Search Results (465)

Structural collapses caused by accidents or disasters could create unexpected radiation shielding, resulting in sharp gradients within the radiation field. Traditional radiation mapping methods often fail to accurately capture these complex variations, making the rapid and precise localization of radiation sources a significant challenge in emergency response scenarios. To address this issue, based on standard Gaussian process regression (GPR) models that primarily utilize a single Gaussian kernel to reflect the inverse-square law in free space, a novel multi-kernel Gaussian process regression (MK-GPR) model is proposed for high-fidelity radiation mapping in environments with physical obstructions. MK-GPR integrates two additional kernel functions with adaptive weighting: one models the attenuation characteristics of intervening materials, and the other captures the energy-dependent penetration behavior of radiation. To validate the model, gamma-ray distributions in complex, shielded environments were simulated using GEometry ANd Tracking 4 (Geant4). Compared with conventional methods, including linear interpolation, nearest-neighbor interpolation, and standard GPR, MK-GPR demonstrated substantial improvements in key evaluation metrics, such as MSE, RMSE, and MAE. Notably, the coefficient of determination (R²) increased to 0.937. For practical deployment, the optimized MK-GPR model was deployed to an RK-3588 edge computing platform and integrated into a mobile robot equipped with a NaI(Tl) detector. Field experiments confirmed the system’s ability to accurately map radiation fields and localize gamma sources. When combined with SLAM, the system achieved localization errors of 10 cm for single sources and 15 cm for dual sources. These results highlight the potential of the proposed approach as an effective and deployable solution for radiation source investigation in post-disaster environments. Full article

Complex oxides with the general formula Gd₂(Ti_1−xZr_x)₂O₇ are promising candidates for radioactive waste immobilization due to their capacity to withstand radiation by dissipating part of the free energy driving defect creation and phase transitions. In this study, samples with varying zirconium content (xZr = 0.00, 0.15, 0.25, 0.375, 0.56, 0.75, 0.85, 1.00) were synthesized via the sol–gel method and thermally treated at 500 °C to obtain nanosized powders mimicking the defective structure of irradiated materials. Synchrotron-based techniques were employed to investigate their structural properties: High-Resolution X-ray Powder Diffraction (HR-XRPD) was used to assess long-range structure, while Pair Distribution Function (PDF) analysis and Extended X-ray Absorption Fine Structure (EXAFS) spectroscopy provided insights into the local structure. HR-XRPD data revealed that samples with low Zr content (xZr ≤ 0.25) are amorphous. Increasing Zr concentration led to the emergence of a crystalline phase identified as defective fluorite (xZr = 0.375, 0.56). Samples with the highest Zr content (xZr ≥ 0.75) were fully crystalline and exhibited only the fluorite phase. The experimental G(r) functions of the fully crystalline samples in the low r range are suitably fitted by the Weberite structure, mapping the relaxations induced by structural disorder in defective fluorite. These structural insights informed the subsequent EXAFS analysis at the Zr-K and Gd-L₃ edges, confirming the splitting of the cation–cation distances associated with different metal species. Moreover, EXAFS provided a local structural description of the amorphous phases, identifying a consistent Gd-O distance across all compositions. Full article

Rare (only 10) observations, made in the southern topside ionosphere during 2015–2016, demonstrate the amplification of westward subauroral polarization streams (SAPS) up to 3000 m/s near the Harang region. The observed amplified SAPS flows were streaming antisunward after midnight and sunward at midnight, where the dusk convection cell intruded dawnward. One SAPS event illustrates the elevated electron temperature (Te; ~5500 K) and the stable auroral red arc developed over Rothera. Three inner-magnetosphere SAPS events depict the Harang region’s earthward edge within the plasmasheet’s earthward edge, where the outward SAPS electric (E) field (within the downward Region 2 currents) and inward convection E field (within the upward Region 2 currents) converged. Under isotropic or weak anisotropic conditions, the hot zone was fueled by the interaction of auroral kilometric radiation waves and electron diamagnetic currents. Generated for the conjugate topside ionosphere, the SAMI3 simulations reproduced the westward SAPS flow in the deep electron density trough, where Te became elevated, and the dawnward-intruding westward convection flows. We conclude that the near-midnight westward SAPS flow became amplified because of the favorable conditions created near the Harang region by the convection E field reaching subauroral latitudes and the positive feedback mechanisms in the SAPS channel. Full article

