Search Results (1,766)

The integration of cultural heritage into sustainable urban development has garnered increasing attention, with a growing recognition of its role in fostering resilient, inclusive, and identity-rich cities. While surface-level monuments often receive the primary focus in heritage conservation, archaeological remains buried beneath cities face escalating threats—particularly from large-scale underground infrastructure projects. Among these, underground transit systems pose the most significant risk due to their spatial extent and physical disruption. This paper addresses the pressing challenge of balancing underground urban development with the preservation of subterranean cultural heritage. Using the Ancient Cultural and Communication Complex “Serdika” in Sofia, Bulgaria, as a case study, this study examines how integrated planning and interdisciplinary cooperation can harmonize heritage conservation with modern infrastructure development. The study explores strategies such as spatial integration, design coordination, and adaptive reuse to embed archaeological remains within transit-oriented public spaces. The Serdica project demonstrates that such approaches not only protect heritage sites but also enhance their accessibility and public value, contributing to strengthened urban identity and increased cultural tourism. The findings highlight the potential of underground heritage spaces to serve as dynamic nodes of cultural exchange and urban continuity. The study concludes that culturally sustainable design of underground public infrastructure-when guided by inclusive planning and heritage-informed strategies—offers a viable path toward sustainable urban futures that respect both development needs and historical continuity. Full article

Embodied energy flows link production systems with the energy sector, reflecting dependencies and structural risks under globalization and regional coordination. Guangdong, China’s most manufacturing-intensive, open, and energy-consuming province, is a central hub in both global value chains and domestic production networks, playing a pivotal role in national energy security. Understanding Guangdong’s embodied energy flows is essential for revealing the transmission of energy across multi-level spatial systems and the resilience of China’s energy infrastructure. This study integrates international (EXIOBASE) and Chinese inter-provincial input–output data to build a province-level nested global MRIO model, combined with Structural Path Analysis (SPA), to characterize Guangdong’s manufacturing embodied energy flows in domestic and international dual circulation from 2002 to 2017. Our findings confirm Guangdong’s pivotal bridging role in embodied energy transfers. First, flows are dual-directional and dominated by international transfers. Second, energy efficiency has improved, narrowing the intensity gap between export- and domestic-oriented industries. Third, flows have diversified spatially from concentration in developed regions toward developing regions, with domestic inter-provincial flows more dispersed. Finally, embodied energy remains highly concentrated across sectors, with leading industries shifting from labor- and capital-intensive to capital- and technology-intensive sectors. This research offers vital empirical evidence and policy reference for enhancing national energy security and optimizing spatial energy allocation. Full article

Due to a complex of factors, visually impaired people are facing difficulties and increased risks during fire emergencies and evacuations from different types of buildings. Even if a lot of studies have been conducted to improve the mobility and autonomy of people with visual impairment during emergency evacuation processes, these offer only partial solutions, especially in the presence of uncertainties characteristic of fire evolution. Aiming for a more comprehensive approach to the safe evacuation of people with visual impairments, this paper proposes a support system that integrates innovative aspects related to the architecture of the application, modeling and simulation methods, and experimental realization. The system is decentralized, capable of anticipating possible fire extensions and determining, in real-time, new corresponding evacuation routes. The overall design complies with the standard norms in emergency situations. Two models, one developed in Stateflow and the other based on Delay Time Petri Nets (DTPN), were constructed to describe the dynamic behavior of the system in the presence of unexpected events that can change the initial recommended evacuation path. To test the functionality and efficiency of the proposed system, the conditions created by potential fire sources were simulated as a part of realistic scenarios. Tests were conducted with visually impaired people. Simulation and prototype testing showed that the presented system can improve evacuation times, achieving a measurable gain compared to scenarios where there is no information regarding fire evolution. Full article

