Search Results (553)

Background/Objectives: Atypical femoral fracture (AFF) represents a diagnostic and therapeutic challenge, particularly in autoimmune disease patients receiving long-term bisphosphonate (BP) and glucocorticoid (GC) therapy. Although bilateral AFF is common, the radiographic evolution of asymptomatic incomplete lesions identified at the time of a complete fracture remains insufficiently defined. This study aimed to characterize the natural history and imaging biomarkers associated with progression in this biologically homogeneous high-risk population. Methods: Ten female autoimmune disease patients with complete AFF and asymptomatic incomplete contralateral lesions were retrospectively evaluated over a mean 59 months. Serial radiographs were assessed for cortical beaking, periosteal flaring, and transverse radiolucent lines. All patients discontinued BP therapy postoperatively; teriparatide was administered when tolerated. Results: Six lesions regressed, three remained stable, and one progressed—this progressing case being the only limb with a transverse radiolucent line at baseline. No patient developed symptoms or sustained a complete fracture on the contralateral side. Radiographic remodeling occurred independently of symptoms. BP discontinuation and, when tolerated, teriparatide appeared to contribute to lesion stabilization, although statistical significance was not achieved. Conclusions: In autoimmune patients with severe long-term BP and GC exposure, most asymptomatic incomplete AFF identified at the time of contralateral complete fracture remains stable or improves under conservative management. A transverse radiolucent line is the most decisive imaging biomarker predictive of progression and warrants intensified surveillance or consideration of prophylactic fixation. Larger cohorts are needed to refine risk stratification algorithms and optimize diagnostic and management strategies. Full article

Micro-motors are widely used in industrial applications, which require effective fault diagnosis to maintain safe equipment operation. However, fault signals from micro-motors often exhibit weak signal strength and ambiguous features. To address these challenges, this study proposes a novel fault diagnosis method. Initially, the Jump plus AM-FM Mode Decomposition (JMD) technique was utilized to decompose the measured signals into amplitude-modulated–frequency-modulated (AM-FM) oscillation components and discontinuous (jump) components. The proposed process extracts valuable fault features and integrates them into a new time-domain signal, while also suppressing modal aliasing. Subsequently, a novel Global Relationship Matrix (GRM) is employed to transform one-dimensional signals into two-dimensional images, thereby enhancing the representation of fault features. These images are then input into an Optimized Convolutional Neural Network (OCNN) with an AdamW optimizer, which effectively reduces overfitting during training. Experimental results demonstrate that the proposed method achieves an average diagnostic accuracy rate of 99.0476% for multiple fault types, outperforming four comparative methods. This approach offers a reliable solution for quality inspection of micro-motors in a manufacturing environment. Full article

Information on crop planting structure serves as a key reference for crop growth monitoring and agricultural structural adjustment. Mapping the spatial distribution of crops through feature-based classification serves as a fundamental component of sustainable agricultural development. However, current crop classification methods often face challenges such as the discontinuity of optical data due to cloud cover and the limited discriminative capability of traditional SAR backscatter intensity for spectrally similar crops. In this case study, we assess multi-temporal Sentinel-1 and Sentinel-2 Satellite images for crop classification in a paddy rice growing region in Helonghu Town, located in the central region of Xiangyin County, Yueyang City, Hunan Province, China (28.5° N–29.0° N, 112.8° E–113.2° E). We systematically investigate three key aspects: (1) the classification performance using optical time-series Sentinel-2 imagery; (2) the time-series classification performance utilizing polarimetric SAR decomposition features from Sentinel-1 dual-polarimetric SAR images; and (3) the classification performance based on a combination of Sentinel-1 and Sentinel-2 images. Optimal classification results, with the highest overall accuracy and Kappa coefficient, are achieved through the combination of Sentinel-1 (SAR) and Sentinel-2 (optical) data. This case study evaluates the time-series classification performance of Sentinel-1 and Sentinel-2 data to determine the optimal approach for crop classification in Helonghu Town. Full article

