Search Results (237)

Detecting and classifying construction workers’ drowsiness is critical in the construction safety management domain. Research efforts to increase the reliability of drowsiness detection through image augmentation and computer vision approaches face two key challenges: the related size constraints and the number of manual tasks associated with creating input images necessary for training vision algorithms. Although text-to-image (T2I) has emerged as a promising alternative, the dynamic relationship between T2I-driven image characteristics (e.g., contextual relevance), different computer vision algorithms, and the resulting performance remains lacking. To address the gap, this study proposes T2I-centered computer vision approaches for enhanced drowsiness detection by creating four separate image sets (e.g., construction vs. non-construction) labeled using the polygon method, developing two detection models (YOLOv8 and YOLO11), and comparing the performance. The results showed that the use of construction domain-specific images for training both YOLOv8 and YOLO11 led to higher mAP@50 of 68.2% and 56.6%, respectively, compared to those trained using non-construction images (53.4% and 53.5%). Also, increasing the number of T2I-generated training images improved mAP@50 from 68.2% (baseline) to 95.3% for YOLOv8 and 56.6% to 93.3% for YOLO11. The findings demonstrate the effectiveness of leveraging the T2I augmentation approach for improved construction workers’ drowsiness detection. Full article

The role of wall roughness in heat and mass transfer for fully developed viscous flows in square microchannels is investigated here. Since the roughness, which is the key geometrical feature to be investigated, introduces high velocity gradients at the wall, the effect of the viscous dissipation is considered. A fully developed flow in the forced convection regime is assumed. This assumption allows the two-dimensional treatment of the problem; thus, the velocity and temperature fields are simulated on the microchannel cross-section. The boundary roughness is modeled by randomly throwing points around the nominal square cross-section perimeter and by connecting those points to generate a simple polygon. This modification of the nominal square shape of the cross-section influences the velocity and temperature fields, which are computed by employing a finite element method solver. The heat and mass transfer is studied by calculating the Nusselt and the Poiseuille numbers as a function of roughness amplitude at the boundary. Each Nusselt and Poiseuille number is obtained by employing an averaging procedure over a sample of a thousand cases. Full article

Remotely sensed data have been instrumental in improving our understanding of the nature of fires within tropical landscapes. However, most studies have depicted fires in a negative light, highlighting how land-use and land-cover changes make forests more vulnerable to fire damage. In contrast to such fires, indigenous peoples utilize fires as a key part of their livelihood practices, and such relationships have not been extensively examined using remotely sensed data. In this paper, we utilize MODIS Active Fire data to examine the spatial and temporal distribution of fires relative to indigenous lands across Guyana. We employed the DBSCAN clustering algorithm and Voronoi polygons to examine the patterns of fire distribution across the Guyanese landscape. We found that while indigenous territories accounted for approximately 15% of Guyana’s terrestrial landscape, 25% of fires occurred within Amerindian lands, and 71% within 16 km of village boundaries. A strong linear distance decay (R² = 0.97) was observed between the occurrence of fires and Amerindian village boundaries. Four previously undefined fire regions emerged for Guyana–Coastal, Forest, Forest Edge North, and Forest Edge South–with the Forest Edge regions hosting the second highest number of fires but the highest indigenous peoples’ presence. The spatial distribution of fires relative to each region suggested that Forest Edge indigenous villages had a strong reliance on fires as a part of their toolkit for maintaining the rich ecological processes characteristically observed around their lands. Full article

This paper addresses the critical challenge of deploying a minimum number of wireless charging pads (WCPs) in obstacle-rich, large-scale Wireless Rechargeable Sensor Networks (WRSNs) to sustain drone operations. We assume a single base station, stationary sensors, convex polygonal obstacles that drones must avoid, and that both the base station and WCPs provide unlimited energy. To solve this, we propose the Outside-to-Inside Onion-Peeling (OIOP) strategy, a novel two-stage algorithm that prioritizes the coverage of the most remote sensors first and then refines the deployment by removing redundant pads while strictly adhering to obstacle constraints. Simulation results demonstrate OIOP’s superior efficiency: it reduces the number of required pads by approximately 10.83% ± 1.30% and 12.16% ± 1.59% compared to state-of-the-art methods (SMC and MC) and achieves execution times that are 58.02% ± 2.44% and 72.09% ± 2.88% faster, respectively. The algorithm also exhibits remarkable robustness, showing the smallest performance degradation as obstacle density increases. Full article

