Geometric analysis on weighted manifolds under lower 0-weighted Ricci curvature bounds

Geometric and radiometric analysis of dual wavelength NIR-LiDAR scanning for estimating physiological and free water of leaves in apple tree canopies

A meshing points capture-based approach for geometric modeling and parametric analysis of variable base-circle scroll compressors

Mining-induced surface cracks are critical indicators of overburden deformation and pose significant threats to ground stability and mine safety. However, their fine-scale geometry and complex background interference make automated extraction challenging. This study proposes an improved DRA-UNet model for high-precision crack detection from UAV orthophotos. The network integrates residual learning, a dual-attention mechanism (DAM), and an atrous spatial pyramid pooling (ASPP) module to enhance feature representation, suppress noise, and capture multi-scale contextual information. A complete analytical framework is established by coupling crack segmentation with skeleton extraction and quantitative geometric characterization, enabling fine-scale morphological analysis. Experimental results show that the proposed method outperforms representative segmentation models, achieving an F1-score of 71.60% and MIoU of 70.00% on a mining-area UAV dataset. Ablation studies verify the effectiveness of each module, while external validation on the Crack500 dataset demonstrates strong cross-scene generalization (F1 = 85.32%, MIoU = 83.69%). Geometric analysis reveals pronounced right-skewed distributions of crack length, width, and area, with rectangularity decreasing as crack length increases. Spatial results indicate higher crack density and complexity near working-face boundaries. Overall, the proposed framework provides a robust and fully automated solution for mining-induced crack detection and morphological analysis.

Abstract This study determines the thermodynamically most probable microstructures (first solvation shell configuration) of saturated NaCl solution via integrated experimental-computational approaches. Experimental XRD analysis reveals distinct structural features distinguishing saturated NaCl solution from pure water. DFT simulations employing the explicit/implicit solvation model identify M(H₂O)₆ (M=Na+, Cl-) clusters as stable first solvation shells, confirmed by both geometric and energetic analyses. Crucially, simulated XRD patterns derived from the first solvation shells show excellent agreement with experimental data in peak positions, plateau regions, and relative intensities, so that the rationality and accuracy of the model has been fully verified.

Monitoring and management of power line corridors are essential for ensuring the safe and reliable operation of power transmission systems. Traditional manual inspection methods are not only inefficient but also pose significant safety risks, while certain existing automated approaches suffer from limited effectiveness in complex terrains or in the presence of discontinuities in point cloud data, resulting in insufficient accuracy in power line extraction and frequent reconstruction failures. To address these challenges, this study proposes a novel power line reconstruction method termed Weighted Multi-feature & Multi-plane Projection Geometric Fusion (WM-MPGF). The proposed method comprises two sequential stages: Weighted Multi-Feature SVM (WMF-SVM) and Multi-plane Projection and Geometric Joint Reconstruction (MPG-Recon). Specifically, WMF-SVM introduces a weighted multi-feature support vector machine framework that integrates elevation data derived from the Digital Elevation Model (DEM) with spatial features extracted via Principal Component Analysis (PCA), while optimizing feature weights through the entropy weight method to enhance the accuracy of power line identification. Subsequently, MPG-Recon performs geometric analysis to construct directional projection planes and applies the Hough transform to project power line points and determine their dominant orientations on the XOY and YOZ planes. The Davies-Bouldin index is employed to determine the optimal number of clusters, thereby enabling accurate estimation of the number of power lines. By integrating the K-means clustering algorithm, the method achieves effective separation of multiple power lines and ensures high-precision fitting of individual conductors. Experimental results indicate that the proposed approach achieves average fitting errors of 5.41 cm on the XOY plane and 5.68 cm in the vertical direction, successfully capturing the three-dimensional structural characteristics of power lines. The method constructs a robust 3D model and provides critical technical support for advanced applications in power line corridor monitoring and maintenance.

