Search Results (72)

This study devised a blasting experiment to establish a dynamic quantified relationship between blasting and movement, failure, and ejection of rock masses. The experiment was conducted using the 3D digital image correlation method (3D-DIC), which provided high-speed images capturing the process of shallow-buried tunnel blasting. The study analyzed the mechanical behavior of full-section rock mass under blasting action through cross-scale image processing. Yield and elastic points were distinguished based on the time–displacement curve. Then, the spatial vector method was employed to deduce flying rock trajectory and throwing distance, enabling the subdivision of underground space based on risk assessment. The results show that the rock in the cut zone starts moving within 3 ms after initiation, ultimately exhibiting a maximum visible off-plane displacement of 215 mm. Displacements are related to delay time and distance. Different zones show distinct dominant directions of rock mass displacement. The rock mass becomes flying rocks separated from the cross-section. The initial velocity of the flying rocks ranges from 11.8 m·s⁻¹ to 29.9 m·s⁻¹. Around 85% of the flying rocks fall within the range of 0 to 40.8 m. Only 5% of the flying rocks fall outside 64.3 m. Appropriate protective measures should be taken for equipment during experiments. Full article

Commercial plots in hot–humid tropical island cities require effective pedestrian-level ventilation; however, the extent to which different layout forms enhance wind-driven cooling potential under fixed development intensity remains insufficiently quantified. Taking Haikou as a representative tropical island case, this study examines how building count and spatial enclosure form affect the pedestrian-level wind environment of a commercial plot. A total of 63 layouts with one, two, and three building units were constructed under identical development constraints. ANSYS Fluent 2023 R1 (ANSYS, Inc., Canonsburg, PA, USA). was used to simulate pedestrian-level wind fields under representative summer southerly and east–northeasterly (ENE) wind conditions. Six ventilation-related indicators, including area-weighted mean wind speed, maximum wind speed, and the non-low-wind-speed area ratio in both seasons, were integrated into a Wind-Driven Cooling Potential Index (WDCPI). The weighting scheme combined climate-informed seasonal weights with entropy-based objective indicator weights. The results show that summer ventilation is more sensitive to layout form than winter ventilation. Although the average WDCPI decreases as building subdivision increases, layout B2 shows the highest WDCPI among the tested scenarios because its open inter-building space forms a continuous ventilation path aligned with the prevailing summer wind. The sensitivity analysis supports the relative stability of the ranking results. These findings highlight airflow connectivity and windward openness as important layout-screening principles for cooling-oriented commercial plot design in tropical island cities. Full article

Lightweight polylactic acid (PLA LW) is a thermally activated foaming filament in which print temperature governs the extent of in situ gas expansion. This dual role, as a microstructural design parameter and a primary source of performance variability, motivates the three-phase, multi-factorial experimental program reported here. FDM-printed specimens of three infill topologies were investigated: orthogonal Cubic, hierarchical Subdivision Cubic (Sub-Cubic), and Gyroid triply periodic minimal surface (TPMS), each representing a distinct crystallographic symmetry class. A total of 504 specimens were fabricated across eight print temperatures (190–260 °C), three flow rate settings (70%, 80%, 100%), and four infill ratios (10%, 20%, 40%, 60%) and tested under quasi-static tensile and Charpy impact loading, with six replicates per condition distributed across two independent batches. One-way ANOVA confirmed a strong temperature effect on ultimate tensile strength (UTS) in Phase 1 (F(7,40) = 22.37, p < 0.001), while the Gyroid is uniquely temperature-sensitive in Phase 2 at 70% flow rate (F(1,8) = 14.30, p = 0.005) compared to the Cubic and Sub-Cubic, which exhibit no significant temperature effect in the 230–240 °C window. The Gyroid at 240 °C and 70% flow rate achieved the highest specific strength among Phase 2 configurations (20.9 MPa·cm³/g); Phase 3 demonstrated that Gyroid-specific strength decreases monotonically with the infill ratio, reaching 15.4, 12.3, and 8.8 MPa·cm³/g at 10%, 40%, and 60% infill, respectively. Cubic infill at 230 °C and 80% flow rate delivered the most reproducible performance (CV_UTS = 3.3%), while Sub-Cubic at the same condition combined high specific strength (20.5 MPa·cm³/g) with low variability (CV_UTS = 4.3%); both observations are quantified through a symmetry robustness index and a symmetry consistency indicator. Macrographic fractography supported geometry-controlled fracture: Cubic specimens fracture along layer interface mirror planes or ±45° shear planes depending on the thermal regime, while Gyroid specimens exhibit multi-plane, curvature-deflected fracture with no preferred crack propagation direction. These results indicate that geometric symmetry class is an important organizing factor for the mechanical response of FDM-printed PLA LW structures within the investigated parameter space. Full article