Within natural rock masses, discontinuous joints are more prevalent than continuous joints. Discontinuous joints refer to non-persistent structural planes separated by intact rock bridges and can be quantified by the continuity coefficient K_A. They significantly affect the macroscopic mechanical properties of rock masses. Therefore, investigating discontinuous jointed rock masses with diverse morphologies carries considerable theoretical and engineering significance. Using 3D printing technology, resin-based specimens with discontinuous joints were subjected to laboratory mechanical tests to explore the evolution of failure mechanisms and mechanical properties of discontinuous jointed rock masses with different inclinations, undulation amplitudes, and structural plane continuity. Results show that under compression, discontinuous jointed rock masses consistently undergo combined tensile and shear stresses, with joint undulation amplitude and continuity governing coplanar crack initiation. As the joint inclination angle ranges from 0° to 90°, the peak compressive strength first decreases and then increases: specimens with continuous joints or discontinuous joints (continuity coefficient K_A < 0.25) follow a “V”-shaped trend, while those with K_A > 0.25 exhibit a “U”-shaped trend. Joint continuity is a key factor governing rock mass strength: at the same rock column radius, higher continuity results in lower strength, and vice versa. Joint morphology also influences strength, with specimens with regular zigzag joints and rectangular corrugated joints exhibiting 6.7% and 11.2% higher strength than smooth-jointed specimens, respectively. These results clarify the effects of joint continuity and undulation on rock mass strength, providing a theoretical foundation for the rapid determination of K_A via borehole imaging and laser scanning in engineering practice, and enabling direct prediction of rock mass strength trends. Full article

Background: Non-absorbable polyvinyl alcohol sponges (Merocel) are widely used in otolaryngology for nasal and ear packing but are prone to bacterial colonization and biofilm formation, which may increase infection risk and drive frequent use of systemic antibiotics. Sustained-release drug delivery systems enable prolonged local antiseptic activity at the site of packing while minimizing systemic exposure. Methods: We developed a sustained-release varnish containing chlorhexidine (SRV-CHX) and coated sterile Merocel sponges. Antibacterial, in vitro, activity against Staphylococcus aureus and Pseudomonas aeruginosa was evaluated using kinetic diffusion assays on agar, optical density (OD₆₀₀) measurements of planktonic cultures, drop plate, ATP-based viability assays, biofilm analysis by MTT metabolic assay, crystal violet bio-mass staining, high-resolution scanning electron microscopy (HR-SEM), and spinning disk confocal microscopy. Results: SRV-CHX-coated sponges produced sustained zones of inhibition on agar plates for up to 37 days against S. aureus and 39 days against P. aeruginosa, far exceeding the usual 3–5 days of clinical sponge use. Planktonic growth was significantly reduced compared with SRV-placebo, and a bactericidal effect persisted for up to 16 days for S. aureus and 5 days for P. aeruginosa before becoming predominantly bacteriostatic. Biofilm formation was markedly inhibited, with suppression of metabolic activity and biomass for at least 33 days for S. aureus and up to 16 days for P. aeruginosa. HR-SEM and confocal imaging confirmed sparse, discontinuous biofilms and predominance of non-viable bacteria on SRV-CHX-coated sponges compared with dense, viable biofilms on the placebo controls. Conclusions: Coating Merocel sponges with SRV-CHX provides prolonged antibacterial and anti-biofilm activity against clinically relevant pathogens. This strategy may reduce dependence on systemic antibiotics and improve infection control in nasal and ear packing applications in otolaryngology. Full article

Background: Tumor necrosis factor-α (TNFα) inhibitors have significantly improved outcomes in children with non-systemic juvenile idiopathic arthritis (JIA), achieving long-term clinical remission for many patients. However, the optimal strategy for TNF-α inhibitor withdrawal remains unknown, whether through abrupt discontinuation, gradual dose reduction, or interval extension. Objective: We aim to identify patient-, disease-, and treatment-related predictors of successful TNF-α inhibitor withdrawal in children with non-systemic JIA. Methods: In this prospective, randomized, open-label, single-center study, 76 children with non-systemic JIA in stable remission for ≥24 months on etanercept or adalimumab were enrolled. At the time of TNF-α inhibitor discontinuation, all patients underwent a comprehensive evaluation, including a clinical examination, laboratory tests (serum calprotectin [S100 proteins] and high-sensitivity C-reactive protein [hsCRP]), and advanced joint imaging (musculoskeletal ultrasound and magnetic resonance imaging [MRI]) to assess subclinical disease activity. Patients were randomized (1:1:1, sealed-envelope allocation) to one of three predefined tapering strategies: (I) abrupt discontinuation; (II) extension of dosing intervals (etanercept 0.8 mg/kg every 2 weeks; adalimumab 24 mg/m² every 4 weeks); or (III) gradual dose reduction (etanercept 0.4 mg/kg weekly; adalimumab 12 mg/m² every 2 weeks). Follow-up visits were scheduled at 3, 6, 9, 12, and 18 months to monitor for disease relapse. Results: Higher baseline Childhood Health Assessment Questionnaire (CHAQ) scores (≥2), elevated serum calprotectin [S100 proteins] and hsCRP levels at withdrawal, imaging evidence of subclinical synovitis, and a history of uveitis were all significantly associated with increased risk of flare. No significant associations were found for other clinical or demographic characteristics. Conclusions: Early significant clinical response, absence of subclinical disease activity, and concomitant low-dose methotrexate therapy were key predictors of sustained drug-free remission. These findings may inform personalized strategies for biologic tapering in pediatric JIA. Full article

