Search Results (1,673)

This study presents the results of preliminary documentation and radon tracer investigations conducted at the “Aurelia” Mine in Złotoryja. Measurements of ²²²Rn activity concentrations were carried out between 17 March and 26 August 2023, while terrestrial laser scanning (TLS) for mapping purposes was performed on 16 November 2024. The radon data exhibited a consistently right-skewed distribution, with skewness coefficients ranging from 0.9 to 8.2 and substantial standard deviations, indicating significant data dispersion. Outliers and extreme outliers were identified as key factors influencing average radon activity concentrations from April through August, whereas data from March displayed homogeneity, with no detected anomalies. The average ²²²Rn activity concentrations recorded from March to July ranged from 51.4 Bq/m³ to 65.9 Bq/m³. In contrast, July and August showed elevated average values (75.8 Bq/m³ and 5784.8 Bq/m³, respectively) due to the presence of outliers and extreme values. Upon removal of these anomalies, the adjusted means were 73.8 Bq/m³ and 1003.6 Bq/m³, respectively, resulting in reduced skewness and improved representativeness. These findings suggest that the annual average radon concentrations at the “Aurelia” Mine remain compliant with the regulatory threshold of 300 Bq/m³ set by the Atomic Law Act, with exceedances likely related to atypical or rare geophysical phenomena requiring further statistical validation. August exhibited a significant occurrence of outliers and extreme outliers in ²²²Rn activity concentration data, particularly concentrated between the 13th and 17th days of the month. This anomaly is hypothesized to be associated with geological processes, notably mining-induced seismic events within the LGOM (Legnica–Głogów Copper District) region. It is proposed that periodic transitions between tensional and compressional phases within the rock mass, triggered by mining activity, may lead to abrupt increases in radon exhalation, potentially occurring before or after seismic events with a magnitude exceeding 2.5. Although the presented data provide preliminary evidence supporting the influence of tectonic kinematic changes on subsurface radon dynamics, further systematic observations are required to confirm this relationship. At the current stage, the hypothesis remains speculative but may contribute to the broader understanding of radon behavior in geologically active underground environments. Complementing the geochemical analysis, TLS enabled detailed geological mapping and 3D spatial modeling of the mine’s underground tourist infrastructure. The resulting simplified linked data model—integrating radon activity concentrations, geological structures, and spatial parameters—provides a foundational framework for developing a comprehensive GIS database. This integrative approach highlights the feasibility of combining tracer studies with spatial and cartographic data to improve radon risk assessment models and ensure regulatory compliance in underground occupational settings. Full article

Background: Spinal anesthesia is a widely used technique for pain control in surgical procedures, requiring effective drug distribution within the cerebrospinal fluid (CSF) for optimal outcomes. The distribution is influenced by injection parameters such as needle diameter and injection speed, which, if not optimized, can reduce efficacy or cause side effects. This study investigates how these parameters affect drug distribution in the CSF using computational fluid dynamics (CFD). Material Methods: An anatomically accurate three-dimensional model of the CSF space was created using MRI data. Simulations were performed using three needle tips (22 G, 25 G, 27 G) and different injection rates at the L4–L5 vertebral level. The model included physiological CSF oscillations from cardiac and respiratory cycles. Drug dispersion was analyzed in terms of spatial distribution and concentration changes over time. Results: The findings obtained show that the combination of a large-gauge needle (22G) and high injection speed provides wider distribution within the CSF and more effective transport to the cranial regions. On the other hand, with a small-gauge needle (27G) and low injection speed, the drug remained more localized, and access to the upper spinal regions was limited. Additional parameters such as injection duration, direction, and flush applications were also observed to significantly affect distribution. Conclusions: CFD modeling reveals that injection parameters significantly affect drug dispersion patterns in spinal anesthesia. Optimizing these parameters may improve therapeutic outcomes and reduce complications. The model provides a foundation for developing personalized intrathecal injection protocols. Full article

Urbanization profoundly transforms ecosystems, often resulting in habitat loss and biodiversity decline. Urban spontaneous plants, which are established naturally without human intervention, play a critical role in urban ecosystems by providing habitats, mitigating urban heat islands, and acting as indicators of environmental changes. Multidimensional urbanization, encompassing vertical and horizontal scale, exerts a significant influence on the biodiversity of green space. While previous studies have extensively examined the effects of horizontal spatial scales (such as land use and population density), the impacts of vertical spatial scales remain understudied. To elucidate the spatial patterns and driving factors of spontaneous plant diversity under multidimensional urbanization, we conducted a comprehensive survey of spontaneous plants across Changchun, a rapidly urbanizing city in northeast China. We established 1147 herbaceous plots within 245 urban green space patches across 38 sites and analyzed the effects of multidimensional urbanization metrics on spontaneous plant diversity. A total of 408 species of spontaneous plants were recorded, with herbs as the dominant life-form (89.2%), 322 are native species (78.9%), and 21.1% non-native species (of which 65.1% are invasive), primarily dispersed by autochory. Significant differences in plant diversity indices were observed across various urban green spaces and habitat types in Changchun, with native plant diversity generally highest in square green spaces and scrub gaps, while non-native plant diversity was most prominent in brownfield sites and showed no significant variation among habitat types. Regression analyses revealed that, in addition to patch characteristic factors (including patch area, perimeter–area ratio, and landscape shape index), the richness of total, native, and autochorous spontaneous plants was primarily influenced by vertical urbanization (as indicated by building volume), with building volume positively associated with species richness. In contrast, the richness of non-native and anemochorous plants was also significantly affected by horizontal urbanization factors, such as the proportion of impervious surface within a 100 m buffer zone and distance from patch to city center. The results reveal distinct spatial patterns of spontaneous plant diversity driven by both urbanization of horizontal spatial scales and vertical spatial scales. Our study provides new insights into the interplay between multidimensional urbanization and biodiversity, offering a theoretical foundation for integrating biodiversity conservation into sustainable urban planning and ecosystem management. Full article