Symmetry breaking is crucial in many areas of physics, mathematics, biology, and engineering. We investigate the symmetry of regular convex polygons, non-convex regular polygons (stars), and symmetric Jordan curves/domains. We demonstrate that removing a single point from the boundary of regular convex and non-convex polygons and symmetrical Jordan curves reduces the symmetry group of the polygon to the trivial $C_1$ group when the point does not belong to the axis of symmetry of the polygon. The same is true for solid and open 2D regular convex polygons and symmetric Jordan curves. The only exception is a circle. Removing a single point from the boundary of a circle creates a curve characterized by the $C_2$ group. The symmetry of circles is reduced to the trivial $C_1$ group by removing a triad of non-symmetrical points. The same is true for a solid circle. The “effort” necessary to break the symmetry of a circle is maximal. A 3D generalization of the theorem is exemplified. Thus, the classification of symmetrical curves following the minimal number of points necessary to break their symmetry becomes possible. The demonstrated theorem shows that the symmetry group action on curves and domains becomes trivial when an asymmetric perturbation is introduced, when the curve is not a circle. An informational interpretation of the demonstrated theorem, which is related to the Landauer principle, is provided. Full article

Traditional unmanned aerial vehicle (UAV) path planning methods for image-based 3D reconstruction often rely solely on geometric information from initial models, resulting in redundant data acquisition in non-architectural areas. This paper proposes a UAV path planning method via semantic segmentation of 3D reality mesh models to enhance efficiency and accuracy in complex scenarios. The scene is segmented into buildings, vegetation, ground, and water bodies. Lightweight polygonal surfaces are extracted for buildings, while planar segments in non-building regions are fitted and projected into simplified polygonal patches. These photography targets are further decomposed into point, line, and surface primitives. A multi-resolution image acquisition strategy is adopted, featuring high-resolution coverage for buildings and rapid scanning for non-building areas. To ensure flight safety, a Digital Surface Model (DSM)-based shell model is utilized for obstacle avoidance, and sky-view-based Real-Time Kinematic (RTK) signal evaluation is applied to guide viewpoint optimization. Finally, a complete weighted graph is constructed, and ant colony optimization is employed to generate a low-energy-cost flight path. Experimental results demonstrate that, compared with traditional oblique photogrammetry, the proposed method achieves higher reconstruction quality. Compared with the commercial software Metashape, it reduces the number of images by 30.5% and energy consumption by 37.7%, while significantly improving reconstruction results in both architectural and non-architectural areas. Full article

Buildings are a significant component of urban space and are essential to smart cities, catastrophe monitoring, and land use planning. However, precisely extracting building polygons from remote sensing images remains difficult because of the variety of building designs and intricate backgrounds. This paper proposes an end-to-end polygon dynamic adjustment algorithm (PDAA) to improve the accuracy and geometric consistency of building contour extraction by dynamically generating and optimizing polygon vertices. The method first locates building instances through the region of interest (RoI) to generate initial polygons, and then uses four core modules for collaborative optimization: (1) the feature enhancement module captures local detail features to improve the robustness of vertex positioning; (2) the contour vertex tuning module fine-tunes vertex coordinates through displacement prediction to enhance geometric accuracy; (3) the learnable redundant vertex removal module screens key vertices based on a classification mechanism to eliminate redundancy; and (4) the missing vertex completion module iteratively restores missed vertices to ensure the integrity of complex contours. PDAA dynamically adjusts the number of vertices to adapt to the geometric characteristics of different buildings, while simplifying the prediction process and reducing computational complexity. Experiments on public datasets such as WHU, Vaihingen, and Inria show that PDAA significantly outperforms existing methods in terms of average precision (AP) and polygon similarity (PolySim). It is at least 2% higher than existing methods in terms of average precision (AP), and the generated polygonal contours are closer to the real building geometry. Values of 75.4% AP and 84.9% PolySim were achieved on the WHU dataset, effectively solving the problems of redundant vertices and contour smoothing, and providing high-precision building vector data support for scenarios such as smart cities and emergency response. Full article