The sudden increase of fluxes of quasi-trapped energetic electrons under the Earth’s radiation belt (ERB) has remained a puzzling phenomenon for decades. It is known as enhancements of forbidden energetic electrons (FEEs). The FEE enhancements are occasionally observed by low-Earth orbit NOAA/POES satellites. Previously, no strong correlation was established between FEEs and geomagnetic activity, while external control of FEE occurrence by solar activity and interplanetary parameters was revealed on a long time-scale. Two important questions are still open: (1) key parameters of the mechanism and (2) solar wind drivers or triggers. In the present study we conducted detailed analysis of three FEE events that occurred during the greatest geomagnetic storms, which dramatically affected space weather. The FEE enhancements occurred under northward IMF and, thus, Bz and convection electric fields could have been neither driver nor trigger. We found that an abrupt and significant change in solar wind pressure is a key solar wind driver of the FEE enhancements observed. The characteristic time of FEE injection from the inner edge of the ERB at L-shell 1.2 to the forbidden zone at L < 1.1 was estimated to be 10–20 min. In the mechanism of ExB drift, this characteristic time corresponds to the radial inward transport of electrons caused by a transient electric field with the magnitude ~10 mV/m. Full article

This paper presents the development and analysis of a planar microfluidic microwave sensor featuring three circular complementary split-ring resonators (CSRRs) fabricated on an RO3035 substrate. The sensor demonstrates enhanced sensitivity in characterizing liquids contained in a fine glass capillary tube by leveraging a novel configuration: a central 5-split-ring CSRR with a drilled hole to suspend the capillary, flanked by two 2-split-ring CSRRs to improve the band-stop filtering effect. The sensor’s performance is benchmarked against another CSRR-based microwave sensor with a similar configuration. High linearity is observed (R² > 0.99), confirming its capability for precise ethanol concentration prediction. Compared to the replicated square CSRR design from the literature, the proposed sensor achieves a 35.22% improvement in sensitivity, with a frequency shift sensitivity of 567.41 kHz/% ethanol concentration versus 419.62 kHz/% for the reference sensor. The enhanced sensitivity is attributed to several key design strategies: increasing the intrinsic capacitance by enlarging the effective area and radial slot width to amplify edge capacitive effects, adding more split rings to intensify the resonance dip, placing additional CSRRs to improve energy extraction at resonance, and adopting circular CSRRs for superior electric field confinement. Additionally, the proposed design operates at a lower resonant frequency (2.234 GHz), which not only reduces dielectric and radiation losses but also enables the use of more cost-effective and power-efficient RF components. This advantage makes the sensor highly suitable for integration into portable and standalone sensing platforms. Full article

This paper presents a circularly polarized (CP) antenna based on crossed dipoles with bandpass-type filtering radiation response. The antenna employs a pair of crossed dipole arms as radiators, which are printed on the upper and lower planes of the substrate. To achieve bandpass filtering effects, radiation nulls are introduced on both sides of the passband. By vertically extending the ends of the four dipole arms, a ring-shaped current is formed between adjacent dipoles, generating the upper-band radiation null. Additionally, four parasitic patches are introduced parallel to the ends of the crossed dipole arms, creating another upper-band radiation null, further enhancing the frequency selectivity at the band edges and broadening the axial ratio (AR) bandwidth. Moreover, a square-ring slot is etched on the ground plane to introduce a lower-band radiation null, ultimately achieving a good bandpass filtering response. The proposed wideband CP filtering dipole antenna is implemented and tested. The antenna has a compact size of 0.49${\lambda }_0\times$ 0.49${\lambda }_0\times$ 0.16${\lambda }_0$ (where ${\lambda }_0$ denotes the wavelength corresponding to the lowest operating frequency). The measured results show that the proposed antenna has an impedance bandwidth of 75% (1.65–3.66 GHz) and an overlapping AR bandwidth of 46.9% (2.25–3.63 GHz). Without additional filtering circuits, the antenna exhibits a stable gain of approximately 7 dB and three radiation nulls, with suppression levels of 20 dB in both the lower and upper stopbands, achieving good bandpass filtering performance. Full article

