Search Results (4,097)

The accurate and efficient placement of traffic cones is a critical safety and logistical requirement in diverse industrial environments. This study introduces a novel dataset specifically designed for the near-overhead detection of traffic cones, containing both bounding box annotations and apex keypoints. Leveraging this dataset, we systematically evaluated whether classical object detection methods or keypoint-based detection methods are more effective for the task of cone apex localization. Several state-of-the-art YOLO-based architectures (YOLOv8, YOLOv11, YOLOv12) were trained and tested under identical conditions. The comparative experiments showed that both approaches can achieve high accuracy, but they differ in their trade-offs between robustness, computational cost, and suitability for real-time embedded deployment. These findings highlight the importance of dataset design for specialized viewpoints and confirm that lightweight YOLO models are particularly well-suited for resource-constrained robotic platforms. The key contributions of this work are the introduction of a new annotated dataset for overhead cone detection and a systematic comparison of object detection and keypoint detection paradigms for apex localization in real-world robotic applications. Full article

The hydrogen economy stands at the forefront of the global energy transition, and additive manufacturing (AM) is increasingly recognized as a critical enabler of this transformation. AM offers unique capabilities for improving the performance and durability of hydrogen energy components through rapid prototyping, topology optimization, functional integration of cooling channels, and the fabrication of intricate, hierarchical, structured pores with precisely controlled connectivity. These features facilitate efficient heat and mass transfer, thereby improving hydrogen production, storage, and utilization efficiency. Furthermore, AM’s multi-material and functionally graded printing capability holds promise for producing components with tailored properties to mitigate hydrogen embrittlement, significantly extending operational lifespan. Collectively, these advances suggest that AM could lower manufacturing costs for hydrogen-related systems while improving performance and reliability. However, the current literature provides limited evidence on the integrated techno-economic advantages of AM in hydrogen applications, posing a significant barrier to large-scale industrial adoption. At present, the technological readiness level (TRL) of AM-based hydrogen components is estimated to be 4–5, reflecting laboratory-scale progress but underscoring the need for further development, validation and industrial-scale demonstration before commercialization can be realized. Full article

Hydrogen is increasingly recognized as a clean energy vector and storage medium, yet its viability and strategic role in the Western Balkans remain underexplored. This study provides the first comprehensive techno-economic, environmental, and strategic evaluation of hydrogen production pathways in Albania. Results show clear trade-offs across options. The levelized cost of hydrogen (LCOH) is estimated at 8.76 €/kg H₂ for grid-connected, 7.75 €/kg H₂ for solar, and 7.66 €/kg H₂ for wind electrolysis—values above EU averages and reliant on lower electricity costs and efficiency gains. In contrast, fossil-based hydrogen via steam methane reforming (SMR) is cheaper at 3.45 €/kg H₂, rising to 4.74 €/kg H₂ with carbon capture and storage (CCS). Environmentally, Life Cycle Assessment (LCA) results show much lower Global Warming Potential (<1 kg CO₂-eq/kg H₂) for renewables compared with ~10.39 kg CO₂-eq/kg H₂ for SMR, reduced to 3.19 kg CO₂-eq/kg H₂ with CCS. However, grid electrolysis dominated by hydropower entails high water-scarcity impacts, highlighting resource trade-offs. Strategically, Albania’s growing solar and wind projects (electricity prices of 24.89–44.88 €/MWh), coupled with existing gas infrastructure and EU integration, provide strong potential. While regulatory gaps and limited expertise remain challenges, competition from solar-plus-storage, regional rivals, and dependence on external financing pose additional risks. In the near term, a transitional phase using SMR + CCS could leverage Albania’s gas assets to scale hydrogen production while renewables mature. Overall, Albania’s hydrogen future hinges on targeted investments, supportive policies, and capacity building aligned with EU Green Deal objectives, with solar-powered electrolysis offering the potential to deliver environmentally sustainable green hydrogen at costs below 5.7 €/kg H₂. Full article