Plastid division regulatory genes play a crucial role in the morphogenesis of chloroplasts and amyloplasts. Chloroplasts are the main sites for photosynthesis and metabolic reactions, while amyloplasts are the organelles responsible for forming and storing starch granules. The proper division of chloroplasts and amyloplasts is essential for plant growth and yield maintenance. Therefore, this study aimed to examine the J175 (FtsZ2-2) gene, cloned from an ethyl methanesulphonate (EMS) mutant involved in chloroplast and amyloplast division in maize, through map-based cloning. We found that J175 encodes a cell division protein, FtsZ (filamentous temperature-sensitive Z). The FtsZ family of proteins is widely distributed in plants and may be related to the division of chloroplasts and amyloplasts. The J175 protein is localized in plastids, and its gene is expressed across various tissues. From the seedling stage, the leaves of the j175 mutant exhibited white stripes, while the division of chloroplasts was inhibited, leading to a significant increase in volume and a reduction in their number. Measurement of the photosynthetic rate showed a significant decrease in the photosynthetic efficiency of j175. Additionally, the division of amyloplasts in j175 grains at different stages was impeded, resulting in irregular polygonal starch granules. RNA-seq analyses of leaves and kernels also showed that multiple genes affecting plastid division, such as FtsZ1, ARC3, ARC6, PDV1-1, PDV2, and MinE1, were significantly downregulated. This study demonstrates that the maize gene j175 is essential for maintaining the division of chloroplasts and amyloplasts and ensuring normal plant growth, and provides an important gene resource for the molecular breeding of maize. Full article

In recent years, droughts and extreme weather events have witnessed increasing frequency around the globe, leading to a growing number of issues related to soil cracking that severely impact the stability of engineering projects and ecological environments. This study mainly investigates the cracking of clay in arid areas of Xinjiang. An experiment is conducted in a climate simulation laboratory, in which we explored the evolution of soil drying cracks under different (straight/curved) boundary constraints. The crack development process is quantitatively described through the use of digital imaging technology and by combining parameters such as crack rate, fractal dimension, and water-holding performance at different boundaries. The following conclusions were drawn: Under curved boundary conditions, cracks expand in a curve-like manner, and the cracks in the boundary area are densely distributed. However, under straight boundary conditions, penetrating straight cracks are formed, and the soil blocks present as regular polygons. Boundary conditions significantly impact the residual water content. Under straight boundary conditions, the residual masses of strongly and weakly bound water are significantly higher than those under curved boundary conditions. The complexity of the crack network under the curved boundary condition is higher, and its fractal dimension is significantly greater than that under the straight boundary condition. A quantitative analysis based on the use of digital image processing technology indicates that the boundary geometry has a significant controlling effect on the crack propagation path. This research provides guidance on the prevention and control of soil engineering cracking and damage in arid regions. Full article

Posterior pituitary tumors (PPTs) are rare, non-neuroendocrine neoplasms derived from pituicytes of the neurohypophysis or infundibulum. According to the 2025 WHO classification, PPTs comprise four distinct but related low-grade entities: pituicytoma, granular cell tumor of the sellar region, spindle cell oncocytoma, and ependymal pituicytoma. All share nuclear TTF-1 expression, confirming their common origin, but differ in morphology, immunophenotype, and ultrastructure. Histologically, pituicytomas consist of bipolar spindle cells in fascicles; granular cell tumors show polygonal cells with PAS-positive, diastase-resistant cytoplasmic granules; spindle cell oncocytomas display oncocytic change and abundant mitochondria; and ependymal pituicytomas exhibit perivascular pseudorosettes and EMA positivity in apical or dot-like patterns. Immunohistochemically, all are S100 and vimentin positive, and negative for pituitary hormones and lineage-specific transcription factors. Clinically, PPTs are typically non-functioning but may be associated with corticotroph or somatotroph hyperfunction. Imaging features are nonspecific. Surgical resection is the treatment of choice, although hypervascularity and adherence—especially in spindle cell oncocytomas—can hinder complete excision. Radiotherapy is reserved for recurrences. Molecular analyses reveal recurrent alterations in MAPK/PI3K pathways (e.g., HRAS, BRAF, FGFR1, NF1, TSC1) and suggest a shared histogenesis. Copy number imbalances correlate with reduced progression-free survival in some subtypes. Despite a generally favorable prognosis, recurrence—particularly in spindle cell oncocytomas—necessitates long-term follow-up. The WHO 2025 update provides a unified framework for classification, diagnosis, and prognostic stratification of these rare tumors. Full article