The article presents a three-stage methodology for calibrating 3D printing using mSLA technology, aimed at improving dimensional accuracy and print repeatability. The proposed approach is based on procedures that enable the collection and analysis of numerical data, thereby minimizing the influence of the operator’s subjective judgment, which is commonly relied upon in traditional calibration methods. In the first stage, compensation for the uneven illumination of the LCD matrix was performed by establishing a regression model that describes the relationship between UV radiation intensity and pixel brightness. Based on this model, a grayscale correction mask was developed. The second stage focused on determining the optimal exposure time, based on its effect on dimensional accuracy, detail reproduction, and model strength. The optimal exposure time is defined as the duration that provides the highest possible mechanical strength without significant loss of detail due to the light bleed phenomenon (i.e., diffusion of UV radiation beyond the mask edge). In the third stage, scale correction was applied to compensate for shrinkage and geometric distortions, further reducing the impact of light bleed on the dimensional fidelity of printed components. The proposed methodology was validated using an Anycubic Photon M3 Premium printer with Anycubic ABS-Like Resin Pro 2.0. Compensating for light intensity variation reduced the original standard deviation from 0.26 to 0.17 mW/cm², corresponding to a decrease of more than one third. The methodology reduced surface displacement due to shrinkage from 0.044% to 0.003%, and the residual internal dimensional error from 0.159 mm to 0.017 mm (a 72% reduction). Full article

Y₅F₃[AsO₃]₄ crystallizes needle-shaped in the tetragonal space group P4/ncc with the lattice parameters a = 1143.80(8) pm, c = 1078.41(7) pm and c/a = 0.9428 for Z = 4. The yttrium-fluoride substructure linked via secondary contacts forms a three-dimensional network $\begin{array}{c}3\\ \infty \end{array}${[Y₅F₃]¹²⁺} and the remaining part consists of ψ¹-tetrahedral [AsO₃]³⁻ units, which leave lone-pair channels along [001]. In contrast, platelet-shaped Y₅Cl₃[AsO₃]₄ crystals adopt the monoclinic space group C2/c with the lattice parameters a = 1860.56(9) pm, b = 536.27(3) pm, c = 1639.04(8) pm and β = 105.739(3)° for Z = 4. Condensation of [(Y1,2)O₈]¹³⁻ polyhedra via four common edges each leads to fluorite-like $\begin{array}{c}2\\ \infty \end{array}$ {[(Y1,2)O $\begin{array}{c}e\\ 8/2\end{array}$ ]⁵⁻} layers spreading out parallel to the (100) plane. Their three-dimensional linkage occurs via the (Y3)³⁺ cations with their Cl⁻ ligands on the one hand and the As³⁺ cations with their lone-pairs of electrons on the other, which also form within [AsO₃]³⁻ anions lone-pair channels along [010]. Both colorless compounds can be obtained by solid-state reactions from corresponding mixtures of the binaries (Y₂O₃, As₂O₃ and YX₃ with X = F and Cl) at elevated temperatures of 825 °C, most advantageously under halide-flux assistance (CsBr for Y₅F₃[AsO₃]₄ and ZnCl₂ for Y₅Cl₃[AsO₃]₄). By replacing a few percent of YX₃ with EuX₃ or TbX₃, Eu³⁺- or Tb³⁺-doped samples are accessible, which show red or green luminescence upon excitation with ultraviolet radiation. Full article