Today’s rapidly increasing number and performance of Remotely Piloted Aircraft Systems (RPASs) and sensors allows for an innovative approach in monitoring, mitigating, and responding to natural disasters and risks. At present, there are 100s of different RPAS platforms and smaller and more affordable payload sensors. As natural disasters pose ever increasing risks to society and the environment, it is imperative that these RPASs are utilized effectively. In order to exploit these advances, this study presents the development and validation of a Natural Disaster Information System (NDIS), a geospatial decision-support framework for RPAS-based natural hazard missions. The system integrates a global geohazard database with specifications of geophysical sensors and RPAS platforms to automate mission planning in a generalized form. NDIS v1.0 uses decision tree algorithms to select suitable sensors and platforms based on hazard type, distance to infrastructure, and survey feasibility. NDIS v2.0 introduces a Random Forest method and a Critical Path Method (CPM) to further optimize task sequencing and mission timing. The latest version, NDIS v3.8.3, implements a staggered decision workflow that sequentially maps hazard type and disaster stage to appropriate survey methods, sensor payloads, and compatible RPAS using rule-based and threshold-based filtering. RPAS selection considers payload capacity and range thresholds, adjusted dynamically by proximity, and ranks candidate platforms using hazard- and sensor-specific endurance criteria. The system is implemented using ArcGIS Pro 3.4.0, ArcGIS Experience Builder (2025 cloud release), and Azure Web App Services (Python 3.10 runtime). NDIS supports both batch processing and interactive real-time queries through a web-based user interface. Additional features include a statistical overview dashboard to help users interpret dataset distribution, and a crowdsourced input module that enables community-contributed hazard data via ArcGIS Survey123. NDIS is presented and validated in, for example, applications related to volcanic hazards in Indonesia. These capabilities make NDIS a scalable, adaptable, and operationally meaningful tool for multi-hazard monitoring and remote sensing mission planning. Full article

With the continuous growth of global communication demands, the space-ground integrated optical network (SGION), composed of the satellite optical network (SON) and terrestrial optical network (TON), has gradually become a critical component of global communication systems due to its wide coverage, low latency, and large bandwidth. However, although the high directivity of laser communication can significantly enhance the security of data transmission, it still carries the risk of being eavesdropped on during the process of service routing. To resist eavesdropping attacks during service transmission in the SGION, this paper proposes a secure routing scheme named dynamic multipath secure routing (DMSR). In DMSR, a metric called the service eavesdropping ratio (SER) is defined to quantify the service leakage severity. The objective of DMSR is to reduce each service’s SER by switching its routing path proactively. To realize DMSR, heuristic algorithms are developed to sequentially search for optimal routing paths for service path switching in the TON and SGION. Finally, simulation results demonstrate that DMSR can achieve trade-offs between secure service transmission and network performance at different levels by adjusting its system parameters. Furthermore, the DMSR scheme significantly reduces the SER compared to the baseline schemes, while introducing acceptable increases in computation overhead and service latency. Full article

Digital banking has become part of everyday life in Aotearoa–New Zealand, offering convenience but also raising questions of trust, security, and long-term commitment. This study examines how service quality, security and privacy, user experience, emotional attachment, and perceived risk shape customer trust and commitment in digital banking platforms. Trust is positioned as a key mediating factor, guided by the Technology Acceptance Model, Commitment–Trust Theory, Service Quality Theory, and Perceived Risk Theory. An online survey of 111 digital banking users from diverse backgrounds was conducted, and Hayes’s PROCESS Model 4 was applied to test both direct and indirect relationships. The results show that security/privacy and emotional attachment are the strongest predictors of commitment, while service quality and user experience contribute indirectly through trust. This study adds three contributions. First, it explains customer commitment rather than intention. Second, it compares the indirect paths through trust from service quality, security and privacy, user experience, and emotional attachment within one model using bias corrected bootstrap confidence intervals. Third, in a sample with many experienced users, perceived risk shows no indirect effect, which suggests a boundary condition for risk focused models. Full article

The polder in this case study addresses several environmental issues, risk management concerns related to localities served by existing non-permanent dams, energy requirements that can meet a locality’s needs during the renewable energy transition, and their impacts on both rural and urban built environments. Cultural landscape preservation or solar regeneration on agricultural plots in Romania’s rural wetland areas focuses on traditionally inspired design, emphasising the technical versus humanistic approach as an optimal path through some inspiring “Dyads”. Briefly, the dyads are related to Bennett’s systematic approach to ensure the knowledge necessary for achieving understanding without experiencing it. With a two-way spiral, the defined methodology applies energy as solar photovoltaic technology to water-related natural aspects in the built environment without reducing or harming the relevant water management related to nature or built cultural heritage. The Solar Regeneration Monad “Nature -Energy- Built” is a holistic visual framework, replicable in any built environment for a “Built” regenerative culture, that enables the best solution to be identified for the conservation of cultural heritage values in an “Energy” transition context with “Nature”, biodiversity, or other water-related issues. Full article

This paper presents a kinematics-constrained grid-based path planning algorithm that generates real-time, safe, and executable trajectories, thereby enhancing the performance and reliability of autonomous vehicle parking systems. The grid resolution adapts to the minimum turning radius and steering limits, ensuring feasible motion primitives. The cost function integrates path efficiency, direction-switching penalties, and collision risk to ensure smooth and feasible maneuvers. A cubic spline refinement produces curvature-continuous trajectories suitable for vehicle execution. Simulation and experimental results demonstrate that the proposed method achieves collision-free and curvature-bounded paths with significantly reduced computation time and improved maneuver smoothness compared with conventional A* and Hybrid A*. In both structured and dynamic parking environments, the planner consistently maintained safe clearance and stable tracking performance under variations in vehicle geometry and velocity. These results confirm the robustness and real-time feasibility of the proposed approach, effectively unifying kinematic feasibility, safety, and computational efficiency for practical autonomous parking systems. Full article

