Search Results (828)

High-skilled labor plays an important role in regional economic development, yet accurately identifying its influencing patterns remains challenging due to complex factor interactions, spatial spillover effects, and fuzzy boundaries among urban characteristics. Traditional regression-based approaches primarily focus on isolated linear effects, making it difficult to capture multi-factor combinatorial relationships underlying talent agglomeration. To address these limitations, this study proposes a spatially aware fuzzy association rule mining framework by integrating soft-gated spatial weighting and concept stability theory. Using data from the Sixth and Seventh National Population Censuses and the China City Statistical Yearbook, the framework is applied to the Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), and Middle Reaches of the Yangtze River (MRYR) regions from 2010 to 2020. The results show that the associative patterns of high-skilled labor evolved substantially across regions. In the BTH region, dominant factors shifted from administrative hierarchy and environmental amenities to stronger interactions between economic growth and talent inflow. In the YRD region, economic dynamism gradually replaced static geographic advantages, while in the MRYR region, market-oriented drivers increasingly surpassed administrative-led resource concentration. Overall, the findings suggest a transition from single-factor dependence to multi-factor coupled patterns in China’s regional talent agglomeration. Full article

Sustainable land-use regulation in historical and cultural cities requires balancing heritage conservation, development demand, cropland retention, and urban–rural spatial restructuring. However, the stage-wise reorganization of urban–rural construction land under these coupled pressures remains insufficiently understood. Taking Jingzhou District, China, as a case study, this study uses land-use data from 2000, 2005, 2010, 2015, and 2020 and integrates stage-wise random-forest analysis, consistency-based interaction-network mining, and multi-scenario simulation within the intPLUS framework. Population, GDP, and areal-water distance layers were matched to the corresponding stage-terminal snapshots where applicable, whereas 2020 POI data were used as contemporary spatial-context proxies. From 2000 to 2020, urban industrial land (UIL) expanded from 16.63 to 46.42 km², increasing by approximately 179.1%, whereas rural settlements (RS) increased more moderately from 56.59 to 60.27 km², increasing by approximately 6.5%. The stage-wise RF and interaction-network results show that UIL and RS followed different spatial association structures, with stronger UIL self-reinforcement and stronger RS self-continuity in the later stage. Historical validation showed overall accuracy values of approximately 91% and Kappa values around 0.80, but FoM values remained relatively low, ranging from 0.098 to 0.176. Class-specific mapping accuracy was higher for RS (81.90–82.37%) than for UIL (55.20–66.93%), indicating a weaker performance in locating UIL change. Therefore, the 2035 simulations should be interpreted as parameter-conditioned regulatory comparisons rather than deterministic pixel-level forecasts. The scenario results indicate that the conservation-oriented limited growth was associated with the restricted UIL expansion and better cropland retention under the prescribed demand and constraint settings, while the RS reduction occurred only under explicit village-consolidation and construction-land quota reallocation assumptions. By distinguishing UIL and RS, this study provides differentiated regulation-oriented evidence for sustainable land-use governance in historical and cultural cities. Full article

The continuous analysis of ground deformation is essential for both the assessment of natural hazards and the monitoring of human-induced activities. In this study, we present the results of a Persistent Scatterer Interferometry (PSI) analysis of ground deformations in the region of Cluj-Napoca, Romania. The PSI was performed using more than 10 years of Sentinel-1 ascending and descending Synthetic Aperture Radar data from 2014 to 2025, using a dual master approach. Results show significant displacements at many locations, including recently built-up areas at the edges of the city, often caused by the combined effect of anthropogenic activities and geological conditions. In this study, we highlight three case studies: the surroundings of a reclaimed mine, subsidence induced by dewatering, and a large-area, slow landslide, wherein we examined natural and anthropogenic influences. The accurately mapped and quantified ground deformations can be used for a better understanding of the geological processes and assessing the risk of the urban development in the area. Full article

