Search Results (744)

This paper presents a strategy to mitigate electromagnetic noise in induction motors for electric vehicles by optimizing the rotor slot count and skewing distance. Initially, the magnetomotive forces (MMF) of the stator and rotor windings, air-gap permeance, and the predominant radial electromagnetic force waves in the air-gap magnetic field were analytically determined and compiled. A finite element model of the original 36/42 straight-slot configuration was established for simulation validation. Subsequently, a preliminary optimization scheme for rotor slot number was proposed. A systematic analysis was conducted of the circumferential distribution of radial force waves and their harmonic components in both temporal and spatial orders by comparing electromagnetic vibration characteristics across different rotor slot configurations (42 versus 53 slots) using two-dimensional Fourier decomposition. Furthermore, building upon the mechanism of tooth harmonic suppression via rotor skewing, an advanced optimization strategy for skewing distance was developed. Comparative analysis of harmonic content in air-gap flux density under three configurations (straight slot, 1.0× skewing, and 1.2× skewing) revealed the optimal solution. Experimental vibration tests demonstrated significant improvements: the optimized 53-slot rotor with 1.2× skewing reduced vibration amplitudes by 5 dB·Hz at the 2nd-order natural frequency, 5 dB·Hz at the 3rd-order natural frequency, and 18 dB·Hz at the 3rd-order resonance peak compared to the original 42-slot straight-slot design. These results confirm that coordinated optimization of rotor slot number and skewing distance effectively mitigates electromagnetic vibration and noise in traction motors. Full article

Soil heavy metal contamination poses a serious threat to soil ecosystems and human health. Geochemistry is often used in soil heavy metal contamination research to identify pollution sources, identify elemental cycling mechanisms, and assess the spatial distribution and risk of contamination. However, it is difficult to directly reflect the spatial continuity and deep distribution patterns of contamination. Three-dimensional electrical resistivity tomography (3D ERT) technology often indirectly predicts the distribution of soil contamination by leveraging the electrical structure of the subsurface medium. However, many factors influence this electrical structure, leading to biased predictions. This paper combines geochemistry with 3D ERT technology. A nonlinear statistical model is established based on the geochemical analysis results and resistivity of soil samples. A 3D ERT model is then constructed. This model is used to further investigate the spatial distribution patterns of soil heavy metal contamination and assess the extent of contamination. This study investigated soil sample collection and chemical analysis of heavy metal content at a heavy metal contaminated site in Hunan Province. Antimony contamination was particularly severe in the soil. The 3D ERT data collection and inversion imaging were performed in the soil sample collection area. A 3D ERT model was established to analyze and evaluate the distribution range and extent of antimony contamination in the area. Comparing the antimony content predicted by the model with the actual test data, the results show that the error range is 0.6–16.6%, and the average error is 5.8%. The model has high accuracy, achieving good overall prediction and evaluation results. Full article

We present a hybrid partial differential equation-agent-based model (PDE-ABM). In our framework, tumor cells secrete tumor angiogenic factor (TAF), while endothelial cells chemotactically migrate and branch in response. Reaction–diffusion PDEs for TAF, oxygen, and cytotoxic drug are coupled to discrete stochastic dynamics of tumor cells and endothelial tip cells, ensuring multiscale integration. Motivated by observed perfusion heterogeneity in tumors and its pharmacokinetic consequences, we conduct a linear stability analysis for a reduced endothelial–TAF reaction–diffusion subsystem and derive an explicit finite-domain threshold for Turing instability. We demonstrate that bidirectional coupling, where endothelial cells both chemotactically migrate along TAF gradients and secrete TAF, is necessary and sufficient to generate spatially periodic vascular clusters and inter-cluster hypoxic regions. These emergent patterns produce heterogeneous drug penetration and resistant niches. Our results identify TAF clearance, chemotactic sensitivity, and endothelial motility as effective levers to homogenize perfusion. The model is two-dimensional and employs simplified kinetics, and we outline necessary extensions to three dimensions and saturable kinetics required for quantitative calibration. The study links reaction–diffusion mechanisms with clinical principles and suggests actionable strategies to mitigate resistance by targeting endothelial–TAF feedback. Full article

