Search Results (16,566)

The utilization of metal roofing as natural air terminals is a standard practice in lightning protection; however, the risk of thermal perforation and subsequent ignition of internal hazardous atmospheres remains a critical safety concern. While current standards (e.g., IEC 62305) primarily focus on material thickness and total charge (Q), this study demonstrates that these parameters alone are insufficient for predicting burn-through failure. We present a comprehensive electrothermal analysis based on the method of images to simulate three-dimensional heat diffusion in finite-thickness plates (0.5–7 mm) made of aluminum, copper, and steel. Unlike simplified 1D models, our approach considers the spatial distribution of the heat source and the varying depth of the thermal penetration. The results confirm that the continuing current component ($Q_{long}\approx 200$ C) is the primary driver of volumetric melting. Crucially, the sensitivity analysis reveals that the lightning channel radius ($r_{mbo}$) acts as a governing factor for perforation risk; a reduction in the lightning channel radius from 5 mm to 2 mm can shift the outcome from minor surface heating to complete perforation for thin sheets ($0.5$ mm), even under identical charge conditions. This paper identifies a “safety gap” in current engineering practices, demonstrating that neglecting this parameter constriction effect results in an underestimation of the thermal threat. The proposed analytical model provides a precise tool for determining the safety margins of natural air terminals, offering direct applicability for designing lightning protection systems in high-risk industrial facilities. Full article

Source camera identification relies on sensor noise features to distinguish between different devices, but large-scale sample labeling is time-consuming and labor-intensive, making it difficult to implement in real-world applications. The noise residuals generated by different camera sensors exhibit statistical asymmetry, and the structured patterns within these residuals also show local symmetric relationships. Together, these features form the theoretical foundation for camera source identification. To address the problem of limited labeled data under few-shot conditions, this paper proposes a Cross-correlation Guided Augmentation and Prediction with Hybrid Bidirectional State-Space Model Attention (CGAP-HBSA) framework, based on the aforementioned symmetry-related theoretical foundation. The method extracts symmetric correlation structures from unlabeled samples and converts them into reliable pseudo-labeled samples. Furthermore, the HBSA network jointly models symmetric structures and asymmetric variations in camera fingerprints using a bidirectional SSM module and a hybrid attention mechanism, thereby enhancing long-range spatial modeling capabilities and recognition robustness. In the Dresden dataset, the proposed method achieves an identification accuracy for the 5-shot camera source identification task that is only 0.02% lower than the current best-performing method under few-shot conditions, MDM-CPS, and outperforms other classical few-shot camera source identification methods. In the 10-shot task, the method improves by at least 0.3% compared to MDM-CPS. In the Vision dataset, the method improves the identification accuracy in the 5-shot camera source identification task by at least 6% compared to MDM-CPS, and in the 10-shot task, it improves by at least 3% over the best-performing MDM-CPS method. Experimental results demonstrate that the proposed method achieves competitive or superior performance in both 5-shot and 10-shot settings. Additional robustness experiments further confirm that the HBSA network maintains strong performance even under image compression and noise contamination conditions. Full article

When training a neural network, the choice of activation function can greatly impact its performance. A function with a larger derivative may cause the coefficients of the latter layers to deviate further from the calculated direction, making deep learning more difficult to train. However, an activation function with a derivative amplitude of less than one can result in the problem of a vanishing gradient. To overcome this drawback, we propose the application of pseudo-normalization to enlarge some gradients by dividing them by the root mean square. This amplification is performed every few layers to ensure that the amplitudes are larger than one, thus avoiding the condition of vanishing gradient and preventing gradient explosion. We successfully applied this approach to several deep learning networks with hyperbolic tangent activation for image classifications. To gain a deeper understanding of the algorithm, we employed interpretability techniques to examine the network’s prediction outcomes. We discovered that, in contrast to popular networks that learn picture characteristics, the networks primarily employ the contour information of images for categorization. This suggests that our technique can be utilized in addition to other widely used algorithms. Full article