This study examines how smart city discourse is structurally configured across different contexts from the perspective of policy mobility. To this end, three types of data were analyzed: South Korean policy reports, South Korean academic literature, and global academic literature. Based on these sources, text datasets were constructed and analyzed using text mining-based semantic network analysis to identify key concepts and their relational structures. The results show that while similar keywords appear across datasets, differences are observed in the relative positions and relational patterns of key concepts. In South Korean policy reports, implementation- and operation-related concepts such as “service,” “information,” and “management” exhibit relatively higher centrality. In South Korean academic literature, “planning,” “policy,” “research,” and “technology” appear alongside governance- and actor-related concepts, indicating broader relational configurations. In global academic literature, concepts such as “sustainable,” “social,” “governance,” and “policy” show relatively similar levels of centrality, suggesting the coexistence of multiple dimensions within the discourse. These findings suggest that smart city discourse may be configured differently depending on institutional and discursive contexts, rather than converging into a single uniform structure. However, the observed differences should not be interpreted solely as reflecting national contextual differences, as variations in dataset composition may also have partially influenced the results. By conceptualizing the smart city as a structured policy discourse, this study contributes to understanding how policy-related concepts may be selectively emphasized and reconfigured across contexts. Methodologically, the study demonstrates the applicability of semantic network analysis for examining relational patterns within smart city discourse across different data types and contexts. Full article

Burden of diseases measured as disability-adjusted life years (DALYs) per 100,000 people can be mined from public domain data, when they are made available by population health surveillance systems. This can be analysed to allow insightful comparisons with the national average, and to understand differences in trends between the sexes, age groups, time periods, geographic regions, and sub-regions. In this illustrative case study, we have analysed the Scottish burden of disease database to understand what ailed the population of the Grampian region before the COVID-19 pandemic. We have identified that selected cancers, ischaemic heart disease, Alzheimer’s disease and other dementias are amongst the highest contributors to the burden; that drug use disorders and colorectal cancer are showing worsening trends and require health promotion and disease prevention measures from ages 15 and 25, respectively, especially in Aberdeen City; and that males are more vulnerable to atrial fibrillation and flutter, diabetes mellitus, oesophageal cancer, and self-harm, while females are more vulnerable to cerebrovascular and chronic obstructive pulmonary diseases. We demonstrate the usefulness of our analysis and methodology for the wider health system, allowing targeted medical research investments and coordinated response from public health and health service delivery. We also show the need for up-to-date surveillance data, forecasts, and evidence on the impact of interventions to be made available widely. Full article

This study focuses on 28 mining cities with the aim of promoting their sustainable development, particularly with regard to disaster resilience. The entropy-weight Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model is adopted to measure comprehensive disaster reduction capacity, and spatial analysis/econometric models are used to reveal its spatial distribution pattern, correlation characteristics, and driving mechanism. The region’s comprehensive disaster reduction capacity is generally higher in the west and north and lower in the east and south. Significant differences are observed among cities with obvious spatial agglomeration characteristics, and both high- and low-value areas show a contiguous spatial structure. Economic development and disaster prevention infrastructure construction are the main factors driving the spatial differentiation of disaster reduction capacity. Geological disaster risk exerts a significant negative effect, and various regions exhibit stable positive spatial spillover. These results provide a scientific basis for formulating differentiated disaster reduction strategies and will facilitate the sustainable development of disaster-prone regions. Full article

Assessing the ecological and environmental quality of old industrial cities is crucial for understanding the spatial heterogeneity of ecological quality and its associated factors during regional transformation. Taking Tangshan, a typical old industrial city in China, as a case study, this study employed Landsat 8/9 remote sensing imagery and multi-source auxiliary data from 2015 to 2024 to calculate annual Remote Sensing Ecological Index (RSEI) values using a unified multi-year standardization and principal component analysis framework. Global and local Moran’s I analyses were conducted to examine spatial clustering patterns, and the Optimal-Parameter Geographical Detector (OPGD) was used to quantify the spatial correspondence between RSEI and selected natural and anthropogenic explanatory factors. The results indicate the following. (1) The mean RSEI in Tangshan fluctuated between 0.34 and 0.54 from 2015 to 2024, exhibiting significant interannual variability. (2) Higher RSEI values were primarily distributed in the northern mountainous and southern coastal ecological zones, while lower values were concentrated in the central and eastern industrial-mining zones. (3) The global Moran’s I was significantly positive in all years (0.702–0.778, p = 0.001), indicating the persistence of spatial clustering; the proportion of non-significant local spatial units decreased from 72.00% in 2015 to 69.46% in 2024. (4) Land use/land cover (LULC) exhibited the most consistently high explanatory power. Elevation (ELE), nighttime light (NTL), and built-up intensity (BUILT) also formed a leading group of spatially associated factors, although their relative ranking varied between the optimal-parameter results and the robustness analysis. Slope (SLOPE), annual precipitation (Pre), and annual mean temperature (Tmean) generally showed relatively lower explanatory power. Interaction detection showed that pairwise factor combinations generally had higher q values than individual factors, with LULC × ELE showing consistently high explanatory power in representative years. This study provides a scientific reference for ecological and environmental monitoring and differentiated management in old industrial cities. Full article

