Search Results (400)

This article examines the orientation that emerges during worship in the Abrahamic religions through the interrelation of bodily experience and architectural space. Drawing jointly on Maurice Merleau-Ponty’s phenomenology of the “lived body” and Mircea Eliade’s theory of sacred space, the study discusses how the directionality of worship in Judaism, Christianity, and Islam produces distinct spatial theologies. Methodologically, the research is based on a hermeneutic reading of selected sacred texts, rabbinic and liturgical sources, and on a comparative analysis of synagogue, church, and mosque spaces according to the criteria of orientation, architectural focus, bodily posture, congregational alignment, light, axis, threshold, and ritual surface. The proposed tripartite schema distinguishes between the horizontal covenantal orientation toward Jerusalem in Judaism, the vertical/transcendent axis associated with the cross, resurrection, and ascension in Christianity, and the downward orientation intensified around prostration in Islam. These orientations are not merely ritual prescriptions; rather, they constitute intentional structures through which the body is situated in relation to God, others, and the world. In the synagogue, the Torah ark and the direction of Jerusalem; in the church, the apse, cross, and luminous order; and in the mosque, the qibla wall, the alignment of prayer rows, and the surface of prostration are examined as architectural foci that materialize these intentional structures. The study brings together three domains that are often treated separately in literature: the phenomenology of religion, Eliadean cosmology, and architectural spatial analysis. In doing so, it proposes a comparative model of “spatial theology” among the Abrahamic traditions, articulated through the relationship between body, text, and worship structures. Ultimately, sacred space is interpreted as a dynamic order that is reconstituted in every act of worship through the convergence of bodily orientation, historical memory, and cosmic reference. Full article

Thin, steeply dipping orebodies hosted in kaolinized altered fault zones are difficult to mine safely because of weak rock mass integrity, water sensitivity, and limited self-supporting capacity. This study investigates the F20 ore-bearing altered structural zone at Changtai Mining and develops an artificial floor design for downward drift-and-fill mining. Engineering geological characterization, rock mass quality evaluation, mechanical analysis, and three-dimensional numerical simulation were combined to assess floor-bearing requirements and regional recovery stability. The results show that the wall rocks are grade III, whereas the ore-bearing altered zone is grade IV and represents the controlling weak component. For the preferred 3.5 m × 3.5 m drift, an equivalent artificial floor bearing thickness of about 1.0 m is required. Numerical evaluation indicates that supported drifts remain stable, but crosscut–drift intersections are the main deformation and damage concentration zones. A representative 0.5 m drift offset significantly weakens the load-transfer path of the floor–rock system. The proposed vertically aligned, short drift, rapid backfill scheme with a reinforced composite artificial floor provides a practical basis for safe recovery of weak kaolinized altered orebodies. Full article

Vertically linked commodity markets—global futures, regional spot, and farm-gate prices—transmit information through directed cross-market channels whose strength varies with latent volatility regimes. Standard deep learning forecasters absorb both the directed cross-market dependence and the regime dependence of intrinsic-mode-aligned latent components into shared model weights, with no explicit architectural mechanism that exposes either as an inspectable structure. This paper proposes HVB-RA, a modular framework that combines two such mechanisms with a per-tier Variational Mode Decomposition and bidirectional LSTM backbone: (i) a directed cross-market attention layer in which the upstream-to-downstream topology is supplied from domain knowledge and the time-varying upstream-source attention intensities at the farm-gate tier (the regional-spot tier, with a single upstream key, reduces algebraically to a fixed residual upstream fusion) are extracted from data, and (ii) a regime-informed modal-weighting layer that mixes two trainable softmax weight profiles over IMF-aligned latent components through a filtered Markov-switching state probability fitted in a separate stage. An auxiliary post hoc projection enforces an exact linear constraint defined by long-run sample-mean ratios across tiers; the paper does not claim that these descriptive ratios are cointegrating relations or equilibrium coefficients. The framework is evaluated on three tiers of daily natural-rubber prices spanning 2038 trading days, against three external benchmarks (random walk, ARIMA(2,0,2), and an exogenous-only LSTM) and a contemporary neural hierarchical-interpolation forecaster (NHITS). Root mean squared error is reported per tier-horizon cell; a decision-aware income-smoothing metric quantifies the operational value of $h=5$ farm-gate forecasts under a 5-day selling rule; and a within-method comparison evaluates the marginal contribution of the auxiliary constraint projection. On the present single-regime test window, HVB-RA attains a lower point error than the contemporary NHITS baseline at every tier-horizon cell, while no method—including HVB-RA—improves on the random-walk floor at most cells; the regime-conditional components of the architecture are not identifiable because every calibration and test origin is classified as a high-volatility regime by the trained Markov-switching model. The paper contributes to machine learning and knowledge extraction by demonstrating how time-varying upstream-source attention intensities at the farm-gate tier and regime-dependent latent-component-weight profiles—two forms of latent structure typically absorbed into model weights—can be exposed as explicit, inspectable, and individually testable components of a multi-tier forecasting architecture, and by providing a reproducibility package documenting the conditions under which each component is expected to be identifiable. Full article