Conventional upper limb rehabilitation methods often encounter significant obstacles, including high costs, limited accessibility, and reduced patient adherence. Emerging technological solutions, such as telerehabilitation, virtual reality (VR), and wearable sensor-based systems, address some of these challenges but still face issues concerning supervision quality, affordability, and usability. To overcome these limitations, this study presents an innovative and cost-effective rehabilitation system based on advanced computer vision techniques and artificial intelligence (AI). Developed using Python (3.11.5), the proposed system utilizes a standard webcam in conjunction with robust pose estimation algorithms to provide real-time analysis of patient movements during guided upper limb exercises. Instructional exercise videos featuring an NAO robot facilitate patient engagement and consistency in practice. The system generates instant quantitative feedback on movement precision, repetition accuracy, and exercise phase completion. The core advantages of the proposed approach include minimal equipment requirements, affordability, ease of setup, and enhanced interactive guidance compared to traditional telerehabilitation methods. By reducing the complexity and expense associated with many VR and wearable-sensor solutions, while acknowledging that some lower-cost and haptic-enabled VR options exist, this single-webcam approach aims to broaden access to guided home rehabilitation without specialized hardware. Full article

LiDAR-based Simultaneous Localization and Mapping (SLAM) plays a key role in enabling inspection robots to achieve autonomous navigation. However, at installation construction sites of large-scale public buildings, existing methods often suffer from point-cloud drift, large z-axis errors, and inefficient loop closure detection, limiting their robustness and adaptability in complex environments. To address these issues, this paper proposes an improved algorithm, LeGO-LOAM-LPB (Large-scale Public Building), built upon the LeGO-LOAM framework. The method enhances feature quality through point-cloud preprocessing, stabilizes z-axis pose estimation by introducing ground-residual constraints, improves matching efficiency with an incremental k-d tree, and strengthens map consistency via a two-layer loop closure detection mechanism. Experiments conducted on a self-developed inspection robot platform in both simulated and real construction sites of large-scale public buildings demonstrate that LeGO-LOAM-LPB significantly improves positioning accuracy, reducing the root mean square error by 41.55% compared with the original algorithm. The results indicate that the proposed method offers a more precise and robust SLAM solution for safety inspection robots in construction environments and shows strong potential for engineering applications. Full article

A multi-target robust observation method for satellite constellations based on hypergraph algebraic connectivity and observation precision theory is proposed to address the challenges posed by the surge in space targets and system failures. First, a precision metric framework is constructed based on nonlinear batch least squares estimation theory, deriving the theoretical precision covariance through cumulative observation matrices to provide a theoretical foundation for tracking accuracy evaluation. Second, multi-satellite collaborative observation is modeled as an edge-dependent vertex-weighted hypergraph, enhancing system robustness by maximizing algebraic connectivity. A constrained simulated annealing (CSA) algorithm is designed, employing a precision-guided perturbation strategy to efficiently solve the optimization problem. Simulation experiments are conducted using 24 Walker constellation satellites tracking 50 targets, comparing the proposed method with greedy algorithm, CBBA, and CSA-bipartite Graph methods across three scenarios: baseline, maneuvering, and failure. Results demonstrate that the CSA-hypergraph method achieves 0.089 km steady-state precision in the baseline scenario, representing a 41.4% improvement over traditional methods; in maneuvering scenarios, detection delay is reduced by 34.3% and re-achievement time is decreased by 47.4%; with a 30% satellite failure rate, performance degradation is only 9.8%, significantly outperforming other methods. Full article

Brassinosteroid analogs with heterocyclic rings in the side chain are interesting because important biological activity has been shown by these compounds. Thus, herein, five 23-24-dinorcholane BR analogs with a heterocyclic ester function at C-22 were synthesized and fully characterized by different spectroscopic techniques. The acylation reaction at C-22, which is a key synthetic step, was carried out by two different methods, namely acylation with heterocyclic acid chlorides and Steglich esterification reaction. In both cases, the acyl derivatives were obtained with good yields. Additionally, a preliminary molecular docking study of BRI1–BAK1 complexes formed by these analogs and brassinolide was performed to estimate what their biological activity would be. Results indicate that the complex formed by the analog 36, which has an indole group in the side chain, within the active site of BRI1–BAK1 is more stable than that formed by brassinolide. Additionally, molecular docking of a derivative having a benzoate function at C-22 and a F atom in the ortho position, 23, shows a similar pose and interactions at the active site but the highest binding energy. As 23 has shown similar activity to brassinolide in the Rice Lamina Inclination Test, it is expected that 36 will also exhibit similar behavior. Full article

