Search Results (2,332)

This paper presents a feature-level defective pixel cluster (DPC) correction method specifically designed for dual-band infrared detectors. Due to inherent manufacturing limitations, antimonide-based type-II superlattice (T2SL) focal plane arrays (FPAs) commonly suffer from DPC issues. Existing DPC correction methods often fail to preserve dual-band imaging characteristics, leading to texture distortion and incomplete structure recovery. Inspired by infrared imaging mechanisms and image inpainting theory, we propose PRISM, a patch-based reconstruction framework that leverages inter-band structure migration with hierarchical feature decomposition, decoupling dual-band images into micro-textures, edge gradients, and spatial relationships. Leveraging this multi-level feature representation, we extract prior information to guide DPC correction. The correction process is formulated as a “structure-to-pixel” optimization problem, where an improved feature-guided patch search strategy effectively combines structure completion with texture reconstruction. Experimental results demonstrate that the proposed method not only recovers image content effectively but also faithfully preserves band-specific imaging characteristics. Furthermore, to facilitate quantitative evaluation, we construct a benchmark dataset containing simulated DPCs with corresponding ground truth. Comparative experiments on both our self-constructed dataset and public multimodal benchmarks confirm that PRISM achieves higher PSNR, SSIM, VIF, and CC metrics than state-of-the-art multimodal inpainting methods. Full article

Software-Defined Networking (SDN) provides fine-grained control over network architectures, yet integrating intrusion detection systems (IDSs) into the control plane frequently introduces prohibitive computational overhead. This issue is compounded by the fact that existing machine learning models, typically trained on static benchmark datasets, often degrade under real-time polling conditions and unpredictable traffic bursts. To bridge this gap, this paper evaluates an ultra-compact five-feature polling scheme (F1–F5) designed to preserve statistical symmetry between control-plane monitoring and telemetry overhead within a dynamic Mininet–Ryu testbed. The experimental framework incorporates 15% background noise, and a 10% stealth attack overlaps across a 120 s dynamic trace. Four distinct classifiers—Random Forest (RF), Decision Tree (DT), Multi-Layer Perceptron (MLP), and Long Short-Term Memory (LSTM)—were evaluated across frame-by-frame snapshot and windowed prediction tasks. Empirical findings reveal that tree-based ensembles consistently outperform deep learning approaches, with RF attaining an overall accuracy of 97.57% and DT achieving 96.74%, compared to 90.77% for MLP and 90.73% for LSTM. Analysis of the time-series logs demonstrates that RF’s orthogonal decision boundaries successfully isolate transient, high-intensity threats such as WebAttack and PortScan vectors without needing memory-intensive recurrent architectures. Ultimately, pairing minimal feature extraction with lightweight tree ensembles offers an optimal balance between low control-plane latency and high detection efficacy. Full article

Flow distortion generated by L-shaped elbows in plant-protection spraying equipment disturbs the inlet flow of flat-fan nozzles, causing non-uniform outlet velocity distributions and reduced foliar deposition uniformity. This study developed a flat-fan nozzle with built-in flow-straightening vanes to improve spray stability under complex pipeline conditions. A three-dimensional CFD model integrating an L-shaped elbow, nozzle, and external spray region was established, and the Volume of Fluid (VOF) model was used to examine the effects of flow-dividing channel number, vane geometry, and vane insertion depth on velocity distribution on the spray fan plane. Structural parameters were optimized using a Box–Behnken response surface design. Field experiments on soybean seedlings evaluated droplet deposition using a carmine tracer assay with microplate reader measurement. The built-in vanes reduced elbow-induced flow deflection, swirl, and localized high-velocity zones, thereby improving spray fan velocity uniformity. The influence on the coefficient of variation of normal velocity followed the order: vane geometry > insertion depth > channel number. The optimal configuration comprised four channels, a star-shaped vane, and a 10 mm insertion depth, yielding a normal-velocity coefficient of variation of 16.12% at 400 mm downstream of the nozzle. Field trials showed that the developed nozzle reduced droplet deposition CV from 4.46% to 2.03% compared with the conventional flat-fan nozzle, a 54.5% decrease, with a significant difference between nozzles (p = 0.006). These results indicate that built-in flow-straightening vanes can improve spray stability and foliar deposition uniformity under elbow-induced flow distortion. Full article