Purpose: Hyperparathyroidism (HPT) is a condition marked by excessive secretion of parathyroid hormone (PTH), leading to disturbances in calcium, phosphate, and vitamin D metabolism. HPT is classified into primary (pHPT), secondary (sHPT), and tertiary (tHPT) types, which can cause systemic complications. Parathyroidectomy (PTX) remains the cornerstone treatment for pHPT and refractory cases of sHPT and tHPT. Methods: A retrospective review was conducted on 10 pediatric patients who underwent PTX for HPT at our clinic between 2016 and 2024. Demographic data, preoperative imaging, laboratory findings, surgical details, pathology reports, and postoperative outcomes were analyzed. Patients were categorized as having either pHPT (n = 6) or renal HPT (r-HPT; n = 4), which included one case of sHPT and three cases of tHPT. Results: The mean age of pHPT and r-HPT patients was 15 and 13 years, respectively. While 50% of pHPT patients were female, all r-HPT patients were female. Preoperative imaging localized parathyroid lesions using ultrasonography in all cases, but Sestamibi scintigraphy had a lower detection rate (66.7%). Minimally invasive parathyroidectomy was performed in single-gland pHPT cases, while bilateral neck exploration was used for multiglandular pHPT and all r-HPT cases. No intraoperative complications were observed. Postoperatively, all patients demonstrated normalized calcium, phosphate, and PTH levels with significant symptomatic improvement. Hungry bone syndrome developed in one r-HPT patient and was managed successfully. No recurrences were noted during an average follow-up of 39 months. Conclusions: PTX is a safe and effective treatment for pediatric HPT, providing excellent biochemical and clinical outcomes. Multidisciplinary collaboration is crucial in managing pediatric cases, particularly those with complex renal HPT. Full article

Composite restorations are inevitably exposed to prophylactic procedures associated with a risk of surface damage (loss of substance and roughening). The aim of the present study was to compare the effect of air-polishing with three different powders of reduced abrasiveness on composite fillings. Forty-eight specimens of microhybrid light-cure composite were randomly divided into three groups (n = 16 each), scanned in 3D and air-polished with the following: sodium bicarbonate (40 µm), glycine (25 µm) and erythritol (14 µm), respectively. Then, the specimens were rescanned and the data were processed in specialized 3D analysis software. Loss of composite material was visible in all specimens. The estimated mean composite volume loss was higher for sodium bicarbonate and erythritol (0.09 mm³ and 0.08 mm³, respectively) than for glycine (0.05 mm³). No statistically significant differences were found between sodium bicarbonate and erythritol. Powder particles were additionally characterized from SEM images (N = 1600 per powder), using equivalent circular diameter (ECD) and shape descriptors (aspect ratio and circularity). Therefore, glycine powder should be preferred when the primary goal is minimizing composite abrasion. When higher composite material removal is acceptable, erythritol and sodium bicarbonate may be considered to be interchangeable under the present conditions due to their comparable abrasive effect. Full article

To address the challenges of cross-modal feature misalignment and ineffective information fusion caused by the inherent differences in imaging mechanisms, noise statistics, and semantic representations between visible and synthetic aperture radar (SAR) imagery, this paper proposes a multimodal remote sensing object detection method, namely YOLO-CMFM. Built upon the Ultralytics YOLOv11 framework, the proposed approach designs a Cross-Modal Fusion Module (CMFM) that systematically enhances detection accuracy and robustness from the perspectives of modality alignment, feature interaction, and adaptive fusion. Specifically, (1) a Learnable Edge-Guided Attention (LEGA) module is constructed, which leverages a learnable Gaussian saliency prior to achieve edge-oriented cross-modal alignment, effectively mitigating edge-structure mismatches across modalities; (2) a Bidirectional Cross-Attention (BCA) module is developed to enable deep semantic interaction and global contextual aggregation; (3) a Context-Guided Gating (CGG) module is designed to dynamically generate complementary weights based on multimodal source features and global contextual information, thereby achieving adaptive fusion across modalities. Extensive experiments conducted on the OGSOD 1.0 dataset demonstrate that the proposed YOLO-CMFM achieves an $mAP@50$ of 96.2% and an $mAP@50$:95 of 75.1%. While maintaining competitive performance comparable to mainstream approaches at lower IoU thresholds, the proposed method significantly outperforms existing counterparts at high IoU thresholds, highlighting its superior capability in precise object localization. Also, the experimental results on the OSPRC dataset demonstrate that the proposed method can consistently achieve stable gains under different kinds of imaging conditions, including diverse SAR polarizations, spatial resolutions, and cloud occlusion conditions. Moreover, the CMFM can be flexibly integrated into different detection frameworks, which further validates its strong generalization and transferability in multimodal remote sensing object detection tasks. Full article