Multi-modal remote sensing images often exhibit complex and nonlinear radiation differences which significantly hinder the performance of traditional feature-based image registration methods such as Scale-Invariant Feature Transform (SIFT). In contrast, structural features—such as edges and contours—remain relatively consistent across modalities. To address this challenge, we propose a novel multi-modal image registration method, Cof-SIFT, which integrates a co-occurrence filter with SIFT. By replacing the traditional Gaussian filter with a co-occurrence filter, Cof-SIFT effectively suppresses texture variations while preserving structural information, thereby enhancing robustness to cross-modal differences. To further improve image registration accuracy, we introduce an extended approach, Cof-SIFT_HOG, which extracts Histogram of Oriented Gradients (HOG) features from the image gradient magnitude map of corresponding points and refines their positions based on HOG similarity. This refinement yields more precise alignment between the reference and image to be registered. We evaluated Cof-SIFT and Cof-SIFT_HOG on a diverse set of multi-modal remote sensing image pairs. The experimental results demonstrate that both methods outperform existing approaches, including SIFT, COFSM, SAR-SIFT, PSO-SIFT, and OS-SIFT, in terms of robustness and registration accuracy. Notably, Cof-SIFT_HOG achieves the highest overall performance, confirming the effectiveness of the proposed structural-preserving and corresponding point location refinement strategies in cross-modal registration tasks. Full article

Monocular depth estimation (MDE) has emerged as a powerful technique for extracting scene depth from a single image, particularly in the context of computational imaging. Conventional MDE methods based on RGB images often degrade under varying illuminations. To overcome this, an end-to-end framework is developed that leverages the illumination-invariant properties of infrared images for accurate depth estimation. Specifically, a multi-task UNet architecture was designed to perform gradient extraction, semantic segmentation, and texture reconstruction from infrared RAW images. To strengthen structural learning, a Radiation Field Gradient Guidance (RGG) module was incorporated, enabling edge-aware attention mechanisms. The gradients, semantics, and textures were mapped to the Saturation (S), Hue (H), and Value (V) channels in the HSV color space, subsequently converted into an RGB format for input into the depth estimation network. Additionally, a sky mask loss was introduced during training to mitigate the influence of ambiguous sky regions. Experimental validation on a custom infrared dataset demonstrated high accuracy, achieving a ${\delta }_1$ of 0.976. These results confirm that integrating radiation field gradient guidance and semantic priors in HSV space significantly enhances depth estimation performance for infrared imagery. Full article

Infrared video satellites have the characteristics of wide-area long-duration surveillance, enabling continuous operation day and night compared to visible light imaging methods. Therefore, they are widely used for continuous monitoring and tracking of important targets. However, energy attenuation caused by long-distance radiation transmission reduces imaging contrast and leads to the loss of edge contours and texture details, posing significant challenges to target tracking algorithm design. This paper proposes an infrared small-target tracking method, the UIMM-Tracker, based on the tracking-by-detection (TbD) paradigm. First, detection uncertainty is measured and injected into the multi-model observation noise, transferring the distribution knowledge of the detection process to the tracking process. Second, a dynamic modulation mechanism is introduced into the Markov transition process of multi-model fusion, enabling the tracking model to autonomously adapt to targets with varying maneuvering states. Additionally, detection uncertainty is incorporated into the data association method, and a distance cost matrix between trajectories and detections is constructed based on scale and energy invariance assumptions, improving tracking accuracy. Finally, the proposed method achieves average performance scores of 68.5%, 45.6%, 56.2%, and 0.41 in IDF1, MOTA, HOTA, and precision metrics, respectively, across 20 challenging sequences, outperforming classical methods and demonstrating its effectiveness. Full article

Against the background of the vigorous development of materials science and the deep cross-infiltration in many fields, a new medicine food homology, carbon dots (herein combined and abbreviated as MFH-CDs), has sprung up, showing great potential. This review used ChatGPT 4.0 to collect background information related to carbon dots, focusing on the common rich medicinal and food resources such as Lycium barbarum, Chinese yam, honeysuckle, and Ganoderma lucidum. These carbon dots are synthesized by hydrothermal synthesis, microwave radiation, and pyrolysis, which have the advantages of small particle size, high quantum yield, and low cytotoxicity. Recent studies have found that MFH-CDs have great application potential in biosensors, biological imaging, and drug delivery. In this paper, the characteristics of preparing carbon dots from different medicinal and edible resources and their applications in biology in recent years are reviewed, which provides in-depth guidance for the research and application of carbon dots from medicinal and edible biomass, helps it shine in multidisciplinary fields, and opens a brand-new journey from traditional medicinal and edible culture to cutting-edge technology application. Full article

