Search Results (447)

This study presents the results of over thirty years of non-destructive testing (NDT) in a historic church, providing an unprecedented time analysis of the structural and material integrity of the building and its works of art. During this time, the church has undergone several restorations and two major seismic events. The diagnostics, which include a calibrated mix of established and advanced micro-destructive and non-destructive (NDT) techniques such as X-ray fluorescence, holographic interferometry, electronic speckle pattern interferometry (ESPI), infrared thermography, and IR reflectography, provide critical insights into the impact of the restoration interventions and the earthquakes on the church’s artistic heritage. The results indicate varying degrees of effectiveness of the restoration efforts, highlighting both areas of successful conservation and emerging vulnerabilities. This long-term study highlights the importance of continuous monitoring and its integration with NDT in identifying the effects of time and strong events occurring during the life of artworks that influence their state of conservation. Full article

Although GPUs are widely used in Computer-Generated Holography (CGH), their specific application to concrete problems such as occlusion or speckle filtering through temporal multiplexing is not yet standardized and has not been fully explored. This work aims to optimize the software architecture by taking the GPU architecture into account in a novel way for these particular tasks. We present an optimized algorithm for CGH computation that provides a joint solution to the problems of speckle noise and occlusion. The workflow includes the generation and illumination of a 3D scene, the calculation of the CGH including color, occlusion, and temporal speckle-noise filtering, followed by scene reconstruction through both simulation and experimental methods. The research focuses on implementing a temporal multiplexing technique that simultaneously performs speckle denoising and occlusion culling for point clouds, evaluating two types of occlusion that differ in whether the occlusion effect dominates over the depth effect in a scene stored in a CGH, while leveraging the parallel processing capabilities of GPUs to achieve a more immersive and high-quality visual experience. To this end, the total computational cost associated with generating color and occlusion CGHs is evaluated, quantifying the relative contribution of each factor. The results indicate that, under strict occlusion conditions, temporal multiplexing filtering does not significantly impact the overall computational cost of CGH calculation. Full article

Aiming at the challenges faced by the detection of small-scale ship targets in Synthetic Aperture Radar (SAR) images, this paper proposes a novel deep learning network named FAWT-Net based on attention-matrix despeckling and Haar wavelet reconstruction. This network collaboratively optimizes the detection performance through three core modules. First, during the feature transfer stage from backbone to the neck, a filtering module based on attention matrix is designed, which can suppress the speckle noise. Then, during feature upsampling stage, a wavelet transform feature upsampling method for reconstructing image details is designed to enhance the distinguishability of target boundaries and textures. At the same time, the network also combines sub-image feature stitching downsampling to avoid losing key details in small targets, and adopts a scale-sensitive detection head. By adaptively adjusting the shape constraints of prediction boxes, it effectively solves the regression deviation problem of ship targets with inconsistent aspect ratios. Verified by experiments on SSDD and LS-SSDD, the proposed method improves AP50 by 1.3% and APS by 0.8% on the SSDD. Meanwhile, it is verified that the proposed method has higher precision and recall rates on the LS-SSDD, and the recall rate has been increased by 2.2%. Full article