Two client-owned Lionhead rabbits underwent median sternotomy for mediastinal mass excision. Premedication included methadone, dexmedetomidine, and midazolam, with ketamine added for one rabbit. Anesthesia was maintained with isoflurane in oxygen and a ketamine infusion. Bilateral ultrasound-guided TTP blocks were performed at the level of the second and fifth intercostal spaces using a linear transducer and a spinal needle advanced in-plane in a lateromedial direction. Bupivacaine 0.5% was injected at a total dose of 2 mg/kg per rabbit, divided equally among four injection sites (total volumes of 0.9 mL and 1.0 mL for the first and second rabbits, respectively). Only one rabbit exhibited a brief intraoperative nociceptive response. The second rabbit developed severe postoperative respiratory compromise related to inadequate thoracic drain function and died 4 h after surgery. These cases indicate that the TTP block is technically feasible in rabbits and can contribute to intraoperative analgesia during thoracic surgery. Further studies are needed to evaluate the optimal injectate volume and its distribution, as well as the safety and efficacy of the anesthetic dose. Full article

Urban Internet-of-Things (IoT) infrastructures increasingly host distributed artificial intelligence workloads across heterogeneous edge environments, supporting applications such as urban monitoring, resource optimization, and large-scale sensing analytics. Despite the rapid adoption of edge AI, current systems lack a unified architectural layer responsible for orchestrating distributed intelligence across dynamic urban infrastructures. Existing orchestration mechanisms are typically rule-based and rely on low-level telemetry signals such as latency, node availability, or network conditions, limiting their ability to interpret the contextual meaning of system behavior and environmental events. This paper introduces Urban AI OS, a trustworthy LLM-based semantic control layer for distributed urban edge intelligence. The proposed architecture transforms heterogeneous telemetry and environmental signals into high-level semantic events through large language model reasoning, enabling context-aware orchestration decisions including adaptive topology management, workload coordination, and node role assignment. To address the reliability risks associated with LLM-assisted control, Urban AI OS employs confidence-gated execution with deterministic fallback policies, post-action monitoring, rollback, and auditable decision logging to constrain the operational impact of uncertain or erroneous LLM recommendations. By decoupling semantic reasoning from the data plane execution of AI workloads, Urban AI OS provides a model-agnostic framework for managing large-scale urban edge intelligence infrastructures. Experimental evaluation on a real-world urban IoT deployment with 50+ edge devices demonstrates that the proposed semantic operating layer improves system responsiveness by 35%, reduces unnecessary topology changes by 42%, and improves communication efficiency compared to conventional rule-based and adaptive threshold baselines, while maintaining confidence calibration through formal fallback mechanisms. Full article

In this work, Cu₂CoSnS₄ (CCTS) thin films were deposited on glass substrates by thermal evaporation and investigated for photovoltaic applications. The influence of substrate temperature, varied from 25 °C to 200 °C, on the structural, morphological, and optical properties of the films was experimentally studied using X-ray diffraction (XRD), scanning electron microscopy (SEM), and photoluminescence (PL) measurements. XRD analysis confirmed the formation of crystalline CCTS with a stannite structure and a preferential orientation along the (112) plane. SEM observations revealed rough and non-uniform surfaces accompanied by an increase in grain size with increasing substrate temperature. Room-temperature PL measurements indicated a band-gap energy of approximately 1.3 eV, suitable for photovoltaic applications, and confirmed the presence of secondary phases in the p-type stannite CCTS films. Despite the promising photovoltaic properties of CCTS, numerical studies on CCTS-based solar cells remain scarce in the literature. In this context, a numerical study of the CCTS-based solar structure grown on glass was also performed using SCAPS-1D, showing good agreement with experimental photovoltaic results and validating the simulation model. Replacing the glass substrate with silicon improved the device efficiency to 5.77%. Further optimization of the series and shunt resistances significantly enhanced the photovoltaic performance, achieving a power conversion efficiency of 16.77%, with FF = 52.94%, V_oc = 0.89 V and J_sc = 35.19 mA/cm². Full article

To address the challenges of structural deformation and limited load-bearing capacity in morphing wings, this paper proposes a novel rigid–flexible composite morphing wing based on a foldable membrane–skeleton structure with a high folding ratio. Inspired by the deployment mechanics of biological wings and the cooperative support principle of multi-bar mechanisms, an optimization model was established to resolve hinge interference in the skeletal design. Through geometric reconstruction of the skeleton, the design achieves compact stowage in the folded state and maximizes wing area in the deployed configuration. Furthermore, an integrated design model for the membrane–skeleton interface was established based on rigid–flexible hybrid connection principles, followed by an analysis of the wing’s static structural characteristics via finite element simulation. A prototype was fabricated to experimentally validate its morphing functionality and out-of-plane load-bearing performance. Results demonstrate that the mechanism attains an effective folding ratio of approximately 7.19. Additionally, the influence of membrane prestress on the overall structural load capacity was systematically investigated. Full article