Nano- and submicron particles (NSPs) with folate for targeting are actively used for the treatment and diagnosis of cancer and inflammatory diseases. Albumin-containing systems have enhanced biocompatibility, circulation time, and colloidal stability, which are important for medical applications. The outstanding binding properties of albumin allow the transport of numerous therapeutic and/or imaging agents. This review summarizes multiple aspects of binding a folate residue (or folic acid) to NSPs and the functioning of folate-albumin-NSPs. Special attention in the review is given to the types of bonds between folic acid and albumin, i.e., covalent and non-covalent, and to the confirmation and quantification of binding by different physicochemical methods. The process of binding, the qualitative and quantitative characteristics of binding and forming product, and its functioning are interconnected with the binding conditions; thus, an analysis of reaction conditions is provided. For the proper functioning of folate-albumin-NSPs, the state of albumin within them is important; thus, considerable focus in the review is placed on the features of structure modification of serum albumin in folate-albumin binding, i.e., the amino acid residues involved in this process and the conformational state of the protein. The stability and the functioning of the protein within folate-albumin-NSPs are discussed. Also, the effectiveness of targeting by folate is viewed as dependent on many characteristics of folate-albumin-NSPs, particularly on the peculiarities of binding between the folic acid residue and albumin. Furthermore, the authors discussed and suggested solutions concerning the shortcomings highlighted in the studies devoted to obtaining folate-modified albumin-containing NSPs. Full article

Background/Objectives: This systematic review examines neuroplasticity-informed approaches to learning under cognitive load, synthesizing evidence from functional imaging, brain stimulation, and educational technology research. As digital learning environments increasingly challenge learners with complex cognitive demands, understanding how neuroplasticity principles can inform adaptive educational design becomes critical. This review examines how neural mechanisms underlying learning under cognitive load can inform the development of evidence-based educational technologies that optimize neuroplastic potential while mitigating cognitive overload. Methods: Following PRISMA guidelines, we synthesized 94 empirical studies published between 2005 and 2025 across PubMed, Scopus, Web of Science, and PsycINFO. Studies were selected based on rigorous inclusion criteria that emphasized functional neuroimaging (fMRI, EEG), non-invasive brain stimulation (tDCS, TMS), and educational technology applications, which examined learning outcomes under varying cognitive load conditions. Priority was given to research with translational implications for adaptive learning systems and personalized educational interventions. Results: Functional imaging studies reveal an inverted-U relationship between cognitive load and neuroplasticity, with a moderate challenge in optimizing prefrontal-parietal network activation and learning-related neural adaptations. Brain stimulation research demonstrates that tDCS and TMS can enhance neuroplastic responses under cognitive load, particularly benefiting learners with lower baseline abilities. Educational technology applications demonstrate that neuroplasticity-informed adaptive systems, which incorporate real-time cognitive load monitoring and dynamic difficulty adjustment, significantly enhance learning outcomes compared to traditional approaches. Individual differences in cognitive capacity, neurodiversity, and baseline brain states substantially moderate these effects, necessitating the development of personalized intervention strategies. Conclusions: Neuroplasticity-informed learning approaches offer a robust framework for educational technology design that respects cognitive load limitations while maximizing adaptive neural changes. Integration of functional imaging insights, brain stimulation protocols, and adaptive algorithms enables the development of inclusive educational technologies that support diverse learners under cognitive stress. Future research should focus on scalable implementations of real-time neuroplasticity monitoring in authentic educational settings, as well as on developing ethical frameworks for deploying neurotechnology-enhanced learning systems across diverse populations. Full article