Event-based (neuromorphic) cameras depart from frame-based sensing by reporting asynchronous per-pixel brightness changes. This produces sparse, low-latency data streams with extreme temporal resolution but demands new processing paradigms. In this survey, we systematically examine neuromorphic vision along three main dimensions. First, we highlight the technological evolution and distinctive hardware features of neuromorphic cameras from their inception to recent models. Second, we review image-processing algorithms developed explicitly for event-based data, covering works on feature detection, tracking, optical flow, depth and pose estimation, and object recognition. These techniques, drawn from classical computer vision and modern data-driven approaches, illustrate the breadth of applications enabled by event-based cameras. Third, we present practical application case studies demonstrating how event cameras have been successfully used across various scenarios. Distinct from prior reviews, our survey provides a broader overview by uniquely integrating hardware developments, algorithmic progressions, and real-world applications into a structured, cohesive framework. This explicitly addresses the needs of researchers entering the field or those requiring a balanced synthesis of foundational and recent advancements, without overly specializing in niche areas. Finally, we analyze the challenges limiting widespread adoption, identify research gaps compared to standard imaging techniques, and outline promising directions for future developments. Full article

Heavy metal(loid) (HM) contamination in water arises from various anthropogenic activities and natural processes, posing risks to human health through ingestion and dermal absorption. Although numerous studies have assessed health risks associated with HMs in water, inconsistencies in the selection of exposure and toxicity factors limit comparability and reliability across studies. To address this gap, the aim of this review was to provide a comprehensive synthesis of exposure and toxicity factors used in health risk assessment (HRA) of HMs in water. The objectives were to evaluate the variability in ingestion, body weight, exposure duration and frequency, and dermal contact parameters, as well as in reference doses and cancer slope factors and to propose standardized values and statistical distributions for more consistent risk estimation. A systematic search of the Scopus database retrieved 806 studies, from which highly cited articles (≥100 citations) and recent publications (2023–2025) were prioritized for analysis. The findings revealed substantial variability in factors and showed that probabilistic approaches, particularly Monte Carlo simulation, were increasingly applied and provided more reliable estimates than traditional deterministic methods. The highest agreement was observed for exposure frequency for ingestion (365 days/year) and skin surface area (18,000 cm²), each applied in 75.5% of cases. By identifying inconsistencies in current practices and proposing standardized exposure and toxicity values and distributions for water, this review is expected to offer practical recommendations to improve the robustness, reliability, and comparability of HRAs, ultimately informing more effective policy-making and water management practices. Full article

Today, the abundance of personal care product (PCP) ingredients and UV filters (UVFs) in coastal marine environments is a growing concern worldwide. In addition, mussels are the most commonly used sentinel organisms in bio-monitoring programs. In the current study, we collected mussels (Mytilus galloprovincialis) (over 6 months) from three seawater sites in Tunisia (Monastir, Sousse, and Mahdia). Analysis of the samples by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) revealed the presence of 13 compounds among the 18 PCP ingredients and UVFs investigated. Avobenzone (AVO) and tert-butyl hydroxyphenyl benzotriazole (TBHPBT) were the most frequently observed, ranging from 121.076 ± 1.6 to 193.481 ± 5.5 ng g⁻¹ and 20.987 ± 0.7 to 26.704 ± 1.7 ng g⁻¹, respectively, with maximum values in the city of Sousse. 4-Hydroxybenzophenone (4HB) and benzophenone-1 (BP1) were also found in all mussel samples with levels in the range of 26.745 ± 0.4 ng g⁻¹ and 12.53 ± 0.5 ng g⁻¹, respectively. We observed a positive correlation with the chemical characterization of the contaminated seawater. The environmental hazards of PCP ingredients were estimated with the aim of performing a preliminary risk assessment at the environmental level. For this purpose, the estimated daily intake (EDI) of a substance was calculated. The results obtained revealed a high value of up to 68.36 ng kg body-weight⁻¹ day⁻¹. The high concentration observed in the samples reported for the target PCP ingredients could be partly attributed to their inefficient removal before being released into the sea. We now know that PCP ingredients and UVFs cause irreparable damage to coastal ecosystems and pose the greatest risk to the aquatic organisms tested. Full article

