Search Results (1,291)

Long and narrow shielded confined spaces, represented by traffic tunnels and underground utility tunnels, constitute critical application scenarios for indoor and underground positioning services. Despite their relatively simple geometric configurations, such environments suffer from severe spatial distortion of geometric dilution of precision (GDOP). Coupled with pervasive low-elevation signal propagation and intensive multipath reflection effects, conventional BeiDou Navigation Satellite System (BDS) positioning services are unable to provide continuous and reliable coverage in these scenarios. To date, existing research on high-precision pseudolite positioning for narrow confined spaces remains largely confined to theoretical analysis and laboratory experimental verification, while systematic studies on application-oriented signal atlas feature network design are significantly insufficient, forming a prominent gap that restricts the practical engineering deployment of relevant technologies. To address the aforementioned technical bottlenecks, this paper proposes a novel BDS pseudolite signal atlas network design method to improve the continuity, stability and comprehensive positioning performance in spatially distorted narrow shielded environments. Field vehicular tests were carried out in actual engineering tunnels and underground utility tunnels to systematically analyze the variation characteristics of raw BDS pseudolite observation data, including pseudorange, carrier phase, carrier-to-noise ratio (C/N₀) and Doppler shift. The test results verified that kinematic Doppler parameters exhibited outstanding stability in complex shielded environments with strong multipath interference. On this basis, a spatial feature model based on kinematic Doppler measurements was constructed, and wavelet denoising technology was adopted to extract effective typical spatial feature parameters. Combined with the deterministic one-to-one mapping relationship between Doppler peak characteristics and spatial positions, a multi-peak kinematic Doppler atlas was established, which eliminates the dependence on pre-deployment data collection, dedicated database construction and offline model training. Furthermore, comprehensively considering multi-dimensional constraints such as spatial environment scale, carrier dynamic characteristics and terminal output rate, the atlas network scheme was optimized to achieve a balanced trade-off among positioning detection accuracy, absolute positioning precision and suppression of the pseudolite near-far effect. Comparative experimental results demonstrate that the proposed BDS pseudolite atlas network effectively resolves the inherent GNSS positioning difficulty in long and narrow shielded spaces. Benefiting from the rational spectral peak configuration strategy, the system can satisfy the continuous and stable positioning requirements of multiple carrier types including motor vehicles and railway locomotives under variable motion speeds and terminal output rates. This study provides a robust and feasible technical solution for high-precision BDS positioning services in long and narrow shielded confined spaces, and holds favorable engineering application prospects for underground navigation scenarios. Full article

The Jiaduoling area is located in the northern segment of the Southwest Sanjiang Metallogenic Belt, a region characterized by complex geological structures and abundant mineral resources. This study systematically identifies the spatial correlation between subsurface magnetic bodies and tectonic structures by utilizing 1:50,000 high-precision aeromagnetic data. Advanced processing techniques—including upward continuation, vertical derivatives, total gradient modulus, and Euler deconvolution—were integrated to refine the structural framework and clarify the mechanisms of fault-controlled mineralization. The results indicate that the aeromagnetic anomaly pattern is predominantly governed by NW-trending faults. Specifically, the deep-seated major fault F₁ (with a calculated depth exceeding 3 km) served as the primary migration channel for ore-forming fluids, while secondary faults created localized ore-hosting spaces. Physical property analysis reveals a significant magnetic contrast, where Mesozoic intermediate-acid magmatic rocks act as the essential source for mineralization, providing both material and thermal energy for the formation of porphyrite-type iron deposits. Based on these findings, a three-dimensional “aeromagnetic anomaly-structural framework-mineralization” correlation model was established. Finally, two high-potential metallogenic prospective zones (P1 and P2) were delineated, providing precise geophysical evidence and strategic guidance for regional mineral exploration and the targeting of concealed ore bodies. Full article