High-precision and high-resolution surface deformation provide crucial constraints for studying the kinematic characteristics and dynamic mechanisms of crustal movement. Considering the limitations of existing geodetic observations, we used Sentinel-1 SAR images and accurate GNSS velocity to obtain a high-resolution three-dimensional (3D) surface velocity map across the Laohushan segment and the 1920 Haiyuan earthquake rupture zone of the Haiyuan Fault on the northeastern Tibetan Plateau. We tied the InSAR LOS (Line of Sight) velocity to the stable Eurasian reference frame adopted by GNSS. Using Kriging interpolation constrained by GNSS north–south components, we decomposed the ascending and descending InSAR velocities into east–west and vertical components to derive a high-resolution 3D deformation. We found that a sharp velocity gradient extending ~45 km along the strike of the Laohushan segment, with a differential movement of ~3 mm/a across the fault, manifests in the east–west velocity component, suggesting that shallow creep has propagated to the surface. However, the east–west velocity component did not exhibit an abrupt discontinuity in the rupture zone of the Haiyuan earthquake. Subsidence caused by anthropogenic and hydrological processes in the region, such as groundwater extraction, coal mining, and hydrologic effects, exhibited distinct distribution characteristics in the vertical velocity component. Our study provides valuable insights into the crustal movement in this region. Full article

Background: Durvalumab, a PD-L1 inhibitor used as consolidation therapy after chemoradiation in unresectable stage III non–small cell lung cancer (NSCLC), can induce immune-related adverse events, among which immune-mediated pneumonitis represents one of the most severe. Differentiating checkpoint inhibitor pneumonitis (CIP) from infectious pneumonia is challenging due to overlapping clinical and radiologic findings. Case presentation: We describe a 67-year-old woman with stage III lung adenocarcinoma treated with chemotherapy, radiotherapy, and durvalumab, who presented with progressive dyspnea and extensive bilateral ground-glass opacities on CT imaging. Laboratory tests revealed leukopenia and elevated inflammatory markers. Despite broad-spectrum antibiotic and antiviral therapy, her condition worsened, requiring high-flow nasal cannula oxygen therapy. Multiplex molecular testing on sputum identified human metapneumovirus (HMPV), while blood cultures and urinary antigens for Streptococcus pneumoniae and Legionella pneumophila were negative. A pulmonology consultation raised suspicion for severe durvalumab-induced pneumonitis exacerbated by viral infection. High-dose methylprednisolone (2 mg/kg/day) followed by a four-week taper led to gradual clinical and radiologic resolution. Durvalumab was permanently discontinued. Discussion: To our knowledge, this is the first reported case of HMPV-associated pneumonitis in a patient receiving durvalumab. This case highlights the potential synergistic interplay between viral infection and immune checkpoint blockade, resulting in severe lung injury. Comprehensive microbiologic evaluation, including molecular diagnostics, is essential to guide therapy and distinguish infectious from immune-mediated causes. Conclusions: Early recognition of mixed infectious and immune-mediated pneumonitis, and timely corticosteroid therapy are critical to achieving favorable outcomes and preventing irreversible pulmonary damage. Full article