Effective thermal management is critical for ensuring the reliability of modern high-power electronic devices, where thermal interface materials (TIMs) play key roles in minimizing contact resistance and improving heat dissipation. Boron nitride (BN) is widely used as a thermally conductive filler due to its high in-plane thermal conductivity and electrical insulation. However, achieving BN-based polymer composites that simultaneously offer high filler loading, flexibility, and high thermal conductivity (κ) remains a significant challenge. In this work, we introduce a novel two-step fabrication strategy to overcome this limitation. First, continuous BN fibers with high aspect ratios are assembled into BN fiber papers with enhanced fiber alignment. These papers are then cut and integrated into a silicone matrix to form well-oriented thermal conductive channels. This approach enables a significantly higher filler mass fraction of 70%, resulting in a thermal pad with a high κ of 19.23 W/(m·K), low thermal resistance of 1.61 cm²·K/W, and excellent electrical insulation and flexibility. Application tests further demonstrate superior heat dissipation performance and operational stability compared to commercial silicone pads. This work not only highlights the potential of BN fiber-based TIMs but also offers a feasible process for their large-scale manufacturing. Full article

Automatic storage and retrieval systems (AS/RSs) are essential components of modern high-tech production facilities. This study presents the dynamic model and control of an innovative multi-platform automated storage crane system. A novel autonomous AS/RS crane design with six vertically aligned and independently controlled load platforms is proposed, enabling the simultaneous transport of six load units within a single travel cycle. The simulation results indicate up to a 58% reduction under the assumed operating conditions, indicating a significant improvement in storage efficiency. In addition, the vertical position control problem of a load-carrying platform in the proposed crane structure is investigated. The performance of classical PID and model reference adaptive PID (MRAC-PID) was evaluated comparatively. The multi-platform crane design, for which a Decision on Grant of Patent was issued by the Turkish Patent and Trademark Office on 21 April 2026 (TR Patent Application No. 2023/018753, under Industrial Property Law No. 6769), offers an engineering solution that can be applied to increase production efficiency in automated storage and retrieval systems. Full article