Plant-based food systems increasingly rely on heat-induced gelation of protein–starch mixtures, yet no focused synthesis has linked legume protein composition to mixed gel structure and function. This review critically analyses heat-induced gelation mechanisms in legume protein–starch systems, using the legumin-to-vicilin (L:V) ratio and starch origin as integrating design parameters. Legume storage proteins range from legumin-rich faba bean and Lupinus angustifolius, which form dense, disulfide-stabilised networks with high storage moduli, to vicilin-dominated mung bean, which produces weaker gels reliant on starch reinforcement. Pulse starches, characterised by high amylose content (24–45%), C-type crystallinity, and rapid amylose retrogradation upon cooling, act as a parallel gel-forming phase whose contribution scales inversely with protein network strength. Four protein–starch interaction modes, namely segregative phase separation, water competition, granule filler effects, and molecular complexation, jointly determine microstructure and rheological behaviour. A three-axis compositional framework defined by the L:V ratio, starch amylose content, and protein-to-starch ratio maps the gel design space. Variables favouring plant-based meat analogue performance, including high elastic modulus, yield stress, and hardness, are systematically opposed by dysphagia food requirements, including low yield stress, adequate lubrication, and soft fracture. This demonstrates that both application domains traverse the same compositional space in opposite directions. Critical research gaps include chickpea and lentil performance in meat analogue systems, mechanistic modelling of protein-matrix-mediated starch digestibility, and retrogradation kinetics during food storage. Full article

The study examines the evolution, knowledge structure, and trends in snowmelt runoff prediction models. It identifies research hotspots, future directions, and offers a theoretical basis for accurate simulation and prediction. Utilizing CiteSpace software, 556 core Chinese and English publications from 2010 to 2025 were visually analyzed. Research on snowmelt runoff simulation shows: (1) Chinese publications are prominent in core journals like “Journal of Glaciology and Geocryology,” while English publications appear in high-impact journals like “Water Resources Research.” (2) Institutions like the University of Chinese Academy of Sciences, the Northwest Institute of Eco-Environment and Resources, and the University of California have formed a cross-regional research network. (3) International collaboration involves 42 countries, with a focus on China, the United States, and India. However, domestic institutional cooperation needs improvement. (4) Research trends in snowmelt runoff simulation have progressed from empirical statistics to remote sensing and model-driven physical mechanisms, and now to the integration of artificial intelligence with physical models. (5) The Chinese literature focuses on cold regions, while the English literature emphasizes intelligent modeling. This shift indicates a move towards “physical–intelligent” hybrid modeling. Future research should address challenges like model applicability in data-scarce areas, improving interpretability of complex models, quantifying uncertainties, and developing physically constrained deep learning models. Collaboration among institutions is crucial for enhancing water resource management and disaster warning systems in cold regions. Full article

The magmatic Ni-Co-Cu mineralization in the Iken deposit in the central part of the Kun-Manie complex, Amur Oblast, Russia, hosted by an olivine-bearing websterite, is of a low-sulfide type. The fine-grained disseminations of base metal sulfides (BMS), dominantly pyrrhotite, pentlandite (a major source of Ni of industrial importance), and chalcopyrite, are followed by a scarce Pd-Pt-Ag mineralization. Elevated contents of Al in orthopyroxene (mean 2.78 wt.% Al₂O₃) along with Al–Na enrichment in clinopyroxene (diopside; mean 5.10 wt.% Al₂O₃) are associated with highly aluminous compositions of low-chromium members of the spinel–hercynite series. High levels of TiO₂ in kaersutite and titanian phlogopite also reflect a pronounced degree of fractionation of the ore-forming melt. Minor portions of sulfide melt are distributed evenly as a result of immiscibility at advanced stages of orthopyroxene crystallization, after the formation of olivine. Differentiated grains of droplet-like BMS largely settled in situ close to grain boundaries of orthopyroxene or occupied interstitial spaces of pyroxenes and olivine in association with spinel–hercynite and fluorapatite. A combination of late saturation in S with relatively quick cooling rates of the hypabyssal body prevented the effective settlement and accumulation of sulfide droplets in the ore zone. The well-developed lamellae of troilite (Fe₅₀S₅₀) exsolved from the host pyrrhotite Fe₄₈S₅₂ during subsolidus cooling, as a consequence of a low-temperature reaction triggered by a sudden drop in fO₂. An influx of mantle-derived fluid bearing CO₂, CO, and CH₄ with the rising magma could be the primary cause of the fO₂ reduction. Also, graphite-bearing metasedimentary rocks could have been assimilated. Tiny grains of minerals of noble metals (moncheite and merenskyite with essential amounts of melonite component, sperrylite, hessite, alloy Au_63.2Ag_36.8, and argentopentlandite) deposited late in a fluid-enriched medium under submagmatic conditions. Full article