This study examines the persistence, change, and discontinuity of human settlements in the northern Stig Plain along the Danube in Serbia. It examines how natural conditions, together with historical events and the strategic imperatives of specific periods, have shaped the establishment, development, decline, and abandonment of settlements in this landscape, as well as their change and transformation. Particular attention is given to the Roman city of Viminacium, now largely buried beneath fertile farmland and affected by mining activity. The research integrates theoretical perspectives on landscape, human–environment relations, and processes of discontinuity and change with insights into Roman urban planning and overall settlement dynamics, contextualised through the environmental and historical development of the landscape. It considers why Viminacium remained the only major urban centre in the plain and why no later settlement developed directly above it, reexamining whether this absence can be understood as a form of landscape discontinuity. The findings emphasise the strong influence of natural factors, while suggesting that the urban potential of the fertile Stig Plain could only be fully realised in the Roman period, through the establishment of a legionary fortress supported by advanced technology and organised labour, and guided by strategic objectives. From a heritage perspective, the study also examines the definition of landscape boundaries, highlighting Viminacium’s legacy as an integrative element that brings together remains from multiple periods into a unique and evolving cultural landscape worthy of preservation, though one that faces ongoing challenges in sustainable management. Full article

Near-bit multi-parameter MWD (measurement while drilling) is a key technology for achieving precise and efficient directional drilling in underground and tunnel engineering. The near-bit multi-parameter MWD method was studied, and a “center + side wall” distributed measurement scheme was proposed, based on an analysis of special application scenarios in underground and tunnel engineering. The transmission characteristics of Bluetooth wireless signals in water were investigated. An analysis of the underwater Bluetooth signal link was conducted. When the transmission distance is 100 mm, the received signal strength is −17.5 dBm, and the link margin is 69.5 dB. Wireless Bluetooth was used to transmit the near-bit data. A Bluetooth wireless communication simulation model was established using ANSYS software, and the influence of transmission power, transmission medium, and transmission distance on the Bluetooth signal strength was analyzed. The results indicate that: (1) the received signal strength increases with transmission power, and appropriately increasing the transmission power can improve the effect of Bluetooth wireless communication and extend the communication distance. (2) When the transmission medium is water, the received signal is unstable, and the echo loss curve shows a high and low oscillation form, presenting a frequency shift feature; when the transmission medium is air, the received signal is relatively stable, and the echo loss curve shows a parabolic form. The echo loss of Bluetooth wireless signal in water transmission is significantly higher than that in air transmission, indicating that the Bluetooth signal attenuates more rapidly when transmitted in water. (3) When the transmission distance increases near the optimal transmission frequency of 2.4 GHz, the echo loss increases accordingly, and the received signal strength of the wireless receiving module gradually decreases. The theoretical analysis, simulation, and indoor test results are in good agreement. The reasonable Bluetooth transmission power is 1 mW, and the transmission distance is 100 mm. After completing the overall scheme design and simulation analysis optimization, the structure, circuit, and program development were carried out, and the near-bit multi-parameter MWD device was developed. A laboratory water supply test was conducted, and the power supply, collection, and wireless transmission were all normal. A drilling test was carried out at an underground engineering of a coal mine in Wuhai City, achieving a drilling depth of 2328 m. A continuous and stable collection of various parameters such as WOB (weight on bit), torque, rotation speed, vibration, and gamma was carried out. A wireless transmission channel for near-bit data was established across the screw drilling tool. It can provide key technical support for the research and development of near-bit MWD in underground and tunnel engineering. Full article