The mammalian skull, which surrounds and protects the brain, is one of the most morphologically diverse and functionally important structures in the vertebrate body. As one of the most ecologically diverse mammals, the developmental dynamics of morphological and structural changes and functional diversity in the skull of bats need to be revealed. Here, we focused on the developmental characteristics of the Vespertilio sinensis skull, and used statistical analysis, spatial morphology visualization, and comparative analysis of the Stretch Factors (SF) of the masticatory muscles to better understand the connection between the morphology of the skull and the development of the body size during the developmental process of V. sinensis, the changes in the three-dimensional (3D) spatial morphology and structure, and the correlations between opening capacity and the transformation of feeding habits. This study not only provides a new perspective for understanding the morphological adaptive mechanism of ecological niche expansion that accompanies the transition of mammalian skulls from juvenile to adult feeding but also provides a crucial scientific basis for an in-depth understanding of the growth and developmental mechanism of bats’ skull and even vertebrates as a whole, which is potentially useful for the development of ecological conservation and evolutionary biology. Full article

Precise estimate of antenna location is essential for high-quality three-dimensional (3D) radar imaging, especially under sparse sampling schemes. In scenarios involving synchronized scanning and rotational motion, small deviations in the radar’s transmitting position can lead to significant phase errors, thereby degrading image fidelity or even causing image failure. To address this challenge, we propose a novel trajectory estimation method based on microwave three-point ranging. The method utilizes three fixed microwave-reflective calibration spheres positioned outside the imaging scene. By measuring the one-dimensional radial distances between the radar and each of the three spheres, and geometrically constructing three intersecting spheres in space, the radar’s spatial position can be uniquely determined at each sampling moment. This external reference-based localization scheme significantly reduces positioning errors without requiring precise synchronization control between scanning and rotation. Furthermore, the proposed approach enhances the robustness and flexibility of sparse sampling strategies in near-field radar imaging. Beyond ground-based setups, the method also holds promise for drone-borne 3D imaging applications, enabling accurate localization of onboard radar systems during flight. Simulation results and error analysis demonstrate that the proposed method improves trajectory accuracy and supports high-fidelity 3D reconstruction under non-ideal sampling conditions. Full article

This study introduces the Historic Urban Landscape (HUL) approach into a rural setting and conducts a case study of Huaqiu Village. By integrating spatial analysis techniques, unmanned vehicle aerial photography, field surveys, and multitemporal data from 2000 to 2023, this study analyzed the heritage value of traditional villages and explored a rural-adaptable pathway for HUL implementation. Findings showed: 1. Based on the temporal and spatial evaluation analysis logic of landscapes under the HUL framework, spatial patterns of the village, such as vegetation growth and reduced in water bodies, have been quantitatively identified, revealing the interaction patterns of a complex ecosystem. 2. Following HUL’s holistic understanding of heritage value, the three-dimensional value characteristics of the village (landscape, function, and spirit) are clarified. 3. By implementing the community participation mechanism of HUL, through villager-led inheritance of intangible cultural heritage and joint formulation of conservation conventions, the living continuity of heritage has been realized. The HUL approach shows remarkable adaptability, with prominent achievements in dynamic-layered protection and community participation. This study breaks through the urban bias of the HUL approach, enriches understanding of rural heritage, and provides a practical paradigm for promoting sustainable development of similar villages. Full article