Urban tourism communities activate local resources through spaces shared by residents and tourists, yet the inherent spatial overlap and functional complexity of these areas often generate conflicts. Existing research has predominantly focused on traditional scenic areas, heritage sites, or cities affected by overtourism, with comparatively little attention to urban tourism communities. This study draws on three tourism communities in Chongqing, China, employing street-intercept interviews and spatial analysis to investigate the forms and spatial characteristics of resident–tourist conflict. The findings indicate that such conflicts manifest across four dimensions: management conflict, economic conflict, resource and environmental conflict, and socio-cultural conflict. Conflicts are more likely to occur in areas where tourist activities intersect with residents’ daily routines, and different conflict types exhibit distinct spatial patterns. Furthermore, residents are more sensitive to these conflicts than tourists. By adopting a dual resident–tourist perspective, this study advances understanding of the tensions in high-density, high-mobility urban tourism communities and provides empirical insights to inform their sustainable development. Full article

Combined Vertical–Horizontal Well Patterns (CVHWPs) have been increasingly applied in mature and complex reservoirs, such as the C5 Block. Their application is attractive because they provide extensive reservoir coverage and high development efficiency. However, close well spacing and the three-dimensional configuration of vertical and horizontal wells can induce strong stress-shadow interference. This interference makes fracture propagation difficult to control and may reduce stimulation effectiveness. To address this problem, a multi-well, multi-fracture induced-stress model for CVHWP stimulation was developed in this study. The model was validated using laboratory three-stage fracturing experiments, including two horizontal-well stages and one vertical-well stage, together with field observations. Across three stages, the calculated stress intensity factors at breakdown are closely matched, validating the induced-stress model. When the vertical well was fractured first, the horizontal principal-stress difference at the adjacent horizontal stage increased by 2.01 MPa, which was unfavorable for branched fracture development. In contrast, when the horizontal stage was fractured first, the stress difference decreased by 3.25 MPa at the subsequent horizontal stage and by 3.89 MPa at the vertical-well stage. This sequence is preferable because fractures generated from the vertical well impose a stronger stress perturbation on adjacent horizontal-well fractures than fractures generated from the horizontal well impose on the subsequent vertical-well fracture. Under the tested CVHWP conditions, the horizontal-well fractures tended to form nearly symmetric bi-wing planar fractures, whereas branched fractures were more likely to develop in the vertical well. Therefore, for CVHWP reservoirs with close vertical–horizontal well spacing and significant stress interference, fracturing the horizontal well before the vertical well is recommended to control fracture propagation and promote multiple-fracture formation. Field application of this sequence showed notable production improvement, indicating that the proposed method can provide practical guidance for unconventional well-pattern fracturing design. Full article

The interlayer pores of 3D-printed concrete (3DPC) significantly weaken its macroscopic mechanical properties. In this study, the phase-field cohesive zone model (PF-CZM) is employed as a numerical tool to systematically investigate the weakening mechanisms and crack evolution behavior associated with pore characteristics, including pore size, morphology, spatial orientation, and arrangement, through single-factor numerical simulations with different pore numbers. The results demonstrate that the degradation induced by a single pore is controlled by its effective projection length in the direction perpendicular to the principal tensile stress, with horizontal flat pores being the most detrimental under the same porosity. In the multi-pore system, the connection angle between pores, rather than their spacing, is the key factor determining structural degradation, and a horizontal collinear arrangement is prone to triggering brittle fracture. Furthermore, locally aggregated small pores can form combined defects, whose strength-weakening effect surpasses that of isolated large pores, thereby triggering crack path competition and leading to asymmetrical structural failure. This study reveals the fracture mechanisms driven by complex pore configurations and provides a reference for strength prediction of 3DPC. Full article