Northern Thailand experiences annual haze events with fine particulate matter (PM2.5) exceeding standards, posing risks to schoolchildren. This cross-sectional study (Chiang Mai, 2024) evaluated respiratory impacts among primary school children aged 8–12 years. Daily mean PM2.5 concentrations were obtained from a single fixed-site monitoring station (36T) located within 2 km of the spirometry site. Among 93 children with acceptable spirometry, 52% exhibited restrictive, 18% obstructive, and 30% had normal function. After adjustment for BMI, males had significantly lower odds of any pulmonary abnormality than females (AOR = 0.084; 95% CI 0.017–0.417; p = 0.002). The mean FEV₁/FVC ratio was normal (86.30 ± 13.07%), whereas mean FVC, FEV₁, and PEF were significantly below predicted values, indicating a predominantly restrictive pattern. This predominance likely reflects cumulative exposure to biomass-burning related PM2.5 during the haze season, infiltration of outdoor PM2.5 into indoor environments alongside indoor sources, and the vulnerability of developing lungs in children’s factors that reduce lung volumes while largely preserving the FEV₁/FVC ratio. The exposure assessment provides pragmatic, proximity-based estimates but is limited by reliance on one station and one season, which may not capture spatial or temporal variability. These findings highlight sex-based susceptibility and support stronger air quality protections for children. Full article

Quantitative susceptibility mapping (QSM) is a powerful magnetic resonance imaging (MRI) technique for assessing tissue composition in the human body. For imaging short-T2 tissues in the musculoskeletal (MSK) system, ultrashort echo time (UTE) imaging plays a key role. However, UTE-based QSM (UTE-QSM) often involves repeated acquisitions, making it vulnerable to inter-scan motion. In this study, we investigate the effects of motion on UTE-QSM and introduce strategies to reduce motion-induced artifacts. Eight healthy male volunteers underwent UTE-QSM imaging of the knee joint, while an additional seven participated in imaging of the ankle joint. UTE-QSM was conducted using multiple echo acquisitions, including both UTE and gradient-recalled echoes, and processed using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) and morphology-enabled dipole inversion (MEDI) algorithms. To assess the impact of motion, datasets were reconstructed both with and without motion correction. Furthermore, we evaluated a two-step UTE-QSM approach that incorporates tissue boundary information. This method applies edge detection, excludes pixels near detected edges, and performs a two-step QSM reconstruction to reduce motion-induced streaking artifacts. In participants exhibiting substantial inter-scan motion, prominent streaking artifacts were evident. Applying motion registration markedly reduced these artifacts in both knee and ankle UTE-QSM. Additionally, the two-step UTE-QSM approach, which integrates tissue boundary information, further enhanced image quality by mitigating residual streaking artifacts. These results indicate that motion-induced errors near tissue boundaries play a key role in generating streaking artifacts in UTE-QSM. Inter-scan motion poses a fundamental challenge in UTE-QSM due to the need for multiple acquisitions. However, applying motion registration along with a two-step QSM approach that excludes tissue boundaries can effectively suppress motion-induced streaking artifacts, thereby improving the accuracy of musculoskeletal tissue characterization. Full article

