Search Results (196)

Visitor access in linear defensive built heritage landscapes needs to balance historical interpretation, route accessibility, and current protection constraints. This issue is evident in the Laoniuwan section of the Ming Great Wall in Shanxi Province, China, where heritage nodes lie within a scenic area but access infrastructure and interpretive route organization remain underdeveloped. This study proposes a conservation-oriented trail planning method for Great Wall scenic areas by combining MaxEnt-based historical defensive landscape modeling with GIS-based contemporary resistance analysis. MaxEnt was used to model terrain- and visibility-related suitability for defensive node locations, including watchtowers, beacon towers, forts, and mamian. The output was treated as a historical landscape interpretation layer, not as a prediction of tourist movement or final route location. Contemporary resistance was built from terrain ruggedness, road and village disturbance, the Great Wall protection buffer, permanent basic farmland, and the ecological conservation redline. Three historical–contemporary weighting scenarios were compared using least-cost path analysis. A Conservation–Interpretation Balance Index (CIBI) was then used to support scenario selection. The 4:6 scenario achieved the highest CIBI score (0.606). It maintained connectivity among defensive nodes while reducing ecological and farmland conflicts. The recommended loop trail was further translated into a four-tier conservation management zoning scheme. The results offer a spatial decision support approach for organizing fragmented built heritage resources into controlled-access interpretation routes with reduced disturbance to heritage fabric and protected land. Full article

Geographic Information Systems (GIS)-based spatial analyses have become an important tool for prehistoric research globally. Sri Lanka holds a distinctive prehistoric record in South Asia, supported by extensive investigations. In contrast, the systematic applications of GIS analyses for prehistoric studies on the island are comparatively limited. This study examines the spatial distribution of prehistoric sites in the Kegalle district, where recent documentation suggests it differs from previous estimates. The study identified 16 new prehistoric sites, bringing the total to 22, including six already documented, representing the first GIS-based systematic expansion of the prehistoric site inventory in this district in six decades. Three analyses, Kernel Density Estimation (KDE), Least-Cost Path (LCP), supported by 3D terrain modelling and corridor analysis, were applied to examine site distribution and modelled movement potential. KDE results provided a preliminary spatial visualization showing higher site density around the Ma Oya basin and the Seethawaka Ganga, a tributary of the Kelani River basin; given the small sample size (n = 22), these patterns should be treated as survey coverage indications rather than confirmed settlement distributions. LCP indicated valley-oriented modelled movement potential, intermediate elevation site distribution and key topographic convergence points across the landscape. Corridor analysis identified low-gradient valley routes as probable topographic movement zones along the modeled least-cost paths. The integrated results suggest a preliminary pattern of valley-oriented site distribution and topographically favorable movement terrain concentrated around the Ma Oya and Kelani River basins, treated as exploratory spatial indications pending validation through future systematic survey and radiocarbon dating. This study presents one of the first systematic applications of an integrated GIS-based analytical framework for prehistoric spatial analysis in Sri Lanka, suggesting how such approaches can generate testable hypotheses and provide actionable guidance for future archaeological fieldwork in regions where comprehensive chronological data remain limited. Full article

This study examines the effects of silvicultural management on the functional connectivity of fragmented Abies pinsapo forests in southern Spain. Using biomass stock as a resistance proxy, connectivity was assessed through accumulated cost-distance and least-cost path analyses under three scenarios: low intervention, traditional silviculture, and intensive thinning aimed at reducing climate vulnerability. The intensive thinning scenario produced the greatest connectivity gains, reducing mean accumulated costs by approximately 18% and standard deviation by 15%, with local reductions reaching up to 60% between specific population pairs. Median costs also declined, indicating widespread improvements rather than isolated effects. Spatial analyses revealed that previously high-resistance zones, particularly in central and northern sectors, shifted toward more permeable conditions. Least-cost paths were shortened and alternative, more efficient corridors emerged, especially in areas subjected to silvicultural treatments. Connectivity benefits extended to peripheral populations, decreasing their relative isolation and contributing to a more balanced network structure. Targeted biomass reduction may reshape landscape resistance patterns and strengthened ecological linkages, highlighting adaptive silviculture as a potentially valuable strategy for improving landscape connectivity and supporting conservation planning. Full article