The toroidal propeller, as a high-performance propulsor with a unique geometric configuration, presents challenges in parameterizing its complex geometry and conducting design optimization. This paper proposes a hybrid Free-Form Deformation (FFD) based parametric method, which integrates global FFD control with local parameters to achieve flexible and efficient description of the complex surfaces of toroidal propellers. Building upon this, an automated design framework integrating Computational Fluid Dynamics (CFD), a Kriging surrogate model, and a data-driven optimization algorithm is constructed to explore a high-dimensional design space comprising 14 variables. The goal is to minimize torque while satisfying thrust and geometric constraints. Optimization results show that the optimized propeller achieves approximately 3.63% higher propulsive efficiency at the design condition and requires about 4.32% less power for the required thrust, compared with the best design from Design of Experiments (DOE) sampling. Further flow field analysis reveals that the optimized design achieves a more gradual pressure distribution, which effectively suppresses flow separation and cavitation risk, thereby maintaining better performance across a wider operational range. This study provides a systematic parametric modeling method and optimization strategy for the efficient design of toroidal propellers, demonstrating clear engineering application value. Full article

Mountainous traditional villages are rural heritage settlements shaped by complex environmental and socioeconomic interactions. Rapid urbanization has driven resource outflow and spatial restructuring, intensifying the conservation–development conflict. Existing conservation models relying on standardized criteria neglect village heterogeneity, and current studies insufficiently capture cluster-specific driving mechanisms across spatial scales. Using 153 traditional villages in the Qin–Ba Mountains of southern Shaanxi, this study shifts the analysis from overall spatial pattern identification to the comparison of cluster-specific driving mechanisms. The results indicate (1) traditional villages display an agglomeration pattern of “one primary core, one secondary core, and multiple peripheries,” forming valley corridor and hilly barrier clusters; (2) socioeconomic factors show greater explanatory power than natural factors at the global scale; (3) influencing factors exhibit dual heterogeneity, with intensity and direction varying across space and clusters displaying distinct dominant-factor combinations; and (4) socioeconomic factors may provide enabling conditions for traditional village conservation and adaptive reuse under appropriate governance contexts. Accordingly, valley corridor clusters can follow “conservation through development,” whereas hilly barrier clusters should adopt “development through conservation.” These findings offer empirical support for spatially differentiated governance of mountainous traditional villages. Full article

With the rapid development of high-end equipment manufacturing, the number and size of complex surfaces continue to increase. Five-axis machining has become the dominant machining method. Effective prediction of cutting force and stability is of great significance for improving machining efficiency and quality. However, due to the complex and time-varying cutting geometry in five-axis machining of complex surfaces, low prediction efficiency has become a key issue restricting the research and engineering application of cutting force and stability. To address this issue, this study introduces the concept of dimensional compression and establishes an efficient prediction model for cutting force and stability. Each tool position along the tool path is discretized into inclined plane milling based on finite difference, thereby simplifying the research object. The tool twist angle and feed deflection angle are defined to describe the spatial relationship in five-axis machining. Using these two angles as new basis variables, a compressed space is constructed, and a mapping relationship between tool position and spatial point sets is established, further reducing the dimensionality of the research object. The cutting edge contact interval is determined using the spatial constraint method. Based on the full discretization method, the cutting force and stability of inclined plane milling are predicted, and the results are uniformly stored in the compressed space to form a sample point library. Consequently, the prediction process of complex surface five-axis machining is transformed into a process of sample point retrieval, significantly improving computational efficiency. Cutting force and vibration experiments in five-axis machining of complex surfaces are conducted. The results show that the predicted results are in good agreement with the experimental measurements, validating the accuracy of the proposed model and demonstrating its capability to guide practical machining. Full article