The study of faults in seismic gap areas is essential for assessing the potential for future seismic activity and developing strategies to mitigate its impact. In this research, we employed a combination of geomorphological analysis, aerophotogrammetry, high-resolution topography, and soil analysis to estimate the age of tectonically exposed fault surfaces in a seismic gap area. Our focus was on the Piano delle Rose Fault in the northern Calabria region, (southern Italy), which is a significant regional tectonic structure associated with seismic hazards. We conducted a field survey to carry out structural and pedological observations and collect soil samples from the fault surface. These samples were analyzed to estimate the fault’s age based on their features and degree of pedogenic development. Additionally, we used high-resolution topography and aerophotogrammetry to create a detailed 3D model of the fault surface, allowing us to identify features such as fault scarps and offsets. Our results indicate recent activity on the fault surface, suggesting that the Piano delle Rose Fault may pose a significant seismic hazard. Soil analysis suggests that the onset of the fault surface is relatively young, estimated in an interval time from 450,000 to ~ 300,000 years old. Considering these age constraints, the long-term slip rates are estimated to range between ~0.12 mm/yr and ~0.33 mm/yr, which are values comparable with those of many other well-known active faults of the Apennines extensional belt. Analyses of key fault exposures document cumulative displacements up to 21 m. These values yield long-term slip rates ranging from ~0.2 mm/yr (100,000 years) to ~1.0 mm/yr (~20,000 years LGM), indicating persistent Late Quaternary activity. A second exposure records ~0.6 m of displacement in very young soils, confirming surface faulting during recent times and suggesting that the fault is potentially capable of generating ground-rupturing earthquakes. High-resolution topography and aerophotogrammetry analyses show evidence of ongoing tectonic deformation, indicating that the area is susceptible to future seismic activity and corresponding risk. Our study highlights the importance of integrating multiple techniques for examining fault surfaces in seismic gap areas. By combining geomorphological analysis, aerophotogrammetry, high-resolution topography, and soil analysis, we gain a comprehensive understanding of the structure and behavior of faults. This approach can help assess the potential for future seismic activity and develop strategies for mitigating its impact. Full article

Tableware objects such as plates, bowls, and cups are usually textureless, uniform in color, and vary widely in shape, making it difficult to apply conventional pose estimation methods that rely on texture cues or object-specific CAD models. These limitations present a significant obstacle to robotic manipulation in restaurant environments, where reliable six-degree-of-freedom (6-DoF) pose estimation is essential for autonomous grasping and collection. To address this problem, we propose a model-free and texture-free 6-DoF pose estimation framework based on a transformer encoder architecture. This method uses only geometry-based features extracted from depth images, including surface vertices and rim normals, which provide strong structural priors. The pipeline begins with object detection and segmentation using a pretrained video foundation model, followed by the generation of uniformly partitioned grids from depth data. For each grid cell, centroid positions, and surface normals are computed and processed by a transformer-based model that jointly predicts object rotation and translation. Experiments with ten types of tableware demonstrate that the method achieves an average rotational error of 3.53 degrees and a translational error of 13.56 mm. Real-world deployment on a mobile robot platform with a manipulator further validated its ability to autonomously recognize and collect tableware, highlighting the practicality of the proposed geometry-driven approach for service robotics. Full article

Digital twins are essential for the real-time health management and monitoring of aeroengines, and the in situ three-dimensional (3D) reconstruction technology of key components of aeroengines is an important support for the construction of a digital twin model. In this paper, an in situ high-fidelity 3D reconstruction method, named PoseNeRF, for aeroengine blades based on the joint optimization of pose and neural radiance field (NeRF), is proposed. An aeroengine blades background filtering network based on complex network theory (ComBFNet) is designed to filter out the useless background information contained in the two-dimensional (2D) images and improve the fidelity of the 3D reconstruction of blades, and the mean intersection over union (mIoU) of the network reaches 95.5%. The joint optimization loss function, including photometric loss, depth loss, and point cloud loss is proposed. The method solves the problems of excessive blurring and aliasing artifacts, caused by factors such as smooth blade surface and weak texture information in 3D reconstruction, as well as the cumulative error problem caused by camera pose pre-estimation. The PSNR, SSIM, and LPIPS of the 3D reconstruction model proposed in this paper reach 25.59, 0.719, and 0.239, respectively, which are superior to other general models. Full article