Ankle-foot orthoses (AFOs) are widely used to improve gait; nonetheless, it remains unclear how specific settings, particularly the dorsiflexion angle, affect gait kinematics in individuals with stroke. This study investigated the effect of different AFO dorsiflexion angles on gait kinematics in ambulatory adults with hemiparesis. Twenty-six individuals with post-stroke hemiparesis walked on a treadmill while wearing the same type of AFO at four ankle dorsiflexion angles: 0°, 5°, 10°, and 15°. Temporal-spatial variables, joint angles, and toe clearance and its components were quantified using three-dimensional analysis. The double-stance time before the paretic swing shortened significantly with increasing dorsiflexion angle, whereas the mean stride time and length did not significantly change. During the swing phase, increased AFO dorsiflexion was associated with reduced maximal knee flexion, in addition to its direct effect on ankle angles. The absolute toe clearance height was unaffected by the AFO settings; however, the contribution of ankle dorsiflexion to limb shortening increased stepwise from 0° to 15°, and the hip elevation and compensatory movement ratio declined. In conclusion, increasing the AFO dorsiflexion angle significantly altered gait kinematics, with distal ankle mechanics replacing inefficient hip compensation and reducing double-stance time. Full article

Under the framework of the “dual carbon” goals, promoting the coordinated development of carbon emission efficiency, carbon sink capacity, and high-quality growth has become a critical issue for regional sustainability. Using panel data from 2006 to 2021, this study systematically investigates the three-dimensional coupling coordination among carbon emission efficiency, carbon sink capacity, and high-quality development in the Greater Chang-Zhu-Tan urban agglomeration. The spatiotemporal evolution, spatial correlation characteristics, and influencing factors of the coupling coordination were also explored. The results indicate that the coupling coordination system exhibits an evolutionary trend of overall stability with localized differentiation. The overall coupling degree remains in the “running-in” stage, while the coordination level is still in a marginally coordinated state. Spatially, the pattern has shifted from “northern leadership” to “multi-polar support,” with Yueyang achieving intermediate coordination, four cities including Changde reaching primary coordination, and three cities including Loudi remaining imbalanced. Spatial correlation has weakened from significant to insignificant, with Xiangtan showing a “low–low” cluster and Hengyang displaying a “high–low” cluster. The evolution of hot and cold spots has moved from marked differentiation to a more balanced distribution, as reflected by the disappearance of cold spots. The empirical analysis confirms a three-dimensional coupling mechanism: ecologically rich regions attain high coordination through carbon sink synergies; economically advanced areas achieve decoupling through innovation-driven development; while traditional industrial cities, despite facing the “green paradox,” demonstrate potential for leapfrog progress through transformation. Among the influencing factors, industrial structure upgrading emerged as the primary driver of spatial differentiation, though with a negative impact. Government support also exhibited a negative effect, whereas the interaction between environmental regulation and both government support and economic development was found to be significant. Full article

Accurate load profile identification is crucial for effective and sustainable power system planning. This study proposes a characterization methodology based on clustering techniques applied to consumption data from medium- and low-voltage users, as well as distribution transformers from an electric utility. Three algorithms—K-means, DBSCAN (Density-Based Spatial Clustering of Applications with Noise), and Gaussian Mixture Models (GMM)—were implemented and compared in terms of their ability to form representative strata using variables such as observation count, projected energy, load factor ($LF$), and characteristic power levels. The methodology includes data cleaning, normalization, dimensionality reduction, and quality metric analysis to ensure cluster consistency. Results were benchmarked against a prior study conducted by Empresa Eléctrica Regional Centro Sur C.A. (EERCS). Among the evaluated algorithms, GMM demonstrated superior performance in modeling irregular consumption patterns and probabilistically assigning observations, resulting in more coherent and representative segmentations. The resulting clusters exhibited an average $LF$ of 58.82%, indicating balanced demand distribution and operational consistency across the groups. Compared to alternative clustering techniques, GMM demonstrated advantages in capturing heterogeneous consumption patterns, adapting to irregular load behaviors, and identifying emerging user segments such as induction-cooking households. These characteristics arise from its probabilistic nature, which provides greater flexibility in cluster formation and robustness in the presence of variability. Therefore, the findings highlight the suitability of GMM for real-world applications where representativeness, efficiency, and cluster stability are essential. The proposed methodology supports improved transformer sizing, more precise technical loss assessments, and better demand forecasting. Periodic application and integration with predictive models and smart grid technologies are recommended to enhance strategic and operational decision-making, ultimately supporting the transition toward smarter and more resilient power distribution systems. Full article