Modern indoor spaces increasingly contain curved walls, slanted surfaces, nested rooms and other non-Manhattan structures, making room-level subdivision from 3D point clouds challenging. Existing projection-based, primitive-based and semantic methods often rely on Manhattan assumptions, explicit structural labels or local geometric heuristics, which may lead to fragmented spatial units and unstable boundaries in complex scenes. Here, we propose a topology-driven voxel partitioning framework that reformulates indoor space subdivision as controlled connectivity disconnection within a topological closure. The central idea is to first construct a closed voxelated space domain and then selectively disconnect it at near functional openings and topological bottlenecks, rather than partitioning space only from local geometric cues. Within this framework, classical operations are reorganized under topological constraints as follows: adaptive region growing with aperture-sensitive spherical kernels generates initial spatial units, boundary-anisotropic watershed completion restores unlabeled boundary regions within interior domain, and label reassignment regularizes shared interfaces by minimizing discrete contact areas. Experiments on real-world and synthetic datasets show that the method produces stable room-level subdivisions across most Manhattan and non-Manhattan scenes. Cases with narrow bottlenecks or abrupt geometric narrowing still reduce detection-level precision and recall, indicating remaining limitations in highly constrained spatial configurations. Overall, the proposed framework offers a useful topological modeling perspective for indoor space subdivision in complex non-Manhattan environments. Full article

Lead isotope ratios are frequently used in archaeometric provenance analysis; however, the overlap of isotopic fields within the Andean metallogenic belt complicates reliable provenance determination. This study presents a reproducible fidelity-based kernel method for the unsupervised clustering of Andean lead-isotope data and investigates whether a quantum-mechanical similarity space can reveal geologically significant structures beyond the classical Euclidean partition. A dataset of 1522 measurements of ²⁰⁶Pb/²⁰⁴Pb, ²⁰⁷Pb/²⁰⁴Pb, and ²⁰⁸Pb/²⁰⁴Pb was analyzed using a fidelity-based quantum kernel based on a three-qubit Pauli feature map and compared with classical K-means clustering, Gaussian mixture models, and Ward’s agglomerative clustering under various preprocessing strategies and cluster counts. The optimal quantum kernel setup achieved the highest silhouette score at k = 2. However, because analytical uncertainties were not consistently reported across all the compiled sources, an uncertainty-weighted similarity could not be applied. Geological insights indicate that this binary division separates less radiogenic, arc-related compositions from more radiogenic and thorogenic crustal signatures, a contrast that broadly follows the west-to-east crustal-contamination gradient across the Andes. Conversely, the traditional four-cluster approach provides more detailed subdivisions that align with the previously identified isotopic provinces. The reported separation reflects the geometry of the quantum feature space rather than any hardware-level speed-up, as this work represents only a simulation approach. Overall, these findings support a hierarchical and complementary approach to analyzing Pb isotope origins, in which quantum kernel clustering provides robust large-scale separation and classical clustering enhances regional understanding. Full article

The entorhinal cortex (EC) is a central structure of the medial temporal lobe, functioning as the main cortical gateway to the hippocampus (HPC) and playing a crucial role in memory, spatial navigation, and temporal representation. This review outlines the distinct yet complementary contributions of its two main subdivisions, the medial (MEC) and lateral (LEC) entorhinal cortices. Despite being historically viewed as functionally segregated, they operate instead in close coordination to support the encoding and retrieval of multidimensional experiences. While the MEC is prominently involved in mapping spatial relationships and movement through specialized cell populations, and the LEC in processing object-related and contextual information, growing evidence shows substantial integration between these domains, challenging strict dichotomies. The MEC encodes elapsed time through persistent firing and time cell sequences, while the LEC signals temporal context via rate remapping; their convergent projections to the hippocampus enable the formation of temporally structured episodic memories. The review assesses recent findings on memory, navigation, and time processing, and highlights how the EC supports each through its layered architecture, local microcircuitry, and widespread interactions with HPC, cortical, and subcortical networks. Moreover, alterations in EC activity patterns emerge as the earliest signs of pathologies such as Alzheimer’s disease and temporal lobe epilepsy. Altogether, this review offers an up-to-date view of the EC not as a set of parallel modules, but as a highly interactive and dynamic system essential for structuring experience across space, time, and context. Full article