Spatial relationships among major geomorphological and archaeological features in the Bosnian Valley of the Pyramids were examined using GIS-based methods. The analysis focused on linear alignments and spiral geometries linking pyramid summits, tumuli, and underground tunnel systems. High-resolution LiDAR data, digital elevation models (DEM), satellite imagery, and GPS-derived coordinates were processed using spatial statistics, regression analysis, and Monte Carlo simulations to determine whether the observed configurations exceed random landscape distributions. The results identify statistically significant linear alignments and a strong correspondence with a Fibonacci-based spiral geometry, with correlation coefficients exceeding R² = 0.99 and probability values below p < 0.01. These geometric patterns were further examined in relation to terrain optimization, slope stability, hydrological flow, and geotechnical constraints. The findings demonstrate that GIS-supported geometric analysis provides a robust framework for investigating large-scale landscape organization and its potential relevance to prehistoric civil engineering and spatial planning

Bayesian and geometric analyses of power spectral densities of spin qubits in Si/SiGe quantum dot devices

In response to the growing interest in sustainable and material-efficient architectural solutions, this study focuses on innovative applications of engineered timber in lightweight structural systems. It investigates the material optimization and structural performance of engineered timber thin-shell structures through an integrated parametric design approach. The study compares three prefabricated, panelized building systems, gridshell, segmented full-plate shell, and ribbed shell, to evaluate their efficiency in terms of material intensity, stiffness, and geometric behavior. Using Rhinoceros and Grasshopper environments with Karamba3D, Kiwi3D, and Kangaroo plugins, a comprehensive parametric workflow was developed that integrates geometric modeling, structural analysis, and material evaluation. The results show that segmented ribbed shell and two segmented gridshell variants offer up to 70% reduction in material usage compared with full-plate segmented timber shells, with hybrid timber shells achieving the best balance between stiffness and mass, offering functional advantages (roofing without additional load). These findings highlight the potential of parametric and computational design methods to enhance both the environmental efficiency (LCA) and digital fabrication readiness of timber-based architecture. The study contributes to the ongoing development of computational timber architecture, emphasizing the role of design-to-fabrication strategies in sustainable construction and the digital transformation of architectural practice.

Background/Objectives: Geometric morphometric analysis (GMA) is a statistical method that captures and quantifies shape variation. This study aimed to assess hard and soft tissue shape variations and changes following orthodontic treatment in Class III skeletal malocclusion using GMA. Methods: A retrospective study was conducted on 84 lateral cephalometric radiographs (pre-treatment and near-end treatment) of Class III patients aged 16-40 years (ANB < 2°). Thirty-five landmarks were digitized in Cartesian coordinates using MorphoJ software for shape analysis. Results: The sample included 62% females and 38% males, with a mean age of 24.7 ± 5.2 years. Vertical dimension variations (hypodivergent to hyperdivergent) contributed most to shape changes PC1 (23.35%), followed by anteroposterior variations PC2 (13.51%). Gender significantly influenced hard and soft tissue variation with 30.91%SS (F = 56.99, p < 0.0001). Males had significantly larger and longer ramus, body of the mandible, alveolar height, LAFH, TAFH and upper lip length. (PD: 0.026, p < 0.05). Significant shape changes were seen in the mandible (PD = 0.018, p < 0.05). SNB increased by 0.41° (from 81.73° ± 3.67°), and ANB improved by 0.46° but remained Class III (-0.33° ± 1.82°). Lower anterior facial height increased by 1.78 mm (p < 0.05). The lower incisors retroclined significantly (from 92° ± 8.56° to 87° ± 6.96°, p < 0.05), while the interincisal angle increased by 5.9°. Upper incisors remained procline (118° ± 11°, p > 0.05). Upper lip length increased by 0.4 mm (p < 0.05). Conclusions: Vertical and anteroposterior shape variations are notable within Class III malocclusion. Post-treatment changes in both hard and soft tissues indicate that orthodontic camouflage can enhance facial esthetics and skeletal balance. GMA provides objective quantification and visualization of these treatment-related craniofacial changes.