Tool-calling LLM agents are vulnerable to indirect prompt injection: externally retrieved data can redirect tool calls without system-prompt access, and prompt-level defences leave three harm classes undefended (path traversal, user-guided exfiltration, high-frequency tool abuse). We present a Policy Enforcement Point (PEP) that intercepts at the tool-call boundary with declarative rules over a cross-step information-flow label system (source integrity, data sensitivity) and a synchronous SHA-256 hash-chained audit log. On a controlled dataset across four attack classes, the full system cuts the attack success rate (ASR) from 40.0% to 5.0% (deepseek-v4-pro, five repeats) versus 35.0% for the strongest prompt-only baseline; disabling cross-step label propagation raises the call-level false-negative rate by 26.4 points. The 30.0% task-level false-positive rate is dominated by by-design least-privilege capability-token denials, not rule false positives—an expanded 30-task benign set yields 0/30 rule false positives under scripted isolation. A conservative-DS mitigation (intent-taint) closes the constructed denied-read reconstruction blind-spot variant (ASR 100% to 0%) at no cost on standard workflows. The audit log detects all three tested tamper classes; the in-process enforcement overhead is sub-millisecond per call. Across four further backends, ASR drops under the full system, though LLaMA-3.3-70B retains 16.7% (a rule-coverage gap). A preliminary run over a real MCP stdio transport (an official filesystem server) shows the mechanism operates at a real boundary with a sub-millisecond execution-path increment. We frame these as mechanism-coverage evidence on a controlled benchmark, not a deployability claim for production MCP workloads. Code, data, and metrics are openly available in the replication repository. Full article

Chronic kidney disease (CKD) is a rising public health concern in low- and middle-income countries (LMICs), with urban populations disproportionately affected. In Bangladesh, particularly in Dhaka, dialysis services have become essential for CKD management. This study investigates the determinants of revisit intention among adult attendants of dialysis patients in Dhaka, using partial least squares structural equation modeling. A cross-sectional survey was conducted across four major dialysis centers totaling 399 valid responses. A purposive sampling technique was employed to ensure the inclusion of respondents with relevant experience and engagement in dialysis service utilization. Among respondents, over half were male, 43% had primary to higher secondary education, and one-third reported household incomes between BDT 40,001 and 60,000. The largest age group was 45–49 years (32.3%), and nearly 60% selected the facility due to nearness. Reliability and validity metrics met recommended thresholds, and multivariate normality was not assumed (Mardia’s test, p < 0.05). The structural model revealed significant direct effects of cost (β = 0.167, p = 0.003), Perceived trust in healthcare providers (β = 0.252, p < 0.001), and Perceived patient satisfaction (β = 0.422, p < 0.001) on Perceived revisit intention. Dialysis Delivery Service and word of mouth influenced revisit behavior indirectly through Perceived patient satisfaction. All mediation paths were statistically significant and classified as complementary. To improve patient retention, the policymaker should prioritize affordability, perceived trust in healthcare providers, and overall service quality, which together enhance perceived patients’ satisfaction and revisit intention. Full article

Active noise control (ANC) in real-world acoustic environments frequently faces impulsive and heavy-tailed noise disturbances, which degrade the performance significantly and lead to slow convergence. This work proposes a dynamically adaptive distribution-aware risk-sensitive filtered-x normalized least mean square (DA-RS-FxNLMS) method for efficient ANC under a non-Gaussian and impulsive scenario. The proposed ANC framework employs a correntropy-based risk-sensitive exponential cost function, which incorporates higher-order statistics and adapts to the error distribution. Further, an adaptive and dynamically adjusted kernel width mechanism tracks the time-varying noise characteristics. The normalized filtered-x structure provides stability under secondary path uncertainty. Simulation is carried out by applying α-stable noise to create an impulsive noise environment, which is produced by the Chambers-Mallows-Stuck method. The outcomes of the proposed method are compared with the baseline methods, showing that the proposed method achieves a noise reduction of 7.02 dB, a significant 40% faster convergence, and improved robustness under strong impulsive noise conditions with α = 1.2. The outcome confirms that the proposed method efficiently delivers a promising solution for the ANC system. To the best of our knowledge, for the first time, a unified ANC framework integrates distribution-aware, risk-sensitive learning, adaptive correntropy kernel estimation, and filtered-x normalization for non-Gaussian acoustic environments. Full article