Informal urban settlements grow through incremental and adaptive processes, yet the temporal logic through which their access networks emerge, endure, and consolidate has received relatively little systematic attention. This paper examines the configurational development of the access network in Likoni, Mombasa, where rapid informal urbanisation has transformed an area containing only sparse footpaths into a dense urban network over two decades. Using historical satellite imagery, the study mapped five temporal states of access network for 2006, 2011, 2016, 2021, and 2026. The study utilises Space Syntax angular segment analysis. The analysis combines measures of angular connectivity, segment length, global and local integration, global and local choice, intelligibility, and synergy. The study aims to address three main questions: whether early informal footpaths persisted as the structural basis of later development of access network, whether subsequent growth strengthened local or global accessibility, and whether densification improved the overall configurational accessibility and legibility of the system as a whole. The results indicate that a finer-grained and more locally integrated network was produced through subdivision, densification, and the multiplication of short connecting segments. However, the gains were uneven across scales. Global integration and choice remained concentrated along a limited set of inherited and edge-related corridors, while local integration and local choice spread more widely through the settlement. The paper argues that the development of Likoni is a process of selective consolidation. Early footpaths became a persistent movement skeleton, forming the subsequent major paths of the later stages of the settlement. Later growth intensified local accessibility—albeit, as demonstrated through Space Syntax analysis rather than direct observation of movement—without necessarily producing notable improvements in global integration or whole-system configurational intelligibility. This finding adds a temporal and syntactic dimension to the understanding of informal morphogenesis. Full article

In many non-tourism historical districts in China, property division has subdivided traditional dwellings into multi-household units. While such subdivision reshapes spatial sequences and connections, its consequences for everyday space use and circulation are rarely documented with continuous in situ evidence, partly because residential behaviour is temporally continuous and difficult to observe directly. This study examines two typical subdivision patterns in Subu Old Street: a longitudinal, single-axis serial dwelling (Case A) and a transversal, courtyard-centred dwelling (Case B). We formalize spatial units, connections, and operational nodes using a semantic ontology and map day-long Ultra-Wideband (UWB) trajectories to quantify occupancy and transition characteristics. Case A concentrates both staying and passing at the entrance-end kitchen, where activities overlap with through-movements and transition durations are short in most events but highly volatile with a long tail. Case B channels most transitions through the courtyard hub, keeping indoor rooms mainly for staying and producing longer but more stable transition durations. This study is positioned as a comparative exploratory case study of two representative subdivision patterns identified in Subu Old Street. Semantic ontology modelling, UWB-based behavioural tracking, and behavioural indicators are used together in a comparative analytical approach for examining how subdivision reorganises spatial structure and everyday residential behaviour. The results reveal pattern-specific differences in occupancy concentration, transition organisation, and movement duration. These findings are analytical observations derived from two representative cases. They provide a basis for spatial adjustment and micro-regeneration in still-inhabited subdivided traditional dwellings. Full article

In an era of rapid urbanisation and climate challenges, understanding how urban land patterns contribute to resilience is crucial for sustainable development. This theoretical review introduces a novel framework positing that greater heterogeneity in plot sizes and land uses enhances urban resilience by promoting the long-term preservation of built environments, multifunctional spaces, and socio-cultural adaptability. Drawing on urban morphology, assemblage theory, and resilience science, we argue that fragmented ownership in small-plot fabrics acts as a barrier to large-scale redevelopment, fostering diversity that buffers against shocks. Through comparative case studies of Venice (Italy), Tokyo (Japan), Hong Kong, Mexico City (Mexico), and York (UK), we illustrate how historical small-plot subdivisions have endured centuries, supporting ecological, economic, and social sustainability. The analysis reveals common patterns: ownership fragmentation preserves fine-grained urban forms, enabling adaptive reuse (exaptation) and inclusivity. The five case studies serve an illustrative function, demonstrating how the theoretical linkages between plot heterogeneity, institutional friction, incremental transformation, and long-term resilience outcomes can plausibly operate in real-world historic urban fabrics. This paper addresses a gap in the literature by synthesising plot-level heterogeneity with broader resilience outcomes, offering policy implications for protecting such fabrics amid global urbanisation pressures. The findings align with land system science, emphasising multifunctionality for regenerative urbanism. Full article

