere, with potential implications for future advancements. Full article

With the widespread adoption of virtual fitting technology in e-commerce and fashion, optimizing user experience through interface design has become increasingly critical. However, research on the usability of virtual fitting interaction interfaces remains limited. Current interfaces frequently suffer from disorganized information layouts and ambiguous auxiliary instructions, reducing efficiency and immersion. This study systematically investigates the effects of information layout (matrix layout, list layout, horizontal layout) and auxiliary instruction display mode (positive polarity: dark content on light background; negative polarity: light content on dark background) on user task performance and subjective experience. A between-subjects experiment was conducted with 60 participants across six conditions. Participants performed a series of tasks, and data were collected on task completion time, subjective ratings, and Technology Acceptance Model responses. Analyses were conducted using two-way ANOVA. The main findings were as follows: (1) The matrix layout demonstrated higher efficiency in multi-target search and complex decision-making tasks, and also received higher subjective ratings for perceived ease of use. (2) The positive polarity display mode demonstrated better performance in single-information search and cognitively intensive tasks, coupled with higher subjective ratings for interface rationality and information clarity. (3) A significant interaction effect was identified between information layout and display mode. The matrix layout combined with positive polarity improved efficiency, whereas the list layout with negative polarity impaired task performance. The horizontal layout was also rated lower for operational fluency. These findings provide practical guidance for designing virtual fitting interfaces that enhance both performance and subjective user experience. Full article

Early detection is crucial for preventing heart disease. Advances in health technology, particularly wearable devices for automated heartbeat detection and machine learning, can enhance early diagnosis efforts. However, previous studies on heartbeat classification inference systems have primarily relied on batch processing, which introduces delays. To address this limitation, a real-time system utilizing stream processing with a distributed computing architecture is needed for continuous, immediate, and scalable data analysis. Real-time ECG inference is particularly crucial for immediate heartbeat classification, as human heartbeats occur with durations between 0.6 and 1 s, requiring inference times significantly below this threshold for effective real-time processing. This study implements a real-time heartbeat classification inference system using distributed stream processing with LSTM-512, LSTM-256, and FCN models, incorporating RR-interval, morphology, and wavelet features. The system is developed as a distributed web-based application using the Flask framework with distributed backend processing, integrating Polar H10 sensors via Bluetooth and Web Bluetooth API in JavaScript. The implementation consists of a frontend interface, distributed backend services, and coordinated inference processing. The frontend handles sensor pairing and manages real-time streaming for continuous ECG data transmission. The backend processes incoming ECG streams, performing preprocessing and model inference. Performance evaluations demonstrate that LSTM-based heartbeat classification can achieve real-time performance on distributed edge devices by carefully selecting features and models. Wavelet-based features with an LSTM-Sequential architecture deliver optimal results, achieving 99% accuracy with balanced precision-recall metrics and an inference time of 0.12 s—well below the 0.6–1 s heartbeat duration requirement. Resource analysis on Jetson Orin devices reveals that Wavelet-FCN models offer exceptional efficiency with 24.75% CPU usage, minimal GPU utilization (0.34%), and 293 MB memory consumption. The distributed architecture’s dynamic load balancing ensures resilience under varying workloads, enabling effective horizontal scaling. Full article

Mangroves play a critical role in global carbon sequestration, biodiversity conservation, and climate change mitigation. Accurately quantifying mangrove biomass is essential for sustainable forest management and carbon accounting. Yet, the structural complexity and species diversity of mangrove ecosystems pose significant challenges for accurate estimation. In this study, we developed an integrated model that combines multispectral imagery and radar data. Using Sentinel-2 and ALOS-2 satellite imagery combined with field measurements, these data were used to construct linear regression and random forest models for the Matang Mangrove Reserve, Malaysia. We further analyzed the relationships between vegetation indices, radar polarization modes, and biomass. Results indicate that the average biomass is approximately 146 t/ha. The Optimized Soil-Adjusted Vegetation Index (OSAVI) and horizontal–vertical (HV) polarization showed the strongest correlation with field-measured biomass, with an R² of 0.735 and a root mean square error (RMSE) of 46.794 t/ha. This study provides a scientific basis and technical support for mangrove carbon stock assessment, ecosystem management, and climate change mitigation strategies, and highlights the potential of integrating optical and radar remote sensing for large-scale mangrove biomass monitoring. Full article