During the launching process of electromagnetic projectiles, radiated noise, smoke, and debris will interfere with the line of sight and affect the accuracy of initial attitude estimation. To address this issue, an enhanced method that integrates Mask R-CNN and a multi-constraint genetic algorithm was proposed. First, Mask R-CNN was utilized to perform pixel-level edge segmentation of the original image, followed by the Canny algorithm to extract the edge image. This edge image was then processed using the line segment detector (LSD) algorithm to identify the main structural components, characterized by line segments. An enhanced genetic algorithm was employed to restore the occluded edge image. A fitness function, constructed with Hamming distance (HD) constraints alongside initial parameter constraints defined by centroid displacement, was applied to boost convergence speed and avoid local optimization. The optimized search strategy minimized the HD constraint between the repaired stereo images to obtain accurate attitude output. An electromagnetic simulation device was utilized for the experiment. The proposed method was 13 times faster than the Structural Similarity Index (SSIM) method. In a single launch, the target with 70% occlusion was successfully recovered, achieving average deviations of 0.76°, 0.72°, and 0.44° in pitch, roll, and yaw angles, respectively. Full article

Background/Objectives: Radiodermitis is an inflammatory or dystrophic skin process caused by the direct action of ionizing radiation. The primary objective was to study two clinical cases. The secondary objective was to propose the foundations of an intelligent system for decision support in complex cases of radiodermitis diagnosis that can operate even in the case of a low amount of available clinical data that can be used for training. Methods: The first case is a female patient, aged 74 years, with squamous cell carcinoma on a chronic radiodermitis site, which appeared after 20 years of local radiotherapy treatment for mammary adenocarcinoma. Dermatologic examination revealed five round-oval nodules between 2 and 8 cm in diameter. They were pink colored with lilac edges, hard and infiltrated on palpation, adherent to the subcutaneous tissue, painless, and located above and lateral on the right chest and the upper region of the right hypochondrium. The second case concerns a 60-year-old patient with verrucous squamous cell carcinoma appearing on a chronic radiodermatitis 40 years after local radio-therapeutic treatment with Chaoul rays for a deep right temporal region mycosis. There are presented artificial intelligence (AI) challenges regarding the application of advanced hybrid models in decision support for diagnosis of difficult radiodermitis cases, in that intelligent computing must be made in the context of very little available data, and collaboration between physicians is necessary. Results: Both cases were confirmed by histology as squamos cell carcinomas. In the AI research, the adaptation of the IntMediSys intelligent system was proposed for solving complex cases of radiodermitis. The proposal integrates different AI technologies, which include agents, intelligent computing, and blackboard systems. Conclusions: The presented first cases confirm the presence of a squamous cell carcinoma that appeared on chronic radiodermitis after a long latency. The foundations of a highly complex collaboration and decision support system that can assist physicians in the radiodermitis diagnostics establishment that opens the path for further development are presented. Full article

Clouds play a central role in regulating incoming solar radiation and outgoing terrestrial emission; hence, they must be internally constrained to prognose Earth’s temperature. At the same time, planetary fluids are inherently turbulent, so the climate state would tend toward maximum entropy production—a generalized second law of thermodynamics. Incorporating these requirements, I have previously formulated an aquaplanet model to demonstrate that intrinsic water properties may strongly lower the climate sensitivity to solar irradiance, thereby resolving the faint young Sun paradox (FYSP). In this paper, I extend the model to include other external forcings and show that sensitivity to the reduced outgoing longwave radiation by the elevated pCO₂ can be several times greater, but the global temperature remains capped at ~40 °C by the exponential increase in saturated vapor pressure. I further show that planetary albedo augmented by a tropical supercontinent may cool the climate sufficiently to cause tropical glaciation. And since the glacial edge is marked by above-freezing temperature, it abuts an open, co-zonal ocean, thereby obviating the “Snowball Earth” hypothesis. Our theory thus provides a unified framework for interpreting Earth’s diverse climates, including the FYSP, the warm extremes of the Cambrian and Cretaceous, and the tropical glaciations of the Precambrian. Full article