Sulfides are essential tracers for understanding the redox conditions, diffusion processes, and thermal mechanisms involved in the formation of ordinary chondrites. Their mineralogical and textural evolution provides valuable constraints on the metamorphic history of parent bodies. In this context, the Ksar El Goraane meteorite, which fell in Morocco in 2018 and is classified as an H5 ordinary chondrite, represents a particularly instructive case for investigating sulfur behavior during thermal metamorphism. Petrographic observations combined with geochemical data obtained by electron probe microanalysis (EPMA) and energy-dispersive X-ray spectroscopy (EDS) were used to characterize the main silicate and sulfide phases and to evaluate their degree of chemical equilibration. The compositions of olivine (Fa_18–20), Mg-Rich orthopyroxene, and sodic plagioclase (An_10–15) display limited analytical dispersion and well-recrystallized textures, confirming that Ksar El Goraane experienced an equilibrated metamorphic grade consistent with an H5 ordinary chondrite. The sulfide assemblage is dominated by troilite (FeS), iron-rich pyrrhotite (Fe_1−xS), and pentlandite ((Fe,Ni)₉S₈), with minor occurrences of pyrite (FeS₂). Textural relationships and chemical homogeneity observed in backscattered electron images and elemental maps indicate progressive re-equilibration during thermal metamorphism. Formation and transformation temperatures of the sulfide phases are inferred through comparison with experimental and empirical constraints reported in the literature. These results suggest early high-temperature crystallization of troilite, followed by sulfur depletion leading to pyrrhotite formation, subsequent low-temperature exsolution of pentlandite, and localized late-stage pyrite crystallization. Full article

Background: Rosacea is a chronic facial skin disease in which persistent erythema is a significant clinical problem, often resistant to standard therapies. Intensive pulsating light (IPL) has become a recognised and effective method of treating erythema and telangiectasia. The latest recommendations emphasise the advantage of combining subjective clinical assessments with objective imaging analyses in monitoring therapy effects. Methods: A total of 20 patients with rosacea qualified for this study. They were subjected to three polychromatic light procedures (Lumecca, Inmode; wavelength of 515–1200 nm) at 21-day intervals. The skin condition was documented photographically, and the degree of erythema was assessed on the basis of the Clinician Erythema Assessment (CEA) scale and objective analysis of the skin texture, using the parameters of contrast and homogeneity of the grey level co-occurrence matrix (GLCM). Results: A series of three polychromatic light treatments yielded a significant clinical improvement in all patients. The mean CEA value decreased by 61.11%, whereas the GLCM contrast in all the analysed facial areas dropped by about 17%, and homogeneity increased by 4–5%. The effects persisted for at least three months after the treatments. A high correlation of CEA scale results with GLCM parameters (R = 0.81–0.94 for contrast; R = −0.77 to −0.83 for homogeneity) was observed. Conclusions: Three polychromatic light treatments proved to be a very effective method of reducing erythema in rosacea, confirmed by both clinical evaluation and objective imaging analysis. The effects of therapy were durable and clear. Integration of the subjective method (CEA) with GLCM analysis can be a path for future research and clinical practice in the assessment of erythematous skin lesions. Full article

Reliable assessment of building damage is essential for effective disaster management. Synthetic Aperture Radar (SAR) has become a valuable tool for damage detection, as it operates independently of the daylight and weather conditions. However, the limited availability of high-resolution pre-disaster SAR data remains a major obstacle to accurate damage evaluation, constraining the applicability of traditional change-detection approaches. This study proposes a comprehensive framework that leverages generated SAR data alongside optical imagery for building damage detection and further examines the influence of elevation data quality on SAR synthesis and model performance. The method integrates SAR image synthesis from a Digital Surface Model (DSM) and land cover inputs with a multimodal deep learning architecture capable of jointly localizing buildings and classifying damage levels. Two data modality scenarios are evaluated: a change-detection setting using pre-disaster authentic SAR and another using GAN-generated SAR, both combined with post-disaster SAR imagery for building damage assessment. Experimental results demonstrate that GAN-generated SAR can effectively substitute for authentic SAR in multimodal damage mapping. Models using generated pre-disaster SAR achieved comparable or superior performance to those using authentic SAR, with $F_1$ scores of 0.730, 0.442, and 0.790 for the survived, moderate, and destroyed classes, respectively. Ablation studies further reveal that the model relies more heavily on land cover segmentation than on fine elevation details, suggesting that coarse-resolution DSMs (30 m) are sufficient as auxiliary input. Incorporating additional training regions further improved generalization and inter-class balance, confirming that high-quality generated SAR can serve as a viable alternative especially in the absence of authentic SAR, for scalable, post-disaster building damage assessment. Full article