ABSTRACT Modern geometric techniques offer significant potential to uncover the worlds in which weapons were created, worlds shaped by specific environmental conditions and knowledge systems transmitted through established networks. We analysed the morphology of Mesolithic harpoon points from Eastern Middle Sweden to explore developments in craft and hunting techniques across the circum-Baltic Sea area, and to investigate if specific morphological traits are linked to regional environmental and faunal changes. We identified and separately analysed structural elements of the harpoon points, barbs, proximal and distal parts, and full-body silhouettes using geometric morphometrics and direct radiocarbon dating. Our results show that barb and proximal part shapes changed during the transition from the Early to the Middle Mesolithic in Eastern Middle Sweden which fits into broader superregional trends in craft and hunting techniques. In contrast, the width of the proximal part remained relatively stable throughout the Mesolithic, indicating continuity in regional crafting traditions and specific environmental conditions. The shapes of distal parts and full-body silhouettes correlate with the regional availability of large terrestrial prey. This study highlights the potential of geometric morphometric analysis to study morphological changes in harpoon points and to shed light on the multiple influences that shaped Mesolithic hunting weapons.

Pumpkin seedlings serve as rootstocks for watermelon grafting, and the partial leaf trimming operation performed approximately two days before grafting is crucial for the survival rate of grafted watermelon seedlings. Extracting the position of the main veins of the leaf is a prerequisite for achieving automated partial pruning. The existing methods have problems such as low segmentation accuracy and misclassification between primary and branch veins in the pumpkin seedling segmentation task. This study proposes a three-classification segmentation model Dynamic Region Enhancement Transformer (DRE-Former) of main vein, branch vein and background, as well as a post-processing system. The encoder of DRE-Former consists of two modules. The former is Dynamic Frequency Conv and Normalized Efficient Conv (DN Block), which can enhance the feature extraction ability for small targets. The latter is the Region Transformer Block, which enhances the ability to distinguish between the main vein and the branch vein. In addition, in the skip connection part of the model, a Skip Connection Fusion Block (SCF Block) has been added, which can reduce the dilution degree of detailed features. The post-processing section outputs the cutting position and cutting Angle through rule-based methods and geometric analysis. The experimental results show that the proposed model achieves mean Intersection-over-Union (mIoU) and Overall Accuracy (OA) of 90.80% and 95.88%, respectively, outperforming the comparative models. In stability and error testing, the average standard deviation is 0.60, and the average relative error is 11.90%. Compared with the primary mIoU data in the dataset, the average relative error differs by only 2.11%. The post-processing system enables the accurate determination of cutting positions and angles, but it has a strong dependence on the segmentation model. The research can provide reliable technical support for the subsequent automatic cutting equipment for pumpkin seedlings.

Loeys-Dietz syndrome is a rare connective tissue disorder characterized by life-threatening aortic aneurysm and distinctive craniofacial anomalies. It is caused by mutations along the transforming growth factor beta (TGF-β) signaling pathway (LDS1-6). We previously showed that craniofacial anomalies varied among LDS subtypes and that LDS2, caused by mutations in the TGFBR2 gene, exhibited the most severe and variable phenotype. In this study, we performed a thorough qualitative and quantitative analysis of craniofacial anomalies in a mouse model for LDS2, through micro computed tomography and 3D geometric morphometric analysis at multiple postnatal stages. We show that craniofacial shape in Tgfbr2G357W/+ mice strongly deviates from their WT littermates from an early age and exhibit high variability and evidence of left–right asymmetry despite the pure genetic background. Cranial doming, shortening of the anterior part of the skull, widening of the space between orbits, reduction of mandibular size, suture fusion in the cranial vault and palate, and abnormal condylar shape were among features that were consistent with the phenotype seen in patients with LDS. Interestingly, several of these features were more prevalent and severe in females than in males, indicating potential sexual dimorphism, further supported by the trend observed in our revisited clinical data.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-026-35325-8.