Urban–rural fringes within contaminated regions frequently exhibit severe socio-environmental fragmentation and territorial stigmatization. This study evaluates the implementation of a Successional Agroforestry System (SAFS) in the “Land of Fires” (Southern Italy), which is conceptualized as a multifunctional socio-ecological infrastructure. Adopting a six-year longitudinal case study design (2019–2025), the research utilizes the Gioia methodology to triangulate retrospective field records and systematic monitoring with iterative qualitative narratives. Semi-quantitative and retrospective ecological evaluations indicate that the established multi-layered vertical stratification improved proxy indicators of structural complexity and soil functionality. Estimated soil surface coverage increased from 5.0 ± 1.2% to 85.0 ± 4.3%, while proxy vegetation density rose from 4.8 ± 1.2 to 36.4 ± 4.7 plants/m² (p < 0.001). Beyond these biophysical trends, the intervention catalyzed a “narrative inversion,” transitioning the site from a stigmatized wasteland to a socio-ecological hub that fostered a significant increase in community engagement (from 6.2 ± 1.4 to 34.8 ± 6.5 participants per event). By integrating agroecological practices with the EcoFoodFertility framework, the project highlights the potential of localized interventions to support primary environmental prevention strategies aligned with a One Health paradigm. The findings suggest that this SAFS represents a scalable model for territorial re-signification, offering transferable insights for aligning ecological restoration with social innovation in degraded peri-urban landscapes in accordance with Nature-Based Solutions (NBSs) and European Green Deal objectives. Full article

The relationship between water and sediment in the lower reaches of the Yellow River is uncoordinated, leading to frequent floods. In this area, the floodplain is situated below the main channel and embankment foundations, increasing the likelihood of overbank flooding. Ecological protective forests serve as a nature-based mitigation measure by reducing flow velocities along embankments and lowering the risk of structural failure during near-bank flood events. To assess the role of ecological protective forests, laboratory experiments were conducted, and field data informed parameterization and geometry selection. A total of 24 scenarios were designed, combining four forest arrangements (A1, A2, A3, and A4), two submergence degrees (H₀/H = 0.5 and 1.0), and three water and sediment conditions. Results show that sediment deposition increases with vegetation density. Under constant vegetation density and embankment-aligned flow, a larger along-flow to cross-flow spacing ratio promoted deposition upstream, whereas a smaller ratio extended deposition further downstream. Deposition thickness was greater under fully submerged conditions than under semi-submerged conditions. Among the arrangements, sediment deposition effectiveness followed the order A1 > A2 > A4 > A3, with arrangement A1 providing the strongest promotion of deposition. Under varying flow–sediment conditions, the A1 arrangement enhanced sediment deposition by 6.8% to 20.6%. Flow structure was also modified: under semi-submerged conditions, the vertical profile of longitudinal velocity approximated a logarithmic distribution, whereas full submergence produced a different profile due to combined drag from tree trunks and canopy. Vertical sediment concentration profiles were similar under both submerged states, with minimum values near the water surface and maximum concentrations near the bottom. These changes confirm that ecological protective forests contributed to reducing flow velocity and diminishing sediment transport capacity. Full article

High-resolution remote sensing image segmentation is important for urban mapping but remains challenging because of spectral ambiguity, large scale variations, fragmented elongated structures, and background interference. This study aims to improve semantic segmentation in complex aerial scenes by combining local feature extraction, selective multi-scale fusion, and global sequence modeling. We propose DSD-Mamba, an asymmetric dual-stream architecture with a ResNet-18 encoder. The Dense-Sparse Pyramid Fusion Module aligns multi-level features and applies dual Top-k selective value aggregation for cross-scale response filtering and background-response suppression. This Top-k operation is used as a feature-selection mechanism and is not intended to reduce the theoretical memory footprint of dense attention. Scale-Aware Strip Attention refines skip connections through horizontal and vertical dependency modeling, and the Dual-Stream Context Decoder combines a Mamba-based global branch with a CNN-based local branch during upsampling. Experiments were conducted on UAVid, ISPRS Vaihingen, and ISPRS Potsdam under a single-model inference protocol without test-time augmentation. DSD-Mamba achieved mIoU scores of 73.4%, 85.2%, and 87.2%, respectively. Ablation experiments on Vaihingen showed that DSPFM, SASA, and DSCD improved performance over the baseline when evaluated in this setting, with the full model reaching the highest mIoU. The method improves segmentation accuracy under the tested protocols, although its higher FLOPs indicate an accuracy-oriented rather than lightweight design. Full article