Unmanned aerial vehicle (UAV) flight trajectories in complex environments are often affected by multiple uncertainties, making accurate prediction challenging. To address this issue, this study proposes a probabilistic four-dimensional (4D) trajectory prediction model based on Brownian bridge motion. The UAV’s flight from mission start to endpoint is modeled as a Brownian bridge stochastic process with endpoint constraints, where the mean function sequence is constructed from path planning results and UAV performance parameters. To incorporate operational feasibility, the concept of the spatiotemporal reachable domain from time geography is introduced to dynamically constrain reachable positions, while a truncated Brownian bridge distribution is used to model probabilistic positions in three-dimensional space. A simulation platform in a realistic 3D geographical environment is developed to validate the model. Case studies show that the proposed method achieves dynamic probabilistic trajectory prediction under mission constraints with strong adaptability and practicality. The results provide theoretical support and technical reference for trajectory planning, conflict detection, and flight risk assessment in the pre-tactical phase. Full article

This study presents an integrated geophysical and hydrogeological characterization of fault systems in the sandstone-hosted uranium deposit within the K₁b² Ore Horizon of the Bayin Gobi Basin. Employing 3D seismic exploration with 64-fold coverage and advanced attribute analysis techniques (including coherence volumes, ant-tracking algorithms, and LOW_FRQ spectral attenuation), the research identified 18 normal faults with vertical displacements up to 21 m, demonstrating a predominant NE-oriented structural pattern consistent with regional tectonic features. The fracture network analysis reveals anisotropic permeability distributions (31.6:1–41.4:1 ratios) with microfracture densities reaching 3.2 fractures/km² in the central and northwestern sectors, significantly influencing lixiviant flow paths as validated by tracer tests showing 22° NE flow deviations. Hydrogeological assessments indicate that fault zones such as F11 exhibit 3.1 times higher transmissivity (5.3 m²/d) compared to non-fault areas, directly impacting in situ leaching (ISL) efficiency through preferential fluid pathways. The study establishes a technical framework for fracture system monitoring and hydraulic performance evaluation, addressing critical challenges in ISL operations, including undetected fault extensions that caused lixiviant leakage incidents in field cases. These findings provide essential geological foundations for optimizing well placement and leaching zone design in structurally complex sandstone-hosted uranium deposits. The methodology combines seismic attribute analysis with hydrogeological validation, demonstrating how fault systems control fluid flow dynamics in ISL operations. The results highlight the importance of integrated geophysical approaches for accurate structural characterization and operational risk mitigation in uranium mining. Full article

Surface subsidence and seepage damage in surrounding soils induced by leakage from municipal water supply pipelines pose significant risks to urban infrastructure. To clarify how leakage water diffuses in unsaturated soils and to assess seepage damage potential, this study established a numerical model based on the Richards equation combined with the van Genuchten (VG) model. The model was validated against physical model tests using remolded Q3 loess, ensuring consistency in soil parameters and leakage conditions. Simulation results reveal that soil saturation evolution follows three stages—initial, rising, and stable—with preferential flow paths forming above the leakage point before gradually evolving into radial diffusion controlled by both pressure and gravity. The extent of the saturated zone increases with pipeline pressure, but the enhancement effect diminishes as pressure rises, reflecting the nonlinear water-retention characteristics of loess. Seepage damage risk was evaluated using the Terzaghi critical hydraulic gradient criterion. The results show that higher pressures enlarge the critical zone more rapidly, yet its ultimate radius stabilizes within approximately 2.3 m around the leakage point. Moreover, this study proposes that potential seepage damage may occur once effective saturation reaches about 85%, corresponding to the air-entry value of loess, thus providing a more conservative criterion for engineering risk assessment. Overall, the validated Richards-based numerical model reproduces the key features of leakage-induced unsaturated diffusion and offers practical guidance for identifying seepage-prone zones and mitigating subsidence hazards in municipal water supply systems. Full article