The lack of two active centers and simultaneous hydrogen evolution reaction (HER) restrict single-atom catalysts (SACs) to produce C2 products in CO reduction reaction (CORR)/CO2 reduction reaction (CO2RR). In this work, we propose SACs with a N-B neighborhood, which can obtain ethylene and ethanol as desired C2 products through CO2RR in the presence of CO gas. We have identified Fe, Co, Rh, and Ni (tested 28 systems) as possible active centers in MNxB SAC to produce a C2 product with limiting potential as low as -0.66 V (FeN3B) in CORR and CO/CO2RR. The ↓dyz orbital occupancy exhibited a significant correlation with Eb_CO-CO (R2 = 0.74), explaining the origin of CO-CO coupling on M-NxB systems. Further, we have provided geometrical analysis and σ-electron donation (CO) and π-electron back-donation (dyz) to understand why MNxB systems are suitable for producing C2 products. This study opens the possibility of a future investigation in SAC for C2 products in CORR beyond Cu.

ABSTRACT Emerging forms of spatial data, such as sensor-based location data collected by mobile apps (MPD), have shown promise in enhancing or replacing traditional analytical methods. MPD provides detailed and timely information at lower costs, making it valuable for urban and transport planning. Multi-source MPD also offers advantages, such as greater representativeness. However, the high volume, variable frequency, and heterogeneity pose significant challenges in data processing and analysis. This study investigates the potential of multi-source MPD to estimate traffic volumes at the street level, focusing on Glasgow city-region. The evaluation covers a range of processing approach combinations. These include three MPD spatial extraction techniques —Simple Buffer (SB), Connected Street Buffer (CB), and Entire Street Buffer (ESB) —to filter relevant vehicular movement data. Additionally, four processing approaches are considered: raw counts (A1), simplified counts with commuter assumptions (A2), detailed geometric analysis (A3), and map matching (A4). The results are compared to manual traffic counts from the Department for Transport (DfT). The findings reveal that raw MPD counts (A1) lead to important biases due to uneven data volume per user. Simplified counts (A2) improve accuracy but still capture non-vehicular activities. Map matching (A4) introduces substantial improvements compared to A1 and A2. However, this approach proves less effective than A3. The geometric-temporal approach (A3) offers the most accurate estimates by incorporating movement inferences. Buffer size and built environment factors influence the methods’ performance, highlighting the need for localised buffers and built environmental controls. This research finds moderate potential for multi-source MPD to supplement traditional traffic systems, providing cost-effective and detailed traffic insights at least from a spatial variability perspective, but not for cross-temporal comparisons. Future studies can extend MPD applications for active travel and extend the analysis to other cities.

In this work, we present the design of a prototype fluid analyzer based on photon sieves, permeable diffractive optical elements capable of focusing light through diffraction. The photon sieve comprises a spatial distribution of circular apertures patterned onto an aluminum substrate, which provides intrinsic fluid permeability and functions as either a lens or a mirror. In our approach, the aluminum surface is chemically functionalized to detect a specific biomolecular marker—human serum albumin—whose interaction with the surface induces measurable changes in the spectral reflectance. The operating wavelength is selected to maximize the reflectance contrast produced by the presence of the biomarker. The optical set-up is configured such that the light source and detector lie in the same plane when the photon sieve operates in reflection. A combined geometrical and diffractive analysis is conducted to optimize their positions. Upon detection of the biomarker, the measured signal decreases to 0.43 of its initial value prior to biomarker binding. These results highlight photon sieves as a promising platform for the development of compact, lightweight, and low-cost optical chemical sensors for running fluids.