This paper discusses the evolution of convolutional (CNN) and recurrent (RNN) artificial neural networks in applications for Building Information Modeling (BIM). The paper outlines the milestones reached in the last two decades. The article organizes the current state of knowledge and technology in terms of three aspects: (1) computer visualization coupled with BIM models (detection, segmentation, and quality verification in images, videos, and point clouds), (2) sequence and time series modeling (prediction of costs, energy, work progress, risk), and (3) integration of deep learning results with the semantics and topology of Industry Foundation Class (IFC) models. The paper identifies the most used architectures, typical data pipelines (synthetic data from BIM models, transfer learning, mapping results to IFC elements) and practical limitations: lack of standardized benchmarks, high annotation costs, a domain gap between synthetic and real data, and discontinuous interoperability. We indicate directions for development: combining CNN/RNN with graph models and transformers for wider use of synthetic data and semi-/supervised learning, as well as explainability methods that increase trust in AECOO (Architecture, Engineering, Construction, Owners & Operators) processes. A practical case study presents a new application, Bimetria, which uses a hybrid CNN/OCR (Optical Character Recognition) solution to generate 3D models with estimates based on two-dimensional drawings. A deep review shows that although the importance of attention-based and graph-based architectures is growing, CNNs and RNNs remain an important part of the BIM process, especially in engineering tasks, where, in our experience and in the Bimetria case study, mature convolutional architectures offer a good balance between accuracy, stability and low latency. The paper also raises some fundamental questions to which we are still seeking answers. Thus, the article not only presents the innovative new Bimetria tool but also aims to stimulate discussion about the dynamic development of AI (Artificial Intelligence) in BIM. Full article

Since skeletal development is largely completed by adulthood, it is difficult for traditional methods to capture subtle age-related structural changes in bones and surrounding tissues. Recent advances in deep learning have demonstrated remarkable potential in medical image-based age estimation. The cervical vertebrae, as captured in lateral cephalometric radiographs (LCR), have shown particular value in such tasks. To systematically investigate the contribution of different vertebral representations to age estimation, we developed four distinct input modes: (1) Contour (C); (2) Mask (M); (3) Cervical Vertebrae (CV) and (4) Cervical vertebrae region (SR). Using a large-scale LCR dataset of 20,174 subjects aged 4–40 years, grouped into 5-year intervals, we evaluated these modes with deep learning models. The Mean Absolute Error (MAE) was used to evaluate performance. Results indicated that the SR mode achieved the lowest overall MAE, particularly for the C1–C4 combination, followed by CV, while C and M modes showed similar and poorer performance. For subjects younger than 25 years, MAEs for individual vertebrae (C1–2, C3, C4) were less than 5 years across all modes; however, in the 26–40 years group, MAEs for C and M modes exceeded 10 years, whereas CV and SR modes remained below 10 years for most combinations. Combining vertebrae consistently improved accuracy over individual ones, with continuous combinations (e.g., C1–2 + C3) outperforming discontinuous ones (e.g., C1–2 + C4). Visualization of age-related salience revealed that salient regions varied by input mode and expanded with increased information content. These findings underscore the critical importance of incorporating peripheral soft tissue and comprehensive vertebral context for accurate age estimation across a wide age spectrum. Full article

Fused Deposition Modeling (FDM) is an extensively employed additive manufacturing method for producing precise and complicated polymer models, with its industrial applications expanding under various loading conditions. A review of existing research highlights the insufficient investigation of the influence of geometric discontinuities in additively manufactured polylactic acid (PLA) members under fatigue loads. This study aims to analyze the combined effects of build orientation and geometric discontinuities on the static and fatigue performance and damage evolution of 3D-printed PLA. To achieve improved fabrication quality and minimize process-induced defects, the quasi-static tensile tests were conducted on specimens printed in on-edge orientation with a concentric infill pattern and the flat direction with a rectilinear infill pattern. The test results have shown that on-edge-printed objects have reduced micro-voids and improved layer bonding, resulting in a 19% increase in tensile strength compared to the flat-printed specimens. Consequently, this configuration was adopted for three specimen types, e.g., smooth, semi-circular edge-notched, and central-holed, tested under axial fatigue with a 0.05 load ratio. Fatigue test findings indicate that the stress concentration is more pronounced around central holes than near edge notches, leading to shorter fatigue life. This phenomenon is consistent with its effects under static tensile loading. Furthermore, using Digital Image Correlation (DIC) technique, damage initiation, progression, and failure mechanisms were analyzed in detail. According to fractographic analysis, the micro-voids in the 3D-printed specimens serve as potential regions for the initiation of multiple fatigue cracks. Additionally, the inherent internal defects can interact with geometric discontinuities, thereby weakening the fatigue performance. Full article