Background and Objectives: The aim of this study is to evaluate the changes in speckle tracking velocity vector analysis (VVI) values within the descending thoracic aorta (DTA) in patients with cardiogenic shock (CS) who are on mechanical ventilation (MV), under varying levels of positive end-expiratory pressure (PEEP). Materials and Methods: Transthoracic echocardiography (TTE) was performed during incremental increases in positive end-expiratory pressure (PEEP) from 0 to 15 cmH₂O over 15 to 30 min. The effects of increased PEEP on velocities, displacement, strain (S), and strain rate (SR) were evaluated. DTA speckle tracking values were analyzed to determine their association with patient mortality. A control group of healthy individuals was used to establish normal DTA variables. Results: Sixty-two mechanically ventilated patients were included in this study. The mean age was 62.48 ± 11.22 years. The highest values for various parameters were obtained with 5 cmH₂O PEEP. The values obtained for DTA using speckle tracking at increasing PEEP levels (ZEEP, PEEP 5, PEEP 10, and PEEP 15 cm H₂O) were as follows: DTA rotational velocity [55.18 ± 14.60, 107.39 ± 19.33, 60.05 ± 0.28, and 42.11 ± 0.34°/s], DTA radial velocity [0.80 ± 0.09, 2.21 ± 0.27, 0.99 ± 0.16, 0.56 ± 0.17 cm/s], DTA rotational displacement [5.68 ± 0.40, 15.71 ± 0.13, 5.98 ± 0.35, 6.64 ± 3.45°], circumferential strain for DTA [−8.55 ± 0.92, −11.86 ± 0.07, −9.88 ± 0.25, −8.76 ± 0.6%], and DTA circumferential SR [−0.87 ± 0.1, −1.91 ± 0.03, −1.21 ± 0.12, −0.97 ± 0.05/s]; all p-values < 0.05. Logistic binary regression found left ventricular strain and DTA rotational displacement on 5 cmH₂O PEEP level were associated with death. Conclusions: Changes in PEEP levels affect the speckle tracking measurements of the DTA. Speckle tracking can be used to assess the thoracic aorta, and certain parameters, such as rotational displacement, may relate to the prognosis of cardiogenic shock. Full article

Background: Anthracycline-based chemotherapy is associated with a risk of cancer therapy-related cardiac dysfunction (CTRCD), particularly in patients with moderate to high cardiovascular risk. Left ventricular global longitudinal strain (GLS) is a sensitive marker for early myocardial dysfunction, but the prognostic value of baseline GLS in this population remains unclear. Objective: We aimed to evaluate whether baseline GLS can predict CTRCD in moderate- to high-risk cancer patients undergoing anthracycline chemotherapy. Methods: In this prospective, single-center observational study, 80 anthracycline-naive cancer patients classified as moderate or high risk were enrolled. Baseline GLS was assessed via speckle-tracking echocardiography, with a threshold of ≥−18% considered decreased. Patients were followed for 12 months, and the primary endpoint was the development of CTRCD per ESC 2022 Cardio-oncology guidelines. Results: Of the 77 patients completing follow-up, 27.3% had decreased baseline GLS. CTRCD occurred in 62.4% of patients, with higher incidence among those with decreased GLS (76.7%) compared to those with normal GLS. In multivariable analysis, GLS ≥−18% was the only significant independent predictor of CTRCD (RR 12.0, 95% CI 2.0–71.9; p = 0.0065). All-cause mortality was also significantly higher in patients with decreased baseline GLS (19.1% vs. 1.8%, p = 0.018). Conclusions: Decreased baseline global longitudinal strain is an independent predictor of cancer therapy-related cardiac dysfunction and all-cause mortality in moderate- to high-risk patients receiving anthracycline therapy. These findings support the inclusion of baseline GLS in pre-treatment cardiovascular risk assessment, particularly in patients with an LVEF above 54%, to more effectively identify those who may benefit from early cardioprotective interventions. Full article

Long bone fractures are breaks or cracks in a long bone of the body typically caused by trauma like a fall, sport injury, accidents etc. This study investigates the effectiveness of experimental methods for fast and safe healing of long bone fractures in humans, highlighting both their advantages and disadvantages, respectively finding the most effective and safe methods for evaluating the types of fixators that can be used in the consolidation of fractured long bones. As for the preliminary data, numerical methods and applied mathematics were used to address this problem. After collecting of preliminary data there were performed a series of experimental analysis as follows: Electrical Strain Gauges (ESGs); the Moiré Fringes method; Photo-Elasticity, with the particular technique thereof, the so-called Photo-Stress method; Holographic Interferometry (HI); Speckle Pattern Interferometry (ESPI) and Shearography; and Video Image Correlation (VIC), which is also called Digital Image Correlation (DIC). By analyzing different methods, the following two methods resulted to be widely applicable, namely, ESG and DIC/VIC. The findings highlight the net advantages regarding the objective choice of these types of fixators, thereby contributing to a possible extension of these approaches for the benefit of medical surgical practice Full article