Residential buildings must now be designed and retrofitted as adaptive climate–health–work systems rather than as static housing units. This structured literature review synthesises peer-reviewed journal and conference evidence on residential taxonomy, ventilation, indoor environmental quality, overheating, airborne infection resilience, post-pandemic occupancy changes and future performance benchmarks. The review shows that single-family and multifamily buildings remain the most practical first-order categories because they differ in envelope exposure, ventilation pathways, system ownership, governance, retrofit feasibility and occupant control. Single-family dwellings generally provide greater household autonomy, roof-based renewable potential and room-level intervention flexibility, but can also carry higher envelope losses, lower density and stronger dependence on occupant operation. Multifamily buildings benefit from compactness and shared infrastructure, yet face additional risks from common services, vertical shafts, stack effects, corridor pressurisation, inter-zonal airflow and collective maintenance. Ventilation evidence indicates that natural, exhaust-only, supply, balanced heat-recovery, hybrid, demand-controlled and filtration-based strategies cannot be ranked universally; their effectiveness depends on climate, airtightness, pollutant source, occupancy, maintenance and governance. This review further shows that overheating, cooling-demand growth, airborne infection preparedness and remote work are shifting residential performance from winter-centric energy efficiency toward year-round thermal resilience, clean-air delivery and prolonged-occupancy functionality. A future taxonomy is therefore proposed around adaptive performance attributes, including thermal resilience, clean-air capacity, ventilation controllability, energy flexibility, remote-work readiness, vulnerability and retrofit potential. The core contribution is a hypothesis-generating, decision-support and benchmark-development framework for aligning residential design, retrofit and policy with health, indoor environmental quality, energy efficiency and carbon performance. Full article

This study focuses on the design and development of the Double Purpose Bench Vise to address safety, efficiency, and adaptability challenges in welding and fabrication environments. The project responds to limitations of conventional vises that restrict precision and increase the risk of strain-related injuries when handling heavy, irregular, or vertically oriented workpieces. Through an engineering-based development approach involving analysis, design, fabrication, and performance evaluation, the study introduces a Double Jaw Vertical Bench Vise equipped with a dual-clamping system and an integrated hydraulic jack mechanism for precise vertical adjustment with minimal physical effort. The device is designed to securely hold various materials, including metal bars, pipes, and wooden components, during cutting, grinding, shaping, welding, and assembly operations. Evaluation results from functional testing and user feedback indicate improved clamping stability, alignment accuracy, and ergonomic performance compared to traditional models, although refinements in structural optimization, weight distribution, and user interface components are recommended. The study suggests further prototype enhancement, extended field testing, and integration of advanced ergonomic and safety features to maximize durability, usability, and overall productivity in professional workshops and technical training laboratories. Full article

Accurate Unmanned Aerial Vehicle (UAV) position estimation is the cornerstone of urban low-altitude safety management systems. Time Difference of Arrival (TDOA) and Remote Identification (Remote ID) are widely used surveillance technologies with complementary characteristics. TDOA provides high-rate updates but suffers from geometry-induced horizontal–vertical anisotropy and multipath effects, while Remote ID supplies absolute state information yet struggles with intermittent sampling and packet loss. Existing fusion schemes typically address these issues in isolation: sequential filtering manages asynchrony but assumes Gaussian noise, robust estimators suppress outliers at the cost of discarding valid data, and coupled-filter architectures allow vertical anomalies to contaminate horizontal estimates through the Kalman gain cross-coupling. No prior framework jointly handles structural TDOA altitude jumps, stochastic Remote ID timing jitter, and the geometric anisotropy between estimation subspaces within a single coherent pipeline. To bridge this gap, we propose a Hybrid Conditional Kalman Filter (HCKF) framework comprising three integrated modules. First, a kinematics-based temporal alignment module maps asynchronous measurements onto a uniform timeline and predicts missing samples, resolving cross-modal time mismatches. Second, a measurement quality evaluation mechanism detects TDOA altitude steps via robust two-layer stratification and scores Remote ID timing irregularity through a confidence mapping, converting these anomalies into dynamic covariance adjustments and weight caps without discarding observations. Third, a Subspace-Decoupled Fusion strategy exploits the physical insight that TDOA horizontal precision derives from hyperbolic intersection geometry, whereas its vertical estimates suffer from weak observability due to near-coplanar ground-station deployment. By applying entropy-guided weighting in the horizontal plane and a conditional Remote ID-dominant rule in the vertical axis, this design prevents cross-dimensional error propagation. The framework was validated using three real-world flight missions at distinct altitudes (255 m, 345 m, and 440 m) totaling 13.51 km of flight distance, with RTK serving as ground truth. HCKF reduces the Root Mean Square Error by over 40% relative to single-source baselines (95% bootstrap confidence interval: [35.2%, 48.7%]), and paired Wilcoxon signed-rank tests confirm statistically significant improvement ($p<0.01$) over standard EKF, Covariance Intersection, and Iterative CI across all three tracks. Full article