Urban UAV imagery presents challenges for reliable feature matching owing to complex 3D structures and depth discontinuities. Conventional 2D-based outlier rejection methods often fail to maintain geometric consistency under significant altitude variations or viewpoint differences, resulting in the rejection of valid correspondences. To overcome these limitations, a depth-guided local outlier rejection methodology is proposed which integrates monocular depth estimation, DBSCAN-based clustering, and local geometric model estimation. Depth information estimated from single UAV images is combined with feature correspondences to form pseudo-3D coordinates, enabling spatially localized registration. The proposed method was quantitatively evaluated in terms of Precision, Recall, F1-score, and Number of Matches, and was applied as a depth-guided front-end to three representative 2D-based outlier rejection schemes (RANSAC, LMedS, and MAGSAC++). Across all image sets, the depth-guided variants consistently achieved higher Recall and F1-score than their conventional 2D counterparts, while maintaining comparable Precision and keeping mismatches low. These results indicate that introducing depth-guided pseudo-3D constraints into the outlier rejection stage enhances geometric stability and correspondence reliability in complex urban UAV imagery. Accordingly, the proposed methodology provides a practical and scalable solution for accurate registration in depth-varying urban environments. Full article

Geometric inaccuracies in the design of X-ray baggage scanners can lead to significant image artifacts, such as banding and discontinuities, which compromise security screening effectiveness. Although comprehensive commercial solutions are available, constructing a custom X-ray scanner requires the precise alignment of detector arrays. This is a complex and time-consuming process when performed manually. The core of the proposed method is a computational model that calculates the optimal position and orientation for each detector card based on user-defined scanner dimensions and hardware parameters. To validate the geometry created with this method, its performance was compared against flat and arc-shaped geometries. The results demonstrate that the proposed method successfully generates geometries that produce continuous and artifact-free images. The study concludes that the developed software tool provides a robust and practical solution, significantly simplifying the complex task of scanner construction and accelerating the development of reliable, custom X-ray inspection systems. Full article

Indocyanine green (ICG) is widely used in minimally invasive surgery for real-time fluorescence imaging of vascular, biliary, and urological structures. Although its intravenous use has been extensively validated, data on intraureteral administration remain scarce, particularly regarding renal safety. We report the case of a 50-year-old woman undergoing laparoscopic bilateral endometrioma excision with intraureteral ICG instillation for ureteral visualisation. Despite an uneventful surgery, the patient developed anuria and acute kidney injury (AKI) within 24 h, requiring temporary hemodialysis. Imaging demonstrated bilateral renal dysfunction without evidence of ureteral transection. Renal function gradually improved with supportive care, and dialysis was discontinued. This is, to our knowledge, the first reported case of AKI following intraureteral ICG use. Potential mechanisms include dye-induced tubular toxicity, ischemic injury, and multifactorial perioperative stressors. Given the increasing adoption of near-infrared fluorescence in gynecologic and urologic surgery, our case highlights the urgent need for systematic studies on the renal safety of intraureteral ICG administration. Until further evidence emerges, surgeons should use the technique with caution, particularly in patients with preexisting risk factors for AKI. Full article

Advanced driver-assistance and autonomous systems require perception that is both robust and affordable. Monocular cameras are promising due to their ubiquity and low cost, yet detecting abrupt road surface irregularities such as curbs and bumps remains challenging. These sudden road gradient changes are often only a few centimeters high, making them difficult to detect and resolve from a single moving camera. We hypothesize that stable image-based homography, derived from robust geometric correspondences, is a viable method for predicting sudden road surface gradient changes. To this end, we propose a monocular, geometry-driven pipeline that combines transformer-based feature matching, homography decomposition, temporal filtering, and late-stage IMU fusion. In addition, we introduce a dedicated dataset with synchronized camera and ground-truth measurements for reproducible evaluation under diverse urban conditions. We conduct a targeted feasibility study on six scenarios specifically recorded for small, safety-relevant discontinuities (four curb approaches, two speed bumps). Homography-based cues provide reliable early signatures for curbs (3/4 curb sequences detected at a 5 cm threshold). These results establish feasibility for monocular, geometric curb detection and motivate larger-scale validation. The code and the collected data will be made publicly available. Full article