Natural fractures dominate fracturing effects and well production. Conventional fracturing fails to fully activate multi-scale fractures, and most simulations adopt homogeneous rock assumptions, lacking systematic analysis on fracture propagation and seepage evolution in heterogeneous fractured formations, while the natural fracture activation mechanism of pulsed fracturing remains unclear. This work constructs a pulsed fracturing model for heterogeneous fractured rock to simulate fracture growth and permeability evolution in intact rock and formations with various fracture attitudes, revealing the coupled laws of fracture propagation and seepage change. Results show rock mechanical heterogeneity determines fracture network complexity in intact rock; pulsed loading slows main fracture breakthrough and stimulates microcracks, creating a near-well dense and far-well sparse fracture distribution. Single-orientation fractures drive directional asymmetric fracture extension following near-weak-zone priority, with matrix heterogeneity merely causing local fracture deflection. Multi-orientation fractures display layered activation: low-angle and near-well fractures initiate first, and cross-fracture interactions raise network complexity and coverage. Fracture growth is jointly governed by weak bedding, pulse fatigue damage and matrix properties. Pulsed fracturing achieves remote non-contact activation of natural fractures, with fracture-permeability evolution showing strong spatiotemporal coupling; main fracture breakthrough triggers abrupt permeability growth. Serving as both mechanical weak planes and preferential flow paths, natural fractures build composite seepage systems of main channels and micro flow zones. This study provides theoretical support for parameter optimization and efficient permeability improvement in fractured reservoirs. Full article

Efficient small-scale hydrogen production via proton exchange membrane (PEM) electrolysis is a key pathway for advancing green hydrogen technologies. This study experimentally investigates a five-cell zero-gap PEM electrolyzer stack to evaluate energy losses, thermal behavior, and hydrogen generation efficiency. Faradaic efficiency increased with current density, reaching 98.03% at 0.232 A·cm⁻², while infrared (IR) thermography reveals non-uniform temperature distributions across the electrolyzer stack, with inter-cell and in-plane temperature gradients exceeding 9 °C. Although increasing current density led to higher ohmic and electrochemical losses, energy efficiency increased from 39.4% at 0.106 A·cm⁻² to 56.28% at 0.232 A· cm⁻², as the reduced relative contribution of activation overpotential predominated over the increase in resistive losses within the investigated range. The results demonstrate the strong coupling between electrochemical resistance growth, thermal gradients, and reduced hydrogen production efficiency. Overall, these findings underscore the importance of optimized thermal management and operating strategies for improving the performance and durability of small-scale PEM electrolyzers in green hydrogen applications. Full article

Thermosetting epoxy resins commonly used in wind turbine blades pose significant recycling challenges. This study addresses this limitation by using an eco-friendly, recyclable liquid polymethyl methacrylate (PMMA) resin to fabricate thermoplastic sandwich panels and by investigating their in-plane compressive buckling behavior. The experimental results demonstrated that the proposed PMMA thermoplastic sandwich panels exhibited improved in-plane compressive performance, with a 5.22% higher ultimate load than traditional epoxy counterparts. Furthermore, to investigate the effect of groove configuration on the buckling stability of composite sandwich panels, a finite element (FE) model for PMMA sandwich panels with initial geometric imperfections was established in this paper, and the reliability of the FE model was validated via compression and buckling tests. Finally, a Kriging surrogate model coupled with the NSGA-II algorithm was adopted to carry out multi-objective optimization, with groove parameters set as design variables. Based on the FE verification results, the optimized configuration (Point A) reduced the structural mass by 2.24%, while increasing the critical buckling load and shear modulus by 5.71% and 10.27%, respectively. Research on the buckling performance and groove configurations of PMMA sandwich panels, which can be applied to wind turbine blade webs and airfoils, can provide crucial data support for the engineering application of sustainable PMMA-based large-scale wind turbine blades. Full article