Rapid urbanization and increasing landscape fragmentation pose significant threats to ecological connectivity, creating a need for integrative decision support approaches in sustainable spatial planning. This study presents a systematic review of ecological network optimization studies published between 2005 and 2025, following the PRISMA protocol. A total of 78 peer-reviewed studies were analyzed to identify methodological trends, recurring limitations, and research gaps in the assessment of structural and functional connectivity. Based on the gaps identified through the systematic review, this study proposes a conceptual Sustainable Spatial Decision Support System (S-SDSS) framework that integrates Morphological Spatial Pattern Analysis (MSPA), Multi-Criteria Evaluation (MCE/AHP), Minimum Cumulative Resistance (MCR), Least-Cost Path (LCP), and Gravity Modeling (GM) within a unified analytical structure. The review findings reveal a clear shift from single-method applications toward integrated multi-model approaches that better represent ecological processes and improve corridor prioritization. The proposed framework synthesizes the complementary strengths of these established methods to support evidence-based ecological network planning. The framework operates as a hybrid structure that combines a sequential analytical workflow with a unified typological classification system, generating Hybrid Ecological Typologies (T1–T5) as planning-oriented outputs that cannot be produced by any individual method alone. The proposed S-SDSS offers a transferable and policy-relevant conceptual basis for ecological network optimization, supporting green infrastructure planning, biodiversity conservation, and long-term landscape resilience across multiple spatial scales. Full article

Precise curvilinear path tracking remains a persistent challenge for autonomous agricultural machines, where conventional Model Predictive Control (MPC) suffers from poor adaptability to varying curvatures and high computational overhead in unstructured farmland environments. This paper proposes a soft-constrained MPC framework enhanced by a two-layer fuzzy architecture and Recursive Least Squares filtering to address these limitations simultaneously. The first fuzzy layer dynamically adjusts the MPC prediction horizon in response to real-time path curvature, enabling proactive steering on complex curved trajectories. The second fuzzy layer tunes the state weighting matrix online based on lateral and heading deviations, improving transient tracking accuracy without increasing computational cost. Recursive Least Squares filtering is further integrated to suppress sensor noise and compensate for tire slip dynamics inherent to farmland operation. The proposed framework is validated using MATLAB simulations on both constant-curvature semicircular paths and variable-curvature S-curve trajectories at operational speeds of 2.0 and 2.5 m/s, followed by outdoor field trials on a scaled autonomous robot platform. Simulation results demonstrate average tracking error reductions of 52.7–55.9% on constant-curvature paths and 10.8–18.2% on variable-curvature paths compared to fixed-parameter soft-constrained MPC. Field experiments confirm practical viability, achieving an RMS lateral error of 0.131 m over a 50 m curved route on natural terrain. These results demonstrate that the hierarchical decomposition of adaptation objectives yields substantial accuracy gains while preserving real-time feasibility on resource-constrained embedded platforms. Full article

As a significant source of global carbon emissions, the construction industry (CI) urgently needs to promote green transformation with the help of digital twin (DT) against the backdrop of human–machine collaboration and sustainable development advocated by CI 5.0. However, there is still a lack of systematic research on its specific driving mechanism and carbon reduction path. This study uses a systematic literature review (SLR) to explore how five key DT-enabled capabilities, namely, resource management (RM), process optimization (PO), real-time monitoring (R-Tm), sustainable design (SD), and predictive maintenance (PM), influence three performance indicators: efficiency improvement (EI), energy optimization (EO), and cost control (CC). Data from 490 companies were analyzed using partial least squares structural equation modeling (PLS-SEM) and a multilayer perceptron (MLP) with Shapley additive explanation (SHAP). The results show that the PLS-SEM and MLP models showed consistent patterns, with EO exhibiting the strongest predictive performance (Q² = 0.372; R² = 0.3666), followed by EI (Q² = 0.307; R² = 0.3109) and CC (Q² = 0.305; R² = 0.2609); the SHAP results further indicated that RM contributed most to EI (0.242), while PO was the most important driver for both EO (0.304) and CC (0.259). Academically, it introduces a quantitative approach combining PLS-SEM and machine learning. Practically, it highlights the priority of key technologies with cross-dimensional effects and offers guidance for governments to optimize digital resource allocation and carbon performance evaluation, as well as for enterprises to apply DT more effectively. Full article