The object detection model for synthetic aperture radar (SAR) images needs to have strong generalization ability and more stable detection performance due to the complex scattering mechanism, high sensitivity of the orientation angle, and susceptibility to speckle noise. Visual large models possess strong generalization capabilities for natural image processing, but their application to SAR imagery remains relatively rare. This paper attempts to introduce a visual large model into the SAR object detection task, aiming to alleviate the problems of weak cross-domain generalization and poor adaptability to few-shot samples caused by the characteristics of SAR images in existing models. The proposed model comprises an image encoder, an attention module, and a detection decoder. The image encoder leverages the pre-trained Segment Anything Model (SAM) for effective feature extraction from SAR images. An Adaptive Channel Interactive Attention (ACIA) module is introduced to suppress SAR speckle noise. Further, a Dynamic Tandem Attention (DTA) mechanism is proposed in the decoder to integrate scale perception, spatial focusing, and task adaptation, while decoupling classification from detection for improved accuracy. Leveraging the strong representational and few-shot adaptation capabilities of large pre-trained models, this study evaluates their cross-domain and few-shot detection performance on SAR imagery. For cross-domain detection, the model was trained on AIR-SARShip-1.0 and tested on SSDD, achieving an mAP50 of 0.54. For few-shot detection on SAR-AIRcraft-1.0, using only 10% of the training samples, the model reached an mAP50 of 0.503. Full article

Background: Anthracycline-based chemotherapy, while highly effective for breast cancer, poses a significant risk for chemotherapy-related cardiac dysfunction (CTRCD), mainly determined by left ventricular ejection fraction (LVEF) reduction. Objectives: We aimed to evaluate the diagnostic utility of speckle tracking analysis (STA) and Diastolic Stress Test Echocardiography (DSTE) for the early detection of cardiac dysfunction either CTRCD or heart failure with preserved ejection fraction (HFpEF) in women undergoing chemotherapy for breast cancer and developed exertional dyspnea and/or fatigue during follow-up. Methods: In this prospective case–control study, 133 women receiving anthracycline-based chemotherapy (with or without anti-HER2 therapy) (chemotherapy group-CTG) and 65 age-matched healthy women as the control group (CG) underwent resting echocardiographic assessment, including LVEF, global longitudinal strain (GLS), myocardial work indices, biomarkers assay (NT-proBNP, troponin, galectin-3) and DSTE at baseline. That assessment was repeated after 12 months in CTG. Results: In this prospective case—control study, 133 women receiving anthracycline-based chemotherapy (with or without anti-HER2 therapy) were included. Based on the presence of CTRCD, they were further subdivided into a CTRCD subgroup (n = 37) and a CTRCD-free subgroup (n = 88). At the end of this study, CTG showed worse values of LVEF, GLS, myocardial work indices than baseline and CG (p < 0.05). Subgroup comparison (CTRCD vs. CTRCD-free) showed significant impairment in LVEF (53.60% vs. 62.60%, p < 0.001), GLS (–16.68% vs. −20.31%, p < 0.001), DSTE-derived tricuspid regurgitation maximum velocity (TRVmax) (3.05 vs. 2.31 m/s, p < 0.001) and elevated biomarkers (NT-proBNP: 200.06 vs. 61.49 pg/mL; troponin: 12.42 vs. 3.95 ng/L, p < 0.001) in the former subgroup. Regression analysis identified GLS, NT-proBNP, troponin, and TRVmax as independent predictors of CTRCD. Notably, a subgroup of CTRCD-free patients (n = 16) showed a high probability for HFpEF based on the HFA-PEFF score, with elevated GLS, NT-proBNP and DSTE-derived TRVmax compared to the rest of CTRCD-free patients and the CG (p < 0.001). Conclusions: STA and DSTE significantly outperform conventional LVEF in detecting subclinical cardiac dysfunction among women with breast cancer receiving chemotherapy. The combination of novel echocardiographic techniques and biomarkers may enable the detection of early CTRCD, including the under-estimated presence of HFpEF among breast cancer women with HF symptoms. Full article