Online incremental orthophoto generation with multiple unmanned aerial vehicles (UAVs) remains challenging, as it requires accurate, efficient, and scalable mapping from distributed aerial observations. In this paper, we present a centralized GNSS-assisted multi-UAV 3D Gaussian Splatting SLAM framework for online incremental orthophoto mapping. Each UAV independently performs visual odometry to build local submaps, which are first aligned into a unified global coordinate system using GNSS constraints and further refined via inter-agent visual loop closures for improved cross-agent consistency. To enable scalable and high-quality mapping, we introduce two complementary Gaussian map maintenance modules: plane-guided grid-based collaborative densification, which improves mapping quality and accelerates convergence under multi-UAV conditions, and visibility-aware adaptive pruning, which effectively controls redundancy and memory usage. These components allow efficient joint optimization within a unified Gaussian representation. Experiments on multiple aerial datasets using video-derived image frames captured by consumer-grade UAV cameras demonstrate that the proposed system provides a favorable trade-off between geo-consistency, visual fidelity, and efficiency compared with existing methods. Quantitatively, the proposed method achieves a GCP RMSE of 2.32 m, completes multi-UAV orthophoto generation within 3.3–5.5 min, and reduces the total mapping time by approximately 35–55% compared with the corresponding single-UAV setting, while supporting online tracking and incremental orthophoto updates with bounded latency and memory consumption. Full article

Background: Breast implant illness (BII) is a constellation of non-specific systemic and local symptoms—including fatigue, joint pain, cognitive dysfunction, and autoimmune-like manifestations—attributed to silicone breast implants. Although BII remains a controversial clinical entity, accumulating evidence suggests symptom improvement following implant removal; however, causal mechanisms and optimal surgical strategies remain uncertain. Objective: The objective was to evaluate the prevalence of BII symptoms and the effect of explantation with en bloc total capsulectomy on symptom resolution in affected women. Methods: A prospective case series of 50 women who underwent explantation with total capsulectomy between 2023 and 2025 was conducted (Level IV evidence). The BII Questionnaire of the American Society for Aesthetic Plastic Surgery (ASAPS) was administered to assess preoperative and one-year postoperative symptom burden. Perioperative data—including implant characteristics, capsular findings, and imaging results—were analyzed. Symptom changes were assessed using descriptive statistics and nonparametric tests. Results: The mean age at explantation was 43 years, with a mean age at implantation of 31 years. Implants were predominantly placed in the retropectoral plane (80%). Intraoperative rupture was identified in 34 patients (68%). At one-year follow-up, a statistically significant reduction in symptom burden was observed, with an 81.7% decrease in mean symptom frequency (preoperative mean: 10.79 vs. postoperative: 1.97; p < 0.001). The most pronounced improvements were noted in chronic fatigue, cognitive impairment, and delayed wound healing. No surgical complications were recorded, and aesthetic outcomes were satisfactory among patients who underwent single-stage mastopexy. Conclusions: Explantation with en bloc total capsulectomy is associated with substantial symptom improvement in women presenting with BII. Although the precise pathophysiology of BII remains elusive, these findings support a patient-centered approach incorporating thorough preoperative evaluation and shared decision-making. Future research should prioritize the development of standardized diagnostic criteria, biomarker validation, and patient subgroup stratification to optimize clinical management and further advance the understanding of BII. Limitations: The absence of a control group precludes causal inference. Objective clinical and immunological assessments were not performed. Patient-reported symptoms were not corroborated by formal clinical evaluation. Most patients were self-referred, introducing referral and expectation bias. The sample size was small. Full article

Ultrasound examination for developmental dysplasia of the hip (DDH) in infants is highly dependent on operator experience, leading to inconsistent imaging quality and poor reproducibility between sonographers. This study proposes an autonomous robotic ultrasound system to improve the standardization and automation of hip ultrasound examinations. The system consists of a robotic arm, a six-axis force/torque sensor, an RGB-D camera and an ultrasound probe, integrating multiple functions including contact force control, visual localization, deep-learning-based segmentation and ultrasound image screening. To ensure stability and safety during scanning, an admittance-based hybrid force/position control strategy is adopted to achieve constant contact force control. For Graf standard plane acquisition, a stage-wise search strategy is designed, in which the search space is progressively narrowed through femoral head searching and multi-angle scanning. The optimal Graf standard plane is then automatically selected by combining image segmentation with a scoring mechanism. A customized hip phantom was used for validation. Experimental results show that the Dice coefficient for femoral head segmentation reaches 0.872, while the average Dice coefficient for multi-structure segmentation reaches 0.866. In 30 autonomous scanning trials, the success rate of Graf standard plane acquisition is 90.0%. Meanwhile, the system can maintain the contact force stably within the target range during scanning, validating the effectiveness of the force control strategy. These results indicate that the proposed robotic system, image recognition algorithm and visual servo control strategy exhibit favorable safety and feasibility, providing an innovative solution for automated infant hip ultrasound examination of DDH. Full article