Aiming at the divergence problem of standalone strapdown inertial navigation system (SINS) affected by initial errors, sensor drift, and cumulative errors in complex marine environments, this paper proposes a long-endurance autonomous navigation scheme without external measurement to suppress Schuler oscillations and improve dynamic navigation performance. First, based on the dynamic error model of SINS, the characteristics of Schuler oscillation are analyzed, and a multi-path delayed-solution strategy is developed. By sequentially delaying the SINS calculation loop and performing arithmetic averaging, periodic oscillation errors are automatically canceled. Second, a chi-square test is constructed to assess sea-state complexity in real time, and a robust adaptive Kalman filter is designed with adaptive filter selection to further improve estimation accuracy under dynamic conditions. Finally, the proposed method is systematically validated through static simulations, dynamic simulations, and full-scale ship experiments. Results show that the delayed-solution strategy significantly mitigates Schuler oscillation in attitude and velocity under static conditions. In dynamic simulations and ship trials, compared with pure SINS, single delayed-calculation, and conventional Kalman filter, the proposed approach achieves superior suppression of attitude, velocity, and position errors, with core navigation error indices reduced by at least one order of magnitude. These findings demonstrate that the Schuler period characteristic of inertial navigation errors can be effectively exploited in dynamic conditions, and the coupling of multi-path delayed calculation with robust adaptive filtering enables substantial improvements in autonomous navigation accuracy without external measurement. The proposed method expands the theoretical and engineering framework of autonomous navigation at no additional hardware cost, providing a new technical route for the practical deployment of long-duration SINS. Full article

Balancing tourism development with ecological integrity remains a central challenge in the management of protected areas. This study proposes a spatial framework that integrates the Outdoor Recreation Suitability Index (ORSI) and the Landscape Ecological Risk Index (ERI) to identify and optimize low-impact recreation corridors within Giant Panda National Park, China. Recreation suitability and ecological risk were modeled using environmental variables and landscape metrics, respectively. The results reveal a clear spatial pattern: high-suitability zones are concentrated in the central and northeastern areas, characterized by gentle terrain and extensive forest cover, while ecological risk is elevated in fragmented, human-disturbed peripheral regions. Although ORSI and ERI exhibit an overall negative spatial correlation, bivariate analysis reveals localized mismatches—areas where high recreation potential coincides with ecological vulnerability—indicating potential conflict zones. These zones are typically located along transitional park boundaries where accessibility intersects with ecological sensitivity. To mitigate such conflicts, a least-cost path analysis was conducted based on a composite resistance surface combining ORSI and inverted ERI values. The resulting corridor network connects 40 core areas while effectively avoiding ecological hotspots. Corridor buffers are predominantly composed of forest and shrubland, suggesting high environmental compatibility, particularly in the Qinling region. By translating spatial trade-offs into practical corridor design, this study provides a replicable approach for harmonizing recreation planning with conservation objectives. The proposed framework offers actionable guidance for evidence-based zoning, visitor flow management, and adaptive tourism development in ecologically sensitive protected landscapes. Full article

Assessing urban resilience under compound shocks requires observable and comparable process evidence that can inform resilient land governance and cross-jurisdiction planning. Using China’s Pilot Free Trade Zones (PFTZs) as a staged institutional setting, this research examines whether institutional exposure is associated with deviation–recovery trajectories of urban activity during the 2020 COVID-19 shock and whether these associations propagate through spatial spillovers with an identifiable scale profile. Institutional exposure is operationalized by the prefecture-level cities actually covered by PFTZ functional areas. With harmonized administrative boundaries, we construct an annual city-level VIIRS nighttime light (NTL) series for 2013–2024 and treat NTL as an activity-change signal rather than a direct proxy for output. We trace shock deviation in 2020 and subsequent recovery via staged differencing. Spatial interaction frictions are represented by least-cost path distance (LCPD) derived from a multi-source cost surface, which is used to build a gravity-based spatial weight matrix. Estimation relies on the Spatial Durbin Model (SDM), with LeSage–Pace impact decomposition to distinguish direct and spillover effects, complemented by distance-threshold diagnostics to map attenuation patterns. Results indicate persistent clustering within the PFTZ-related urban system. The shock year is characterized by compressed connectivity and fragmented brightening, whereas recovery proceeds in a layered manner with earlier core repair, partial corridor reconnection, and weaker adjustment at the periphery. Spatial dependence in activity change is statistically significant. Associations linked to institutional exposure are realized primarily locally, while structural and scale conditions more readily operate through spatial externalities. Spillovers are most detectable at meso-scales and attenuate gradually across distance thresholds. Overall, the integrated earth-observation and spatial-econometric framework provides replicable geospatial evidence to support resilient land governance and regional coordination under common shocks. Full article