This paper presents a high-precision angle demodulation method for magnetic encoders by integrating orthogonal-signal correction with space–time modulation (STM). The proposed approach specifically addresses a critical vulnerability of STM-based high-frequency pulse interpolation: its interpolation accuracy is highly sensitive to zero-crossing timing jitter of the quadrature signals. In practical magnetic encoders, non-idealities such as DC offsets, amplitude mismatch, and phase non-orthogonality in the sine/cosine outputs induce jitter and shift in the zero-crossing points. This directly leads to fluctuations in high-frequency counts and amplifies the final angle error. To mitigate this issue, an online orthogonal-signal correction module is first developed. This module sequentially performs offset estimation, amplitude normalization, and real-time phase orthogonalization, thereby enhancing the orthogonality and zero-crossing stability of the quadrature signals at the source. This preprocessing significantly reduces the sensitivity of the subsequent interpolation counting to noise and signal imperfections. Based on the corrected signals, an STM pulse-counting interpolator is adopted to convert angle information into a time-domain phase (time) difference, and high-frequency counting is used for fine subdivision. A Kalman-filter-based predictor is employed to estimate angular velocity and compensate the intrinsic latency of counting-based demodulation in dynamic conditions. Experimental results demonstrate that the proposed phase orthogonalization correction markedly suppresses zero-crossing timing jitter and enhances the stability of high-frequency pulse interpolation. Consequently, the overall demodulation error is reduced by more than 30 percent compared with existing methods, and the final angle error is maintained within 0.033°. Full article

Curved roofs constructed using hyperbolic paraboloid (HP) modules are gaining popularity in structural engineering due to their unique aesthetic and structural advantages. Consequently, these studies have investigated steel bar modules based on HP geometry, focusing on how variations in geometric configuration and bar topology affect internal force distribution and overall structural performance. Each module was designed on a 4 × 4 m square plan, incorporating external bars that formed the spatial frame and internal grid bars that filled the frame’s interior. Parametric modeling was conducted using Dynamo, while structural analysis and design were performed in Autodesk Robot Structural Analysis Professional (ARSAP). Key variables included the vertical displacement of frame corners (0–1.0 m at 0.25 m intervals), the orientation and spacing of internal bar divisions, and the overall mesh topology. A total of 126 structural models were analyzed, representing four distinct bar topology variants, including both planar and non-planar mesh configurations. The results demonstrate that structural efficiency is significantly influenced by the geometry and topology of the internal bar system, with notable differences observed across the various structural types. Computational analysis revealed that asymmetric configurations of non-planar quadrilateral subdivisions yielded the highest efficiency, while symmetric arrangements proved optimal for planar panel applications. These findings, along with observed design trends, offer valuable guidance for the development and optimization of steel bar structures based on HP geometry, applicable to both single-module and multi-module configurations. Full article

Light Detection and Ranging (LiDAR) point clouds are an essential perception modality for artificial intelligence systems like autonomous driving and robotics, where the ubiquity of small objects in real-world scenarios substantially challenges the visual tracking of small targets amidst the vastness of point cloud data. Current methods predominantly focus on developing universal frameworks for general object categories, often sidelining the persistent difficulties associated with small objects. These challenges stem from a scarcity of foreground points and a low tolerance for disturbances. To this end, we propose a deep neural network framework that trains a Siamese network for feature extraction and innovatively incorporates two pivotal modules: the target-awareness prototype mining (TAPM) module and the regional grid subdivision (RGS) module. The TAPM module utilizes the reconstruction mechanism of the masked auto-encoder to distill prototypes within the feature space, thereby enhancing the salience of foreground points and aiding in the precise localization of small objects. To heighten the tolerance of disturbances in feature maps, the RGS module is devised to retrieve detailed features of the search area, capitalizing on Vision Transformer and pixel shuffle technologies. Furthermore, beyond standard experimental configurations, we have meticulously crafted scaling experiments to assess the robustness of various trackers when dealing with small objects. Comprehensive evaluations show our method achieves a mean Success of 64.9% and 60.4% under original and scaled settings, outperforming benchmarks by +3.6% and +5.4%, respectively. Full article