This paper concerns the old problem of the connection between the dilatations of a given quasisymmetric homeomorphism h of a circle and the associated polygonal quasiconformal maps with a fixed finite number of boundary points, namely whether $k\left(h\right)=sup{k}_n$, where the supremum is taken over all possible n-gons formed by the disk with n distinguished boundary points. A still open question is whether such equality is valid under the additional assumption that the naturally related univalent functions with quasiconformal extensions have equal Grunsky and Teichmüller norms. We solved this problem in the negative for $n\ge 4$. Full article

Road infrastructure is a critical component of modern society, with its maintenance directly influencing traffic safety and logistical efficiency. In this context, automated crack detection technology plays a vital role in reducing maintenance costs and enhancing operational efficiency. However, previous studies are limited by the fact that they provide only bounding box or segmentation mask annotations for a restricted number of crack classes and use a relatively small size of datasets. To address these limitations and advance deep learning-based crack segmentation, this study introduces a novel crack segmentation dataset that reflects real-world road conditions. The proposed dataset includes various types of cracks and defects—such as slippage, rutting, and construction-related cracks—and provides polygon-based segmentation masks captured from an egocentric, vehicle-mounted perspective. Using this dataset, we evaluated the performance of semantic and instance segmentation models. Notably, SegFormer achieved the highest Pixel Accuracy (PA) and mean Intersection over Union (mIoU) for semantic segmentation, while YOLOv7 exhibited outstanding detection performance for alligator crack class, recording an ${AP}_{50}$ of 87.2% and $AP$ of 57.5%. In contrast, all models struggled with the reflection crack type, indicating the inherent segmentation challenges. Overall, this study provides a practical and robust foundation for future research in automated road crack segmentation. Additional resources including the dataset and annotation details can be found at our GitHub repository. Full article

Secret sharing is a robust data protection technique that secures sensitive information by partitioning it into multiple shares, such that the original data can only be reconstructed when a sufficient number of shares are combined. While this method has seen remarkable progress in the realm of images, its exploration and application in 3D models remain in their early stages. Given the growing prominence of 3D models in multimedia applications, ensuring their security and privacy has emerged as a critical area of research. At present, secret sharing approaches for 3D models predominantly rely on the vertex coordinates of the model as the basis for embedding and reconstructing secret messages. However, due to the limited quantity of vertex coordinates, these methods face significant constraints in embedding capacity, thereby limiting the potential of 3D models in secure data sharing. In contrast, the vertex indices of polygons, characterized by higher information density and greater structural flexibility, present a promising alternative medium for embedding secret shares. Building on this premise, the present study investigates the feasibility of leveraging shared vertex indices as a foundation for message embedding. It highlights the advantages of this approach in enhancing both the embedding capacity and the overall security of 3D models. By integrating the Chinese Remainder Theorem into vertex index-based sharing, the proposed method strengthens existing algorithms, offering improved model protection and enhanced embedding security. Experimental evaluations reveal that, compared to traditional vertex coordinate-based methods, incorporating vertex indices into secret sharing techniques significantly increases embedding efficiency while bolstering the security of 3D models. This study not only introduces an innovative approach to safeguarding 3D model data but also paves the way for the broader application of secret sharing techniques in the future. Full article

This study investigates the effects of molybdenum (Mo) and boron (B) on the microstructures and impact properties in the coarse grain heat-affected zone (CGHAZ) of a low-carbon V-Ti-N steel. The results demonstrate that, at a heat input of up to 75 kJ/cm, the addition of Mo alters the microstructure of the CGHAZ, transforming it from a polygonal ferrite (PF) + degraded pearlite (DP) composition to a granular bainite (GB) + a small amount of acicular ferrite (AF). This transformation increases the impact energy from 20 J to 35 J. Furthermore, with the Mo/B composite addition, the CGHAZ microstructure was refined due to the formation of a large number of acicular ferrites, and the mean equivalent diameter (MED_MTA≥15°) decreased from 7.9 μm to 4.2 μm. Consequently, the impact toughness of the CGHAZ increased from 35 J to 111 J. The correlation between the Mo/B elements, microstructure and impact toughness was investigated in detail. The findings of this study have the potential to generate novel ideas for the advancement of steel materials in the context of high heat input welding. Full article

Quantization for a Borel probability measure refers to the idea of estimating a given probability by a discrete probability with support containing a finite number of elements. If, in the quantization some of the elements in the support are preselected, then the quantization is called a conditional quantization. In this paper, we investigate the conditional quantization for the uniform distributions defined on the unit line segments and m-sided regular polygons, where $m\ge 3$, inscribed in a unit circle. Full article