The laser speckle technique provides a non-invasive remote sensing method for monitoring biological dynamics. In this study, we focus on assessing microbial growth through systematic comparison of correlation-based speckle image analysis methods. We compare conventional techniques, NCC, ZNCC, the Lewis method, and Phase correlation, with two newly proposed variants: frequency-domain correlation of normalized images and ZNCC with limited shifts around the peak. We analyze these methods in terms of precision and computational efficiency. Our results demonstrate that the proposed techniques offer optimal trade-offs for tracking subtle microbial activity, particularly in early-stage growth. This paper aims not only to identify the most effective tools for laser speckle analysis, but also to justify the use of laser speckle imaging for microbial activity assessment. Full article

To elucidate the multi-performance evolution mechanisms of basalt fiber-reinforced lightweight expanded polystyrene geopolymer concrete (LEGC), a two-tiered investigation was conducted. In the first part, a series of LEGC mixtures with varying volume fractions of EPS (10–40%) and basalt fiber (BF) (0.4–0.8%) were designed. Experimental tests were carried out to evaluate density, flowability, compressive strength, flexural strength, and splitting tensile strength. Crack propagation behavior was monitored using DIC-3D speckle imaging. Additionally, X-ray CT scanning revealed the internal clustering of EPS particles, porosity distribution, and crack connectivity within LEGC specimens, while SEM analysis confirmed the bridging effect of basalt fibers and the presence of dense matrix regions. These microstructural observations verified the consistency between the synergistic effects of EPS weakening and fiber reinforcement at the microscale and the macroscopic failure behavior. The results indicated that increasing EPS content led to reduced mechanical strength, whereas the reinforcing effect of basalt fiber followed a rising-then-falling trend. Among all specimens, LEGC20BF06 exhibited the best comprehensive performance, achieving a compressive strength of 40.87 MPa and a density of 1747.6 kg/m³, thus meeting the criteria for structural lightweight concrete. In the second part, based on the experimental data, predictive models were developed for splitting tensile and flexural strengths using compressive strength as a reference, as well as a dual-factor model incorporating EPS and fiber contents. Both models were validated and demonstrated high predictive accuracy. Furthermore, a splitting tensile elasto-plastic damage constitutive model was proposed based on composite mechanics and energy dissipation theory. The model showed excellent agreement with experimental stress–strain curves, with all fitting coefficients of determination (R²) exceeding 0.95. These findings offer robust theoretical support for the performance optimization of LEGC and its application in green construction and prefabricated structural systems. Full article

Bamboo cracking is primarily attributed to the influence of moisture on its structure. Natural-speckle digital image correlation (DIC) was employed to characterize tangential shrinkage in cross-sections, using parenchyma cells as intrinsic speckle patterns. Shrinkage behavior during the 24 h drying process at a temperature of 103 °C across the external, middle, and internal layers was comparatively analyzed in bamboo nodal regions (NR), internodal regions (IR), and transitional zones (TZ, i.e., node–internode interfaces). Moisture had the most pronounced effect on NR, which consistently exhibited the highest moisture content and shrinkage ratios during the drying process. Notably, the drying shrinkage of the external layer was significantly greater than that of other layers. Specifically, the drying shrinkage strain ratio of the external layer of NR is 3.02 times higher than that of the internal layer, while for IR, it is 3.60 times higher. Furthermore, the external layer of NR exhibits substantial deformation during the initial stages of drying, with a drying shrinkage strain ratio of 5.96% for 2 h. The results demonstrated that shrinkage deformation in bamboo nodes was significantly greater than in other regions, offering valuable insights for developing strategies to mitigate bamboo cracking. Full article

Digital holography enables the reconstruction of both 2D and 3D object information from interference patterns captured by digital cameras. A major challenge in this field is speckle noise, which significantly degrades the quality of the reconstructed images. We propose a novel speckle noise reduction method based on 3D adaptive filtering. Our technique processes a stack of holograms, each with an uncorrelated speckle pattern, using an adapted 3D Frost filter. Unlike conventional filtering techniques, our approach exploits statistical adaptivity to enhance noise suppression while preserving fine image details in the reconstructed holograms. Both numerical simulations and optical experiments confirm that our 3D filtering technique significantly enhances reconstruction quality. Specifically, it reduces the normalized standard deviation by up to 40% and improves the structural similarity index by up to 60% compared to classical 2D, 3D median, BM3D, and BM4D filters. Optical experiments validate the method’s effectiveness in practical digital holography scenarios by local and global image quality estimation metrics. These results highlight adaptive 3D filtering as a promising approach for mitigating speckle noise while maintaining structural integrity in digital holography reconstructions. Full article