Radar is critical for urban security against Unmanned Aerial Vehicles (UAVs), yet signal occlusion caused by dense buildings and complex urban structures remains a major challenge for coverage assessment. Existing approaches commonly rely on 2D maps or 2.5D Digital Surface Models (DSMs), which have difficulty representing vertical facades, vegetation, bridges, overhanging structures, and void spaces. These geometric limitations can introduce errors in radar occlusion determination and direct-path power-density estimation. Full 3D ray-tracing methods offer high fidelity, but their multi-path modeling and material-parameter requirements can be costly for large oblique photogrammetric city meshes. To address this problem, this paper proposes the Visible Radar Power-Density Field (VRPF), a 3D radar power-density field computation framework based on high-resolution oblique photogrammetric models. The method constructs a reusable spatial index for large numbers of triangular facets and performs two-stage occlusion queries: rapid Axis-Aligned Bounding Box (AABB) pruning followed by ray-triangle intersection tests. Together, these components enable efficient direct-path power-density calculation while accounting for line-of-sight occlusion in complex urban scenes. Qualitative and quantitative experiments show that VRPF better preserves occlusion boundaries around building edges, vegetation, and elevated structures than DSM-based baselines. VRPF also requires less time for repeated occlusion queries than a conventional 3D BVH ray-casting baseline while maintaining highly consistent radar-signal occlusion determinations. With 32 threads, VRPF computes power density for ${10}^8$ target points in 5.92 s, about $2.66\times$ faster than the 1 m DSM method. These results indicate that VRPF provides a practical balance between geometric fidelity and computational efficiency for direct-path radar power-density assessment with urban geometric occlusion. Full article

Post-rotation jacking is a critical construction stage for load-path reconstruction and alignment adjustment in rotation-constructed bridges, particularly for ultra-wide double-deck composite girder systems. Taking a two-span continuous steel truss–concrete composite girder bridge with spans of 2 × 85 m as the engineering background, this study investigates the mechanical behavior during post-rotation jacking through theoretical derivation, finite element simulation, and on-site monitoring. Based on the force method of structural mechanics, a linear relationship between vertical synchronous jacking force and displacement is derived, and an analytical formulation for bearing reaction redistribution under laterally asynchronous jacking is established by considering the coupling effects of vertical bending, torsion, and transverse multi-bearing support. A full-bridge spatial finite element model was developed in MIDAS Civil NX 2024 V1.1 to analyze the redistribution of bearing reactions and the stress response of the concrete crossbeam under different jacking conditions. The results show that, for the investigated bridge, the jacking force–displacement response remains highly linear during synchronous jacking. The B-axis middle bearing is more sensitive to jacking displacement than the two side bearings, with its fitted stiffness being approximately 2.19 times the average stiffness of the side bearings. Eccentric jacking causes reaction concentration at the jacked point and reaction reduction at adjacent supports, and the magnitude of reaction variation increases approximately linearly with jacking displacement. When the transverse non-uniform jacking magnitude reaches 20 mm, a tensile stress of 0.3 MPa appears at the bottom flange of the concrete crossbeam; therefore, a project-specific stroke-difference limit of 20 mm is recommended for this bridge, while the actual construction achieved a stroke control accuracy of ±0.5 mm and a transverse elevation difference within 1 mm. Field monitoring results validate the proposed analytical and numerical methods. The Pearson correlation coefficients of the measured jacking forces with the finite element and theoretical results are 0.9987 and 0.9988, respectively, and the corresponding mean relative errors are 3.84% and 4.23%. For stress responses, the measured and calculated values show a strong correlation, with a Pearson correlation coefficient of 0.9980 and a mean relative error of 12.77%; the critical mid-span monitoring point shows a relative error of only 0.65%. The final bridge alignment deviation is controlled within ±3 cm. The overall mean verification coefficient is 0.968, with a 95% empirical agreement range of [0.888, 1.048], indicating that the proposed mechanical analysis framework and combined force–displacement control strategy can provide a useful reference for refined construction control of similar ultra-wide double-deck composite girder bridges with comparable span arrangement and transverse bearing layout. Full article