This paper presents a novel Earth-System Stratified Grid (ISEA4H-ESSG) model, designed to address the challenges in multi-layer geoscience data management and analysis. In the realm of geosciences, which encompasses the solid earth, atmosphere, hydrosphere, and biosphere, as well as planetary and space sciences, the effective integration of diverse data sources is crucial. Traditional grids have limitations in three-dimensional spatial modeling, cross-layer data fusion, and dynamic multi-scale analysis. The ISEA4H-ESSG model overcomes these drawbacks by integrating the Icosahedral Snyder Equal-Area Aperture 4 Hexagon Discrete Global Grid System (ISEA4H DGGS) with a degenerative subdivision mechanism. It adheres to six core principles, including stratified spherical coverage, geographic consistency, multi-scale dynamic adaptability, global seamless partitioning, encoding uniqueness and efficiency, and multi-source data compatibility. Through the independent subdivision of spherical and radial layers, this model balances resolution differences and resolves polar-grid distortion and cross-layer data heterogeneity issues. The introduction of a four-dimensional spatiotemporal encoding framework enhances the storage and parallel computing capabilities of massive datasets. Case studies on ionosphere three-dimensional modeling and global atmospheric temperature field formatting demonstrate the high precision and adaptability of the ISEA4H-ESSG model. This research provides a unified spatial data infrastructure for geosciences, facilitating in-depth studies on natural hazards, climate change, and planetary evolution, and offering new perspectives for international partnerships and future Earth-related research. Full article

The effective management of spatiotemporal Earth observation data is a significant challenge due to their growing size and scale, geometric distortion, temporal gaps, and restricted access. In this article, we introduce a novel methodology utilizing a Discrete Global Grid System (DGGS) to address a set of challenges related to spatiotemporal data storage with a live updating mechanism, the multiresolution processing of an arbitrary region of interest (ROI) in real time, and the approximation of missing data in a smooth, continuous manner. We use reverse Chaikin subdivision and B-spline curve fitting to handle temporal data gaps, allowing for real-time updates. Additionally, our work presents a triangular wavelet scheme to incorporate a flexible, tensor-based multiresolution storage scheme for spatiotemporal raster data. The case study we present uses data from the RADARSAT Constellation Mission (RCM) of the Canadian Space Agency (CSA). Our system enables the dynamic retrieval and visualization of time-varying data for a user-defined ROI. The obtained results demonstrate that our method ensures high data fidelity while making spatiotemporal data more accessible across various practical applications in Earth observation. Full article

Despite extensive research on what draws people to urban streets, most existing insights originate from Western contexts, offering limited perspectives from wider urban contexts. This study addresses this gap by examining everyday street activities in Chinese urban villages, focusing specifically on how two spatial scales, the entire street edge and territorial segments, influence necessary, optional, and social engagements. Drawing on video recordings and walk-by observations in two urban villages in Wuhan, China, the research systematically measured the type and duration of activities across 110 territorially defined segments. The findings reveal that territorial segments, i.e., smaller-scale personalised subdivisions at a micro-scale often shaped by bottom–up adaptations, exert a significantly stronger influence upon how people use and linger in street space rather than entire street edges at a macro-scale, which shows only limited impact. This underscores the importance of fine-grained socio-spatial design and local ownership in fostering vibrant people-centred streets. By demonstrating the decisive role of micro-scale features, which span storefront layouts, semi-public alcoves, and adaptive uses, these results carry important implications for urban practitioners seeking to balance top–down redevelopment with bottom–up initiatives. Ultimately, the study enriches the global discourse on street-edge understanding and design, emphasising that territorial segments can be powerful catalysts for promoting activity and community life in dense urban contexts. Full article