Detecting ships in Synthetic Aperture Radar (SAR) images poses a complex challenge, with recent progress primarily attributed to the development of rotated detectors. However, existing methods often neglect the crucial influence of inherent characteristics in SAR images, such as common speckle noise. Moreover, a notable gap exists in modeling diverse features, particularly the fusion of rotational and high-frequency features. To address these challenges, this paper introduces a high-accuracy detector called PRDet, which builds on two key innovations: partial differential equation (PDE)-Guided Wavelet Transform (PGWT) and Diverse Feature Learning Block (DFLB). The PGWT enhances high-frequency features, such as edges and textures, while eliminating speckle noise by optimizing wavelet transform with PDE, leveraging the ability of PDE to model local variations and preserve structural details. The DFLB, with strong expressive capability, extracts and fuses multi-form ship features through three branches, enabling more accurate ship localization. Extensive experimental evaluations on the publicly available RSSDD and SRSDD-V1.0 benchmarks demonstrate PRDet’s superiority over other SAR rotated ship detectors. For example, on the RSSDD dataset, PRDet achieves an offshore precision of 0.938 and an mAP of 0.908, confirming its effectiveness for practical maritime surveillance applications. Full article

Speckle noise inherent in Synthetic Aperture Radar (SAR) images severely degrades image quality and hinders downstream tasks such as interpretation and target recognition. Existing despeckling methods, both traditional and deep learning-based, often struggle to balance effective speckle suppression with structural detail preservation. Although Denoising Diffusion Probabilistic Models (DDPMs) have shown remarkable potential for SAR despeckling, their computational overhead from iterative sampling severely limits practical applicability. To mitigate these challenges, this paper proposes the Efficient Conditional Diffusion Model (ECDM) for SAR despeckling. We integrate the cosine noise schedule with a joint variance prediction mechanism, accelerating the inference speed by an order of magnitude while maintaining high denoising quality. Furthermore, we integrate wavelet transforms into the encoder’s downsampling path, enabling adaptive feature fusion across frequency bands to enhance structural fidelity. Experimental results demonstrate that, compared to a baseline diffusion model, our proposed method achieves an approximately 20-fold acceleration in inference and obtains significant improvements in key objective metrics. This work contributes to real-time processing of diffusion models for SAR image enhancement, supporting practical deployment by mitigating prolonged inference in traditional diffusion models through efficient stochastic sampling. Full article

Background/objectives: Optic nerve bending and chiasmal compression impair vision in patients with sellar lesions; however, their effect on optic nerve head (ONH) blood flow remains unclear. This study used laser speckle flowgraphy to examine the relationship between clinical features and ONH blood flow in patients with optic nerve bending and chiasmal compression. Methods: This retrospective study included 32 eyes (16 eyes with and 16 without optic nerve bending on the contralateral side) from 16 patients with sellar lesions. The best-corrected visual acuity (BCVA), simple visual field impairment score (SVFIS), optic nerve head mean blur rate (ONH-MBR), and six-segmented macular ganglion cell layer + inner plexiform layer (GCL + IPL) thickness were examined. Results: Preoperative BCVA and SVFIS in eyes with optic nerve bending were significantly worse than those in eyes without bending, and significantly correlated with the optic nerve-canal bending angle (ONCBA). After tumor resection, BCVA and SVFIS significantly improved in both groups. Preoperative ONH-MBR was significantly lower in bending eyes but increased significantly post-treatment in both groups. Preoperative ONH-MBR correlated with ONCBA, while postoperative ONH-MBR correlated with nasal GCL + IPL thickness. Conclusions: Optic nerve bending and chiasmal compression showed reduced blood flow to the ONH. These changes in blood flow may be associated with GCL + IPL thickness and optic nerve bending angle. Full article