To address the issue of climate change caused by greenhouse gases, extensive research has been conducted on technologies for separating and capturing carbon dioxide. This study aimed to investigate the internal flow behavior and relative spatial distribution of CO₂-related features inside a vortex tube using the Schlieren method. Due to the presence of numerous components in a typical counter-flow vortex tube that may cause optical refraction along the measurement path, a simplified tube with a single nozzle was designed and manufactured for the experiments. The experiments consisted of CO₂ single-phase flow and air–CO₂ mixture flow tests. Images captured during the experiments were processed using Gaussian filtering and background correction to enhance the visibility of boundary layers and internal flow structures. Based on the pixel intensity values of the processed Schlieren images, relative intensity distributions associated with CO₂-related flow behavior inside the tube were estimated and visualized. The experimental results revealed that, in both CO₂ single-phase and air–CO₂ mixture flows, regions of relatively high Schlieren intensity consistently appeared at specific locations within the tube. These observations indicate that the internal flow structure and relative distribution patterns are sensitive to the local flow features near the nozzle region under the tested conditions. The temporal evolution of the normalized Schlieren pixel intensity and its standard deviation was quantitatively evaluated, in a relative sense, to characterize the development of vortex flow structures under different operating conditions. The proposed visualization and analysis framework provides a systematic qualitative approach, supported by relative quantitative indicators, for investigating vortex-induced flow behavior. This framework may serve as a foundation for future studies that integrate complementary diagnostics and numerical analyses to further explore the vortex-based gas separation mechanism. Full article

To address the limitations of conventional wavefront sensorless adaptive optics (AO) systems regarding iteration efficiency and convergence speed, this study conducts an experimental validation of a model-based wavefront sensorless AO approach. A physical experimental platform was established, which consisted of a light source, a Shack–Hartmann wavefront sensor, a deformable mirror (DM), and an imaging detector. Wavefront aberrations under different turbulence levels were employed as correction objects to evaluate the performance of the model-based wavefront sensorless AO system. For comparative analysis, experimental results obtained by using the classical stochastic parallel gradient descent (SPGD) control algorithm are also presented. Under identical software and hardware conditions, the experimental results show that as the turbulence level increases, the SPGD-based wavefront sensorless AO system requires a larger number of iterations and exhibits a slower convergence. In contrast, the model-based wavefront sensorless AO system demonstrates improved applicability and robustness in correcting large aberrations under strong turbulence levels, maintaining an almost constant convergence speed and achieving better correction performance. These findings offer theoretical insights and technical support for the real-time correction potential of large wavefront aberrations. Full article

In the digital era, protecting the integrity and ownership of digital content is increasingly crucial, particularly against unauthorized copying and tampering. Traditional watermarking techniques often struggle to remain robust under various image manipulations, leading to a need for more resilient methods. To address this challenge, we propose a novel watermarking technique that integrates the Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD), and Schur matrix factorization to embed a QR code as a watermark into digital images. Our method was rigorously tested across a range of common image attacks, including histogram equalization, salt-and-pepper noise, ripple distortions, smoothing, and extensive cropping. The results demonstrate that our approach significantly outperforms existing methods, achieving high normalized correlation (NC) values such as 0.9949 for histogram equalization, 0.9846 for salt-and-pepper noise (2%), 0.96063 for ripple distortion, 0.9670 for smoothing, and up to 0.9995 under 50% cropping. The watermark consistently maintained its integrity and scannability under all tested conditions, making our method a reliable solution for enhancing digital copyright protection. Full article

Coastal sandbars play a crucial role in shoreline protection, yet monitoring their dynamics remains challenging due to the cost and limited temporal coverage of traditional surveys. This study assesses the feasibility of using Sentinel-2 multispectral imagery combined with the logarithmic band ratio method to automatically detect submerged sandbar crests along three morphologically distinct beaches on the northwestern Mediterranean coast. Pseudo-bathymetry was derived from log-transformed band ratios of blue-green and blue-red reflectance used to extract the sandbar crest and validated against high-resolution in situ bathymetry. The blue-green band ratio achieved higher accuracy than the blue-red band ratio, which performed slightly better in very shallow waters. Its application across single, single/double, and double shore-parallel bar systems demonstrated the robustness and transferability of the approach. However, the method requires relatively clear or calm water conditions, and breaking-wave foam, sunglint, or cloud cover conditions limit the number of usable satellite images. A temporal analysis at a dissipative beach further revealed coherent bar migration patterns associated with storm events, consistent with observed hydrodynamic forcing. The proposed method is cost-free, computationally efficient, and broadly applicable for large-scale and long-term sandbar monitoring where optical water clarity permits. Its simplicity enables integration into coastal management frameworks, supporting sediment-budget assessment and resilience evaluation in data-limited regions. Full article