Photogrammetry offers a non-contact and efficient alternative for monitoring structural deformation and is particularly suited to large or complex surfaces such as masonry walls. This study proposes a spatio-temporal photogrammetric refinement framework that enhances the accuracy of three-dimensional (3D) deformation and strain analysis by integrating advanced filtering techniques into markerless image-based measurement workflows. A hybrid methodology was developed using natural image features extracted using the Speeded-Up Robust Features algorithm and refined through a three-stage filtering process: median absolute deviation filtering, Gaussian smoothing, and representative point selection. These techniques significantly mitigated the influence of noise and outliers on deformation and strain analysis. Comparative experiments using both manually placed targets and automatically extracted feature points on a full-scale masonry wall under destructive loading demonstrated that the proposed spatio-temporal filtering effectively improves the consistency of displacement and strain fields, achieving results comparable to traditional marker-based methods. Validation against laser rangefinder measurements confirmed sub-millimeter accuracy in displacement estimates. Additionally, strain analysis based on filtered data captured crack evolution patterns and spatial deformation behavior. Therefore, integrating photogrammetric 3D point tracking with spatio-temporal refinement provides a practical, accurate, and scalable approach to monitor structural deformation in civil engineering applications. Full article

Traffic crashes remain a critical public safety issue and are among the leading causes of mortality worldwide. Understanding, analyzing, and forecasting crash trends are essential for implementing effective countermeasures and reducing injury severity. In response to the growing number of crashes and their associated economic and social costs, this study presents a geospatial analytical framework for prioritizing and classifying roadway segments based on crash trends. The framework focuses on a major freeway corridor in the United States, covering a four-year period across 20 counties. This methodology employs spatiotemporal analysis, which integrates both spatial (geographic) and temporal (time-based) dimensions to better understand how crash patterns evolve over time and space. A central component of the analysis is Space–Time Cube (STC) modeling, a three-dimensional GIS-based visualization, and an analytical approach that organizes data into spatial locations (x and y) across a sequence of temporal bins (z-axis) to reveal patterns that may not be evident in a two-dimensional analysis. Additionally, emerging pattern analysis, specifically Emerging Hotspot Analysis (EHA), is used to identify statistically significant trends in crash frequency over time. The results indicate a significant spatial clustering of crashes, with high-risk segments predominantly located in densely populated urban areas with high traffic volumes. Crash hotspots were classified into five distinct categories: persistent, intensifying, new, sporadic, and diminishing, enabling transportation agencies to tailor interventions based on temporal dynamics. The proposed geospatial framework enhances decision making for roadway safety improvements and can be adapted for use in other regional corridors to support infrastructure investment and advance public safety. Full article

Electromagnetic Railguns Face Severe Ablation and Melting Risks Due to Extremely High Transient Thermal Loads During High-Speed Launching, Directly Impacting Launch Reliability and Service Life. To address this thermal management challenge, this study proposes and validates the effectiveness of spray cooling technology. Leveraging its high heat transfer coefficient, exceptional critical heat flux (CHF) carrying capacity, and strong transient cooling characteristics, it is particularly suitable for the unsteady thermal control during the initial launch phase. An experimental platform was established, and a three-dimensional numerical model was developed to systematically analyze the dynamic influence mechanisms of nozzle inlet pressure, flow rate, spray angle, and spray distance on cooling performance. Experimental results indicate that the system achieves maximum critical heat flux (CHF) and rail temperature drop at an inlet pressure of 0.5 MPa and a spray angle of 0°. Numerical simulations further reveal that a 45° spray cone angle simultaneously achieves the maximum temperature drop and optimal wall temperature uniformity. Key parameter sensitivity analysis demonstrates that while increasing spray distance leads to larger droplet diameters, the minimal droplet velocity decay combined with a significant increase in overall momentum markedly enhances convective heat transfer efficiency. Concurrently, increasing spray distance effectively improves rail surface temperature uniformity by optimizing the spatial distribution of droplet size and velocity. Full article