Against the backdrop of rapid new urbanisation and the ongoing integration of urban and rural areas, the evolving spatial dynamics between public service facilities and population distribution have increasingly garnered scholarly interest. The present study employs a grid-based spatial unit and a coupling coordination model as a foundation. This model integrates POI data, Baidu heat maps, and other sources of spatial and temporal information. The objective is to explore the dynamic matching pattern of public service facilities and population distribution. The study’s findings are as follows: The population within the core urban area displays a strong propensity for agglomeration during the morning and evening peak hours, thereby forming a highly coordinated public service network characterised by high-density and piecemeal distribution of public service facilities. The population residing within the transition zone between urban and rural areas is commuting in a substantial number, and the relationship between the supply of and demand for facilities demonstrates cyclical fluctuations. Local areas are subject to time-periodic pressure on the supply of and demand for facilities. In rural areas, due to the continuous population outflow and dispersed residence, the layout of service facilities is fragmented, exhibiting the island effect. The study reveals a structural contradiction between traditional homogeneous planning and the gradient difference between urban and rural areas, providing a scientific basis for Shandong Province to promote new urbanisation and rural revitalisation strategies in an integrated manner. Full article

Social facilities play a crucial role in urban development. However, there are currently few studies on the rationality of the spatial layout of social facilities in inland coastal cross-river cities. In view of this, we choose Nanjing City, China as an example, based on the point of interest (POI) data of social facility, and use the techniques including kernel density analysis, standard error ellipses, and spatial correlation analysis to systematically investigate the spatial distribution characteristics and patterns of social facilities in Nanjing. The research results show that there are significant differences in the spatial distribution of different types of social facilities in Nanjing, and the overall layout presents a pattern of denser distribution in the central urban area and more dispersed distribution in the peripheral areas. Shopping and transportation facilities are mostly concentrated in the core area of the main urban district, medical facilities are relatively concentrated, and cultural and educational facilities are located in all regions. The expert weighting analysis based on the Delphi method indicates that the influence weights of shopping consumption and transportation facilities on urban facilities are relatively greater than those of other factors. Overall, the social service facilities in the central urban area of Nanjing are well developed and well arranged, whereas the construction of facilities in several new districts and suburbs still needs to be further strengthened. The findings offer a scientific foundation for improving the layout of social facilities and urban planning in Nanjing, while also serving as a valuable reference for the development of other inland coastal cities spanning rivers. Full article

Even though clinoptilolite mineral is the most important natural zeolite for technical applications, the molecular-level insights and detailed knowledge of their true local structures and adsorption behavior are largely lacking. An experimental determination of their surface structures, in particular, could be very challenging due to the sensitivity of some facets to temperature and impurities. In this study, we present a robust multiscale modeling framework to investigate the adsorption of 5-fluorouracil, an anticancer drug, on dispersion-corrected density functional theory (DFT-D3)-optimized Na-clinoptilolite surfaces. Using a combination of interface force field and polymer consistent force field-based molecular dynamics with simulated annealing and parallel replica sampling, followed by DFT-D3 optimizations, we explore a wide configurational space of surface–molecule interactions. Our results show that Na-clinoptilolite surfaces support very strong adsorption, with adsorption energies ranging from −430.0 to −174.4 kJ/mol. Surface models with exposed Na cations consistently exhibit stronger binding, in contrast to their known steric hindrance effects in bulk environments. Furthermore, cation-free surfaces displayed relatively weaker interactions, yet configurations exposing the 8-membered rings (8 MR) demonstrated more favorable adsorption than those exposing 10 MR channels due to enhanced hydrogen bonding and spatial and entropic confinement effects. These findings reveal the importance of surface composition, local geometry, and configurational sampling in determining adsorption performance and lay the groundwork for future studies on cation-specific and multicationic clinoptilolite systems. Full article