Background and Objectives: To assess refractive and visual outcomes following phacoemulsification using a novel algorithm for toric intraocular lens (IOL) surgery. Setting: Private practice, Spain. Design: Prospective observational study. Materials and Methods: The algorithm was designed to control the topographic position of the principal meridians (flat and steep) after cataract surgery in eyes without associated corneal pathology or previous corneal surgery. It is well known that a toric IOL must be positioned along the steep meridian. Therefore, it is crucial to predict both the postoperative position of the steep meridian and its magnitude. Data from patients who were planned for refractive lens exchange or cataract surgery using the Pešić-Barraquer algorithm and implantation of a toric IOL in eyes with different degrees of astigmatism were used to assess the effect of residual astigmatism on 6-month postoperative monocular uncorrected and corrected distance logMAR visual acuity values (UDVA and CDVA). Vector analysis was performed with J0 and J45 evaluations, and centroid errors in postoperative refractive astigmatism prediction error were calculated in the spectacle plane using the “Astigmatism Double-Angle Plot Tool”. Results: Three hundred and six eyes of 250 patients with a mean age of 69.0 years ± 8.6 were enrolled in the study. The mean preoperative corneal astigmatism measured with Pentacam was 1.43 D ± 0.83 (SD). One hundred and eighty-four eyes (60.13%) had “against-the-rule” (ATR) astigmatism, 67 (21.90%) had “with-the-rule” (WTR) astigmatism, and 55 (17.97%) eyes had “oblique” corneal (OBL) astigmatism preoperatively. The mean absolute astigmatic prediction error in residual astigmatism was 0.31 D ± 0.28. Eyes with preoperative ATR corneal astigmatism had lower mean absolute errors compared to the eyes with WTR astigmatism (0.29 D ± 0.26 and 0.34 D ± 0.31, respectively). Centroid error in predicted residual astigmatism was 0.08 D ± 0.41 @4°. All eyes achieved residual refractive astigmatism within the 1.00 D range, and 55.23% had no residual astigmatism in the spectacle plane. Mean postoperative refractive astigmatism at the spectacle plane was 0.24 D ± 0.29. There were no postoperative complications. Additional statistical analysis of 310 eyes confirmed that when the main incision is not placed on one of the three meridians (flat, steep, or 45-degree bisector), the axis of astigmatism induced by the incision is significantly altered. Exploratory subgroup analyses demonstrated comparable prediction accuracy across incision positions, preoperative astigmatism types, and surgeons, further supporting the robustness of the proposed algorithm. Conclusions: In addition to enabling more accurate prediction of postoperative refractive residual astigmatism in patients undergoing toric IOL implantation, our newly proposed algorithm provides surgical pearls to facilitate preoperative and intraoperative management of corneal astigmatism, highlighting the importance of precise incision placement for optimal refractive outcomes. Full article

Software-defined satellite networks (SDSNs) enhance resource utilization and flexibility in space-based networks by leveraging a global view and programmability. A highly reliable control plane is essential to sustain network operations. However, the highly dynamic topology and physical failures in Low Earth Orbit (LEO) environments can cause satellite node outages or inter-satellite link disruptions, leading to control plane interruptions and local load imbalances. To address this, we propose a switch migration mechanism for failure recovery and establish a multi-objective migration model that jointly optimizes control link delay, controller load variance, and normalized migration ratio. To accommodate distinct dynamic characteristics such as frequent topology changes, failure-intensive periods, and stable periods, we design two algorithms: a robust migration algorithm, DNSGA-II, which features population diversity maintenance and environmental awareness, and an efficient migration algorithm, IHAOAVOA, which integrates strong global exploration with powerful local exploitation. Simulation results show that IHAOAVOA rapidly converges under large-scale failures, achieving millisecond-level delay recovery and low normalized migration ratio overhead during failure-intensive periods, while DNSGA-II focuses on long-term load balancing and system stability during stable periods, effectively suppressing localized controller overload. By adopting IHAOAVOA during topology fluctuations or high-failure phases to reduce delay, and switching to DNSGA-II during stable phases to optimize load distribution, the overall network robustness can be improved under the evaluated failure scenarios. This work provides effective support for achieving highly reliable control in SDSNs under failure scenarios. Full article