Water–bearing fractures and seepage–prone zones ahead of tunnel faces may evolve rapidly under excavation–induced disturbance, making early identification and process tracking essential for risk mitigation. Cross–hole electrical resistivity tomography (ERT) is sensitive to fluid–controlled conductivity contrasts, but time–series interpretation based on independently inverted snapshots is often unreliable due to ill–posedness, noise, and temporal inconsistency. In this study, we propose an improved time–lapse ERT inversion framework for monitoring evolving water–bearing fractures ahead of tunnels. The method is formulated as a baseline–anchored, Occam–consistent difference inversion that directly estimates resistivity changes relative to an initial state, incorporating error–aware weighting of differenced data and anisotropic regularization adapted to cross–hole sensitivity, so that temporal coherence is enforced during inversion rather than through post hoc differencing. Synthetic verification is conducted using three dynamic scenarios representing horizontal, vertical, and diagonal migration of conductive water–bearing pathways between boreholes. Quantitative comparison against independent inversion across all scenarios and time steps demonstrates that the proposed framework substantially reduces the root mean square error and mean relative error of the recovered resistivity, while significantly improving the spatial correlation coefficient between the recovered and true models, with the largest improvements observed in the diagonal–migration scenario. The reconstructed change maps exhibit more compact anomaly geometry and delineate evolution corridors aligned with the prescribed trajectories, whereas independent inversion produces diffuse and epoch–dependent change patterns. These results indicate that the proposed time–lapse inversion framework provides a more reliable basis for interpreting evolving seepage–related conductive structures in tunnel–ahead investigations. Full article

To characterize the transport of the mining-induced sediment plume in the Clarion–Clipperton Zone (CCZ) nodule area, this study introduces a particle relative dispersion (RD) to assess material dispersion in 2D and 3D. In 2D, forward and backward RD results show clear sub-regional differences in particle aggregation and diffusion. Forward RD reaches a maximum ridge value of 40 km in regions of strong shear and strain. Backward RD effectively identifies upstream source regions and convergence pathways. High RD values align closely with strong strain-rate gradients, indicating that particle separation and mixing are primarily driven by transition regions between flow structures rather than uniform high- or low-strain areas. In the 3D, the vertical domain was limited to the 4500–4600 m depth range above the seabed. The overall RD patterns remain broadly consistent with the 2D results, while the maximum RD increases to approximately 80 km due to the inclusion of vertical displacement and local vertical shear effects. Within the 4500–4600 m depth range, horizontal transport remains dominant, whereas vertical variations are comparatively weak, and particle trajectories exhibit only minor local differences. Compared with the 2D case, the deep-layer 3D RD distribution exhibits lower skewness values, suggesting a more spatially balanced particle separation pattern with reduced directional asymmetry. Multi scale quasi-3D RD analysis provides essential insights into material dispersion and convergence patterns, offering valuable information for evaluating transport pathways, potential pollutant spread, and ecological risks associated with deep-sea mining. Full article