This paper proposes a complex fast recursive least-squares (FRLS) channel-estimation algorithm for single-carrier electromagnetic (EM) communications across the seawater–air interface, where severe attenuation and multipath cause strong SNR fluctuations. By redesigning the input-data structure and using forward–backward joint estimation, FRLS reduces the per-iteration complexity from the quadratic cost of classical RLS to a linear form (14L + 20 operations per iteration, where L is the channel length). Simulations under representative one- to three-path channels show that FRLS achieves the lowest steady-state mean-square deviation (MSD) at low SNR, outperforming LMS, IPNLMS, RLS, and PRLS. Offshore experiments further validate the practicality: after MMSE equalization, FRLS yields higher OSNR and improves the BER distribution, demonstrating an effective accuracy–complexity trade-off for hardware-constrained cross-medium EM links. Full article

CO₂ pipeline transportation is a core link in the CCUS (Carbon Capture, Utilization, and Storage Technology) industry. Ensuring the flow safety of CO₂ pipelines under transient conditions is currently a key and challenging issue in industry research. This paper focuses on the phase migration and safety control during the shutdown process of supercritical carbon dioxide pipelines. Taking a supercritical carbon dioxide transportation pipeline in Xinjiang Oilfield, China, as the research object, a hydro-thermal coupling model of the pipeline is established to simulate the pipeline and elucidate the coordinated variation patterns of temperature, pressure, density, and phase state. It was found that there were significant differences in the migration paths of the CO₂ phase at different positions. The accuracy of the simulation results was verified through the self-built high-pressure visual reactor experimental system, and the influences of the initial temperature, initial pressure, and ambient temperature before pipeline shutdown on the slope of the phase migration path were explored. The phase migration line slope prediction model was established by using the least squares method and ridge regression method, the process boundary ranges and allowable shutdown time ranges for pipeline safety shutdowns in both summer and winter were further established. The research results show that when the pipeline operates under the low-pressure and high-temperature boundary, the CO₂ in the pipeline vaporizes earlier from the starting point after the pipeline is shut down, and the safe shutdown time of the pipeline is shorter. There is a clear safety operation window in summer, while vaporization risks are widespread in winter. The phase migration path prediction formula and the safety zone division method proposed in this paper provide a theoretical basis and engineering guidance for the safe shutdown control of supercritical carbon dioxide pipelines, which can help reduce operational risks and lower maintenance costs. Full article

Out-of-hospital cardiac arrest (OHCA) is a major cause of death during mountain activities in the Alpine regions. Due to the time-critical nature of these emergencies and the logistical challenges of remote terrain, emergency medical services (EMS) are investigating the use of unmanned aerial vehicles (UAVs) to deliver automated external defibrillators (AEDs). This study presents a geospatial strategy for optimising AED delivery by UAVs in mountainous environments, using the Province of South Tyrol, Italy, as a model region. A Geographic Information System (GIS) framework was developed to identify suitable sites for vertical drone ports based on terrain, infrastructure, and regulatory constraints. A Low-Altitude-Flight Elevation Model (LAFEM) was implemented to generate obstacle-avoiding, regulation-compliant 3D flight paths using least-cost path analysis. The results identified 542 potential vertical-port locations, covering approximately 49% of South Tyrol within ten minutes of flight, and demonstrated significant time savings for AED delivery in field tests compared with manual and Euclidean routing. These findings show that integrating GIS-based vertical-port placement and terrain-adaptive UAV routing can substantially improve AED accessibility and response times in mountainous regions. The LAFEM model aligns with U-space airspace regulations and supports safe, automated AED deployment for improved outcomes in OHCA emergencies. Full article