Exercise-induced fatigue can degrade athletic performance and increase injury risk, yet traditional fatigue assessments often rely on subjective measures. This study proposes an objective fatigue recognition approach using high-fidelity motion capture data and deep learning. This study induced both cognitive and physical fatigue in 50 male participants through a dual task (mental challenge followed by intense exercise) and collected three-dimensional lower-limb joint kinematics and kinetics during vertical jumps. A bidirectional Gate Recurrent Unit (GRU) with an attention mechanism (BiGRU + Attention) was trained to classify pre- vs. post-fatigue states. Five-fold cross-validation was employed for within-sample evaluation, and attention weight analysis provided insight into key fatigue-related movement phases. The BiGRU + Attention model achieved superior performance with 92% classification accuracy and an Area Under Curve (AUC) of 96%, significantly outperforming the single-layer GRU baseline (85% accuracy, AUC 92%). It also exhibited higher recall and fewer missed detections of fatigue. The attention mechanism highlighted critical moments (end of countermovement and landing) associated with fatigue-induced biomechanical changes, enhancing model interpretability. This study collects spatial data and biomechanical data during movement, and uses a bidirectional Gate Recurrent Unit (GRU) model with an attention mechanism to distinguish between non-fatigue states and fatigue states involving both physical and psychological aspects, which holds certain pioneering significance in the field of fatigue state identification. This study lays the foundation for real-time fatigue monitoring systems in sports and rehabilitation, enabling timely interventions to prevent performance decline and injury. Full article

Whole genome doubling (WGD) triggers profound genomic and epigenetic reorganization, yet the functional dynamics of DNA methylation during this process remain incompletely resolved. Here, we integrate whole genome bisulfite sequencing (WGBS) and three-dimensional chromatin interaction data to display methylation landscapes in autotetraploid Arabidopsis thaliana. Our analysis reveals evolutionarily conserved spatial patterning of DNA methylation after WGD, with centromeric enrichment and telomeric depletion. Chromosome-level profiling identifies Chromosome 2 as the most highly methylated across CG, CHG, and CHH contexts, while Chromosome 1 shows the lowest methylation. Subcontext methylation analysis uncovers increases in methylation levels in autotetraploid Arabidopsis thaliana, most pronounced in the CHH context, yet global distribution patterns remain stable. Comparative methylation profiling around genes and transposable elements (TEs) reveals elevated CHH methylation in autotetraploid gene bodies and flanking regions, whereas TE bodies exhibit minimal changes despite minor flanking hypermethylation. Strikingly, 8% of chromatin compartments were restructured, and B-B interactions weakened in autotetraploid, while DNA methylation remained stable across shifting A/B compartments. Our findings suggest that DNA methylation serves as a resilient epigenetic modification during WGD, even if 3D chromatin architecture undergoes reorganization upon WGD in some degree. Full article

With the increasing importance of urban green spaces in leisure, ecology, emergency management, and other functions, urban forest parks play a key role in enhancing urban tourism resilience. Tourists are closely related to this, but current research lacks discussion on the sustainable development of urban forests and tourism resilience from the perspective of tourist demand. Therefore, this study took Kunming Xishan Forest Park as an example, conducted a questionnaire survey of 385 tourists, and identified tourist demands and weights through in-depth analysis using the KANO model and AHP. The results data show that among the 23 demand indicators across five dimensions, six are must-be qualities, eight are one-dimensional qualities, six are attractive qualities, and three are indifferent qualities. Based on the AHP analysis, we further investigated the weight of each demand indicator. The results of this study not only provide practical support and strategic guidance for the spatial planning and design of urban forests, thereby enhancing the sustainable development of urban tourism resilience, but also contribute to theories of urban tourism resilience and offer a reference source for other cities with similar aspirations. Full article