Procyanidins, a class of substances widely distributed in nature, have attracted the attention of the scientific community due to their bioactive properties, especially with regard to human health. This review is based on an extensive examination of peer-reviewed literature, patents, and clinical trial reports published between 2005 and 2025. From an initial pool of more than 300 documents, 283 studies were selected according to criteria of scientific rigor, methodological clarity, and relevance to the research objectives. A literature search was performed using PubMed, PubChem, Google Scholar, Scopus and ResearchGate employing keywords such as Procyanidins, chemical structure, extraction, and health effects. This article provides a comprehensive overview of current methods for obtaining these compounds, which include both natural sources and synthetic approaches. It provides a concise summary of the molecular structure of procyanidins and emphasizes the importance of understanding their conformational features for predicting biological activity. The challenges of establishing correlations between the structural features of procyanidins and their properties are described. In addition, this article explores the many potential applications of these compounds, spanning both biochemistry and the field of design and synthesis of novel materials. This review provides a comprehensive evaluation of Procyanidins, focusing on their geometrical conformation analysis through advanced NMR spectroscopy techniques including homonuclear correlation (COSY, TOCSY), heteronuclear one-bond (HSQC, HMQC), multiple-bond (HMBC) experiments, and through-space correlation (NOESY) in conjunction with various extraction methodologies.

A novel landmark-based morphometric approach for sequencing typical thoracic vertebrae.

The effective method for eliminating the Moiré fringes in the MC nanoprecipitates in the austenite matrix was studied. Considering the dynamic diffraction between the matrix and precipitate, the spots originating from the Moiré pattern were selected in the fast Fourier transform (FFT) pattern. The Moiré fringe image was extracted by performing inverse FFT(IFFT) of the selected spots. Subtracting the Moiré fringe contribution from the original image intensity reveals the veiled lattice fringes of MC carbide in the austenite matrix. The image was compared and discussed with the IFFT image of the direct selection of the matrix + MC FFT patterns. The suggested method was applied to strain measurement in the MC carbide-containing area using the geometrical phase analysis. Compared with the result obtained from the raw image containing Moiré fringes, the applied method shows artifact-free strain distribution in the MC carbide. The process was applied to the inclined twin interface in BCC steel. The lattice fringe in the overlapping area shows a more detailed lattice feature. This novel study sheds light on the veiled crystal structure and strain distribution under various conditions where more than two lattice fringes overlap.

The formation of nanoscale bubbles is an unavoidable consequence during the transfer of 2D materials onto target substrates, driven by van der Waals interactions at the interface. While often viewed as imperfections, these nanoscale bubbles have garnered considerable scientific interest due to the substantial in-plane strain gradients they induce, which in turn give rise to a variety of intriguing optoelectronic effects, particularly in semiconducting transition metal dichalcogenides. Determining and analyzing the strain distribution within nanobubbles at the nanoscale are crucial for advancing our understanding of these underlying strain-induced effects. Here, we present a high-resolution scanning tunneling microscopy-based tip-enhanced Raman spectroscopic investigation of localized nanoscale strain distribution within the nanobubbles formed between monolayer MoS2 and Au interface. By employing cryogenic temperature (78 K), we successfully differentiate the nanoscale Raman signatures between the nanobubble edge and pristine MoS2. We verify a maximum tensile strain of ∼1.15-1.34% at the nanobubble edge, which gradually diminishes toward the center, yielding a cross-sectional strain profile consistent with a doughnut-shaped distribution. Furthermore, we report to achieve ∼5 nm spatial resolution in probing such edge-localized strain within the nanobubble. In addition, comparative average strain analysis of such MoS2 nanobubbles is conducted via geometric mechanistic analysis, such as membrane and nonlinear plate theories, providing key insight into the geometric nature near the bubble edge. Our findings provide fundamental information about strain-induced nanoscale chemical understanding of 2D materials on the nanometer scale, paving the way for practical applications of nanobubbles in strain-engineered optoelectronic devices.