The dual urban–rural structure severely restricts sustainable and equitable development in China. While agricultural talent policies aim to break down these barriers, their actual net effects and spatial spillovers remain unclear due to the limitations of traditional linear models in handling complex, high-dimensional confounding factors (the research gap). The objective of this study is to accurately identify the causal impacts of these policies on urban–rural integration across 31 major Chinese cities from 2011 to 2024. We utilized text mining to construct a continuous policy intensity index and established a multidimensional integration evaluation system. Crucially, a double machine learning (DML) approach was employed to isolate the net policy effects. The results demonstrate the following: (1) Overcoming the negative bias of classical methods, the DML reveals a significant positive causal effect of talent policies on local urban–rural integration. (2) However, strong policies in central cities create significant negative spatial spillovers (siphon effects) on neighboring peripheral regions, exacerbating spatial injustice. (3) Feature analysis indicates that agricultural productivity is the primary driver of integration, while policies serve as essential catalysts. These findings emphasize that sustainable urban–rural integration requires a shift from zero-sum local competition to coordinated regional talent governance. Full article

False data injection (FDI) cyberattacks pose a growing threat to modern power distribution systems in smart cities by manipulating state-estimation processes and provoking covert voltage violations that traditional defense mechanisms fail to detect. Recent industry data indicate that coordinated FDI attacks can distort measurement sets by as little as 3–7%, yet trigger voltage deviations exceeding 10% in vulnerable feeders, resulting in operational instability, unnecessary load curtailments, and elevated outage risk. To address these challenges, this paper proposes a quantum-accelerated digital twin (QDT) framework that integrates quantum optimization algorithms with a high-fidelity digital twin (DT) of the distribution system to detect, localize, and remediate FDI-induced cyberattacks in real time. The rationale behind the approach lies in the superior combinatorial search capability of quantum solvers, which accelerates the identification of falsified measurement vectors and optimal corrective control actions compared with classical methods. In addition, the framework introduces an innovative Bitcoin-mining-oriented virtual energy storage (BMOVES) mechanism that treats mining facilities as dynamically controllable, fast-response electrical loads within smart city demand–response programs. By modulating mining power consumption with sub-second granularity, the proposed BMOVES resource provides up to 18–45% flexible capacity during attack scenarios, enabling voltage restoration without relying on conventional energy storage assets. The unified QDT + BMOVES architecture is validated using the 136-bus Brazilian distribution system, a realistic benchmark for cyber–physical resilience studies. Simulation results demonstrate over 99% FDI detection accuracy, up to an 82% reduction in peak voltage violations, and restoration of operational limits 11 times faster than state-of-the-art classical methods. These findings highlight the transformative potential of integrating quantum computing, digital twins, and nontraditional flexible assets to enhance cyber-resilient power infrastructure in future smart cities. Full article

As unique settlements born of industrial civilization, workers’ residential areas carry rich heritage and the collective memory of communities they contain, endowing them with distinct historical and cultural significance. Assessing and enhancing their resilience are essential for both heritage preservation and sustainable community development. Despite the prevalence of such neighborhoods in China’s old industrial cities, systematic evaluation of their comprehensive resilience remains limited. To address this research gap, we take Taiyuan Mining Machinery Dormitory as a case study. Integrating multi-source spatial and demographic data, we construct a resilience evaluation framework based on the DPSIR model, comprising five criterion layers, 22 element layers, and 49 indicators. Combined with an obstacle degree model, it identifies key factors constraining resilience. Results indicate that comprehensive resilience of the study area is at a “moderate” level, with the “response” subsystem scoring notably low, reflecting insufficient stakeholder attention. Major obstacles include per capita shelter area, building quality, road accessibility, residents’ willingness to participate in governance, and organizational leadership capacity. Based on these findings, targeted strategies are proposed to enhance resilience amid increasing risks. This study contributes to community resilience theory and offers practical insights for the conservation and regeneration of workers’ residential areas under urban renewal. Full article