Antibodies are a cornerstone of the adaptive immune response, serving as key defenders against viral infections; however, they can also act as a double-edged sword, contributing to immune-mediated pathologies. This review advances a “Yin-Yang” framework to integrate the dual activities of antibodies. The protective ‘Yin’ functions are driven by high-affinity antibodies generated through processes like somatic hypermutation and class-switch recombination. These antibodies execute viral neutralization, activate the complement system, and engage Fc receptors (FcRs) to drive antibody-dependent cellular cytotoxicity (ADCC) and phagocytosis. These mechanisms form the immunological basis of effective vaccines, which aim to elicit durable and functionally specialized antibody isotypes like IgG and mucosal IgA. Conversely, the pathogenic ‘Yang’ of the response can be detrimental. This includes antibody-dependent enhancement (ADE) of infection, notably observed with flaviviruses, and the development of autoimmunity through mechanisms like molecular mimicry and bystander activation, which can lead to conditions such as multiple sclerosis and Guillain-Barré Syndrome. The balance between protection and pathology is tipped by a confluence of factors. These include viral evasion strategies like antigenic mutation and glycan shielding, as well as host-based determinants such as genetic polymorphisms in FcRs, immune history, and the gut microbiome. Understanding these molecular determinants informs the rational design of next-generation interventions. Promising strategies, such as Fc-region glyco-engineering and the design of tolerogenic vaccines, aim to selectively promote protective functions while minimizing pathological risks, offering a clear path forward in combating viral threats. Full article

Recent technological breakthroughs have enabled multidimensional phenotyping, with unprecedented single-cell resolution and genome-wide coverage, across multiple osteoarthritis (OA)-relevant tissues, such as articular cartilage, synovium, infrapatellar fat pad, and subchondral bone. The majority of the single nucleotide variations (SNVs) that have been associated with OA are located in non-protein coding regions and confer risk for disease by altering the expression level, instead of the amino acid sequence of the gene product. These data have shaped the concept of OA as a polygenic disease, where genetic factors disrupt the chromatin landscape in disease-relevant cells, leading to aberrant expression of effector genes. Pharmacologic manipulation of the OA-driving epigenetic landscape has recently emerged as an attractive path for the development of disease-modifying drugs. Novel clustered regulatory interspaced short palindromic repeats (CRISPR)-based technologies provide opportunities for precise epigenetic editing at the desired genomic regions and may allow a targeted transcriptional regulation of disease-relevant genes in disease-relevant cells. The aim of the present narrative review is to summarize the emerging data on the role of epigenetic factors and chromatin structure as calibrators of the risk for developing OA and to discuss the opportunities and challenges arising from the use of chromatin landscape to guide drug discovery. Full article

The social-ecological resilience of rural settlements refers to their ability to resist and mitigate the risks posed by internal and external disturbances, and to utilize the external environment to achieve a new equilibrium state. Amid rapid urbanization, it is of great significance for mountainous settlements to improve their risk resistance and development ability. Taking Dong’an Town in Chengkou County, located in the eastern part of Qinling–Bashan Mountains in southwestern China, as the research object, this study constructs an evaluation index system for rural residential resilience based on social-ecological resilience theory. It explores the resilience level of rural residences in mountainous areas from the dimensions of internal resilience and external environmental resilience and scientifically proposes an optimization path for the spatial layout of rural residences. This study provides a reference for optimizing the rural living environment, promoting spatial equity, and improving people’s livelihood according to local conditions. The results showed that: (1) The overall level of security resilience of rural settlements in Dong’an Town was relatively high, with 221 patches above the security level, accounting for 19.53% of the total area of the town. (2) The rural residents in Dong’an Town can be categorized into three types: core structure optimization, peripheral system upgrading, and relocation and withdrawal. Different types of rural settlements adapt to internal and external resource conditions and select optimal spatial layout paths according to local conditions. Full article

Urban drone operations are exposed to unpredictable risks, including engine failure and deliberate signal interference. A recent and ongoing disruption in Jeddah, Saudi Arabia, has seen widespread GPS spoofing that misleads devices by hundreds of kilometers, illustrating how fragile unmanned aerial vehicle (UAV) operations can become when over-reliant on GNSS-based navigation. Such disruptions highlight the urgent need for contingency planning in drone traffic management systems. This study introduces a safety-aware pre-flight path planning framework that proactively integrates emergency landing and GPS fallback options into UAV trajectory pre-flight planning. The planner considers proximity to predesignated emergency landing zones, communication coverage, and airspace restrictions, enabling UAVs to safely complete their operations. The approach is evaluated across realistic mission profiles such as delivery, inspection, and surveillance. Results show that the planner successfully maintains mission feasibility while embedding emergency readiness throughout each flight. This work contributes toward safer, failure-resilient drone integration in urban airspace, ensuring that contingency plans are proactively incorporated into path planning before the failure even occurs. Full article