Exchange-rate forecasting requires modelling non-stationary dynamics, heavy-tailed shocks, and complex temporal dependencies. However, forecasting performance in emerging-market currencies is fundamentally constrained by intrinsic dynamical instability, while most existing approaches are evaluated primarily through predictive accuracy rather than the predictability limits of the underlying system. This paper develops a predictability-aware framework that combines nonlinear dynamical diagnostics with a Lévy-driven neural stochastic differential equation model. Drift and diffusion are parameterized by neural networks and driven by $\alpha$-stable Lévy motion, enabling the representation of non-Gaussian fluctuations, abrupt shocks, and regime changes. To learn under discontinuous dynamics, we introduce a structurally constrained training objective based on a strong-form discretization of the underlying SDE. To characterise intrinsic predictability, we employ phase-space reconstruction and maximal Lyapunov exponent estimation. These diagnostics are interpreted as finite-sample measures of trajectory divergence and effective instability in a stochastic system, rather than evidence of low-dimensional deterministic chaos—a distinction motivated by well-documented limitations of chaos testing in financial data. Experiments on multiple West African currency pairs demonstrate competitive short-horizon forecasting performance relative to econometric and neural baselines while providing a principled framework for analysing predictability degradation under heavy-tailed stochastic dynamics. Across currencies and model classes, forecasting accuracy deteriorates beyond horizons comparable to the estimated Lyapunov time, suggesting that forecast degradation reflects intrinsic dynamical instability rather than model-specific limitations. The results support the view that reliable exchange-rate prediction is fundamentally a short-horizon problem and illustrate how stochastic dynamical modelling and predictability diagnostics can be combined to characterise forecasting limits in heavy-tailed financial systems. Full article

Background and Clinical Significance: Tumefactive Multiple Sclerosis (TMS) represents a rare and diagnostically challenging form of demyelinating disease characterized by large space-occupying lesions that can closely mimic intracranial neoplasms, abscesses, and other inflammatory or vascular conditions. Case Presentation: The case highlights the overlapping radiologic features that frequently lead to diagnostic uncertainty and underscores the importance of careful interpretation of multimodal imaging and ancillary studies. Overall a comprehensive multidisciplinary evaluation is essential to reduce the risk of misdiagnosis and avoid unnecessary invasive interventions. Conclusions: This review summarizes current evidence regarding the diagnostic approach, imaging characteristics, and therapeutic strategies for tumefactive demyelinating lesions. Additionally, we present a clinical case that illustrates the diagnostic complexity of this entity, in which neuroimaging findings and cerebrospinal fluid analysis supported a demyelinating rather than neoplastic process. Full article

This paper examines the spatial integration of post-socialist churches and parish complexes within the modernist housing estates of Novi Zagreb. Constructed after 1990 in neighbourhoods originally planned without sacral programs, these buildings represent a specific form of post-socialist urban intervention. The study employs a qualitative, comparative approach, analysing five case studies through the parameters of urban context, volumetry, spatial composition, program, and public space interface. The analysis identifies a limited set of recurring typologies that define patterns of spatial integration within the existing urban fabric. The findings indicate that these complexes do not function as dominant urban elements, but instead adapt to the open, functionally organized structure of modernist planning. Their impact on public space remains limited, as they rarely generate new centres or clearly articulated urban nodes. At the same time, the results reveal a shift from singular religious buildings toward programmatically expanded parish complexes that incorporate social and community functions. However, this transformation remains largely internal and does not lead to a significant reconfiguration of the urban structure. The paper contributes to the understanding of post-socialist urban transformation by identifying typological patterns and interpreting religious architecture as a context-dependent urban actor. Full article

This research proposes a conditional diffusion-based workflow for early-stage floor plan design in university research buildings, addressing complex functional organization, strict boundary constraints, and quantitative area control. The method performs denoising directly in two-dimensional grid space and coordinates building outlines and functional area proportions through dual-condition injection using boundary masks and functional area matrices. A two-stage generation mechanism first constructs horizontal circulation and then generates the complete layout, while a statistic-network-guided explicit constraint improves global area consistency. Based on 600 standard-floor samples and an independent test set of 10 real projects, the method is evaluated through model comparison, ablation, and double-blind experiments. The results show that the proposed model achieves the best overall performance, with an FID of 50.3, a building boundary IoU of 99.9%, and horizontal circulation connectivity of 89.8%. The ablation results confirm that the two-stage mechanism and explicit statistical constraint substantially improve generation success and reduce area error. The expert evaluation indicates that AI-generated floor plans approach real cases in functional spatial form and design inspiration, although spatial organization rationality still requires improvement. The generated layouts can be converted into layered DXF files, supporting subsequent editing and human–AI collaborative design. Full article