In light of the accelerating process of global urbanization, the quality of cultural ecosystem services (CES) in urban parks has become a core metric for efforts to promote urban livability and sustainable cities. However, previous research has failed to consider the differential impacts of the external environment across various travel scenes. In this study, 32 parks in Chengdu serve as the empirical data, and public CES perception data are extracted from social media comments via text mining. Based on a unified 15 min time threshold, we delineate the service scope for four travel scenes and employ geographically weighted regression and piecewise regression models to analyze the spatial heterogeneity, driving mechanisms and threshold effects associated with the relationship between external environmental factors and park CES. The findings indicate that the external environment’s influence on CES exhibits a “scene-factor-scale” adaptation pattern. Walking scenes are influenced primarily by land-use and population factors; in contrast, cycling scenes rely on the availability of shared bicycle facilities, and public transport and driving scenes are driven by economic vitality and traffic-support factors, respectively. Five critical thresholds are identified, including a 40% impervious surface area. This research proposes scene-based optimization strategies and helps enhance the “external environment–travel behavior–spatial characteristics” coupling framework, thereby serving as a scientific reference for efforts to improve 15 min living circles. Full article

The Dongchuan District in Kunming City is located in the transition zone between the Yunnan–Guizhou Plateau and the Sichuan Basin. As a region with a copper mining history of over 2000 years, the district has experienced frequent landslides that pose serious threats to human lives, property, and ecological sustainability. Therefore, it is essential to compile a comprehensive landslide inventory and analyze the relationships between landslide spatial distribution and influencing factors for geological hazard prevention. High-resolution remote sensing imagery was interpreted to establish a landslide inventory, based on which the spatial distribution and geometric characteristics of landslides were systematically analyzed. The results show that a total of 1623 landslides were identified, with a total area of 10.36 km². Landslides predominantly occur at elevations of 1000–2000 m, on slopes of 20–45°, with aspects of 255–285°, and relief between 150 and 400 m, in areas with annual rainfall below 825 mm, within 1000 m of rivers and 3000 m of fault lines, and 1000–5000 m of mines. Four landslide clusters were delineated along the Xiao River Fault, highlighting the significant influence of the fault on the spatial distribution of landslides. Most landslides are longitudinal in planform, with travel distances (L) of 50–450 m and heights (H) from 25 to 350 m, both exhibiting allometric scaling with volume. The mean H/L ratio is 0.56 (corresponding to a mean reach angle of 29°), significantly higher than that in Baoshan City (21°). The results provide insights into landslide initiation mechanisms and spatial distribution patterns on the northern margin of the Yunnan–Guizhou Plateau, offering valuable data for landslide hazard assessment and sustainable regional development. Full article

The urban trade in non-timber forest products (NTFPs) plays a key role in sustaining livelihoods in the Global South, while also suggesting potential pressure on resource supply systems. This study provides an integrated analysis of NTFP diversity, market structure, economic importance, and perceived drivers of resource decline in Kolwezi, a rapidly expanding mining city where such dynamics remain poorly documented. Data were collected through surveys conducted with 35 sellers across two major urban markets and 384 consumers from different neighbourhoods and analysed using descriptive and inferential statistics to examine patterns, associations, and socio-demographic influences. A total of 65 NTFP species were recorded, including 49 plant, 14 animal, and 2 fungal species, reflecting strong dependence on Miombo ecosystems. Medicinal (59.3%) and food uses dominate, with multifunctional species such as Bobgunnia madagascariensis (Desv.) J.H.Kirkbr. & Wiersama, Canarium schweinfurthii Engl., Terminalia mollis M.A.Lawson, Gardenia ternifolia subsp. jovis-tonantis (Welw.) Verdc., and Albizia antunesiana Harms, playing a central role in both household use and market supply. The trade is largely female-dominated (79.1%) and constitutes a major component of the informal urban economy, with monthly incomes ranging from USD 9 to 429.3, primarily driven by sales volume rather than unit price. However, the sector is constrained by structural and logistical limitations, including remoteness of supply areas, seasonality, and limited value addition. The perceived declining availability of high-use-value species, attributed by respondents to deforestation, mining expansion, and overexploitation, highlights perceived sustainability concerns. These pressures are perceived differently across socio-demographic groups, indicating heterogeneous understandings of environmental change. Overall, the results indicate a perceived mismatch between rising urban demand and declining resource availability, which may reflect an emerging socio-ecological imbalance between urban demand and perceived resource availability. Addressing these challenges requires integrated strategies that combine the domestication of priority species, the development of processing chains, improved infrastructure, and strengthened governance mechanisms. Such approaches are essential to reconcile livelihood support with the sustainable management of NTFPs in rapidly transforming urban landscapes. Full article