Historically, traditional transportation planning has promoted public policies focused on building and maintaining infrastructure for private cars to improve travel efficiency. This approach presents a significant challenge for cities in the Global South due to their unique socioeconomic conditions and urban development patterns. Dedicated public transport infrastructure can make better use of the road network by moving more people and reducing congestion. Beyond its environmental benefits, it also provides the population with greater accessibility, creating new development opportunities. This study uses Mexicali, Mexico, a medium-sized city with dispersed urban growth and a high dependence on cars, as a case study. The goal is to identify the relationship between the supply of public bus routes and actual work-related commuting patterns. The methodology considers that, given the scarcity of economic resources and prior studies in the Global South, using Geographic Information Systems (GIS) for the spatial analysis of travel is a key tool for redesigning more inclusive and sustainable public transport systems. Specifically, this study utilized origin–destination survey data from 14 urban areas to assess modal coverage, work-related commuting patterns, and the spatial distribution of employment centres. The findings reveal a marked misalignment between the existing public transport network and the population’s travel needs, particularly in marginalized areas. Users face long travel times, multiple transfers, low service frequency, and limited connectivity to key employment areas. This configuration reinforces an exclusionary urban structure, with negative impacts on equity, modal efficiency, and sustainability. The study concludes that GIS-based spatial analysis generates sufficient evidence to redesign the public transport system and reorient urban mobility policy toward sustainability and social inclusion. Full article

Mass gatherings such as the annual Hajj pilgrimage in Makkah, Saudi Arabia, generate extreme, short-term anthropogenic emission loads with significant air quality and public health implications. This study assesses the spatiotemporal dynamics of key atmospheric pollutants—including nitrogen dioxide (NO₂), carbon monoxide (CO), sulfur dioxide (SO₂), formaldehyde (HCHO), and aerosols—across Makkah and its holy sites before and during the Hajj seasons of 2023 and 2024. Using high-resolution Sentinel-5P TROPOMI satellite data, pollutant fields were reconstructed at 100 m spatial resolution via cloud-based geospatial analysis on the Google Earth Engine. During Hajj 2023, spatially resolved NO₂ concentrations ranged from 15.4 μg/m³ to 38.3 μg/m³ with an average of 24.7 μg/m³, while SO₂ during the 2024 event peaked at 51.2 μg/m³ in key hotspots, occasionally exceeding World Health Organization (WHO) guideline values. Aerosol index values showed episodic surges (up to 1.43), particularly over transportation corridors, parking areas, and logistics facilities. CO concentrations reached values as high as 1069.8 μg/m³ in crowded zones, and HCHO concentrations surged up to 9.99 μg/m³ during peak periods. Quantitative correlation analysis revealed that during Hajj, atmospheric chemistry diverged from urban baseline: the NO₂–SO₂ relationship shifted from strongly negative pre-Hajj (r = −0.74) to moderately positive during the event (r = 0.35), while aerosol–HCHO correlations intensified negatively from r = −0.23 pre-Hajj to r = −0.50 during Hajj. Meteorological analysis indicated significant positive correlations between wind speed and NO₂ (r = 0.35) and wind speed and CO (r = 0.35) during 2024, demonstrating that extreme emission rates overwhelmed typical dispersive processes. Relative humidity was positively correlated with aerosol loading (r = 0.37), pointing to hygroscopic growth patterns. These results quantitatively demonstrate that Hajj drives a distinct, event-specific pollution regime, characterized by sharp increases in key pollutant concentrations, altered inter-pollutant and pollutant–meteorology relationships, and spatially explicit hotspots driven by human activity and infrastructure. The integrated satellite–meteorology workflow enabled near-real-time monitoring in a data-sparse environment and establishes a scalable framework for evidence-based air quality management and health risk reduction in mass gatherings. Full article

The spread of the invasive mosquitoes Aedes albopictus, Aedes aegypti, and Aedes japonicus in Spain represents an increasing public health risk due to their capacity to transmit arboviruses such as dengue, Zika, and chikungunya, among others. Traditional field entomological surveillance remains essential for tracking their spread, but it faces limitations in terms of cost, scalability, and labor intensity. Since 2014, the Mosquito Alert citizen-science project has enabled public participation in surveillance through the submission of geolocated images via a mobile app, which are identified using AI in combination with expert validation. While field surveillance provides high accuracy, citizen science offers low-cost, large-scale, real-time data collection aligned with open data management principles. It is particularly useful for detecting long-distance dispersal events and has contributed up to one-third of the municipal detections of invasive mosquito species since 2014. This study assesses the value of integrating both surveillance systems to capitalize on their complementary strengths while compensating for their weaknesses in the areas of taxonomic accuracy, scalability, spatial detection patterns, data curation and validation systems, geographic precision, interoperability, and real-time output. We present the listing of municipal detections of these species from 2004 to 2024, integrating data from both sources. Spain’s integrated approach demonstrates a pioneering model for cost-effective, scalable vector surveillance tailored to the dynamics of invasive species and emerging epidemiological threats. Full article

Habitat fragmentation represents a significant threat to biodiversity, particularly the survival of wild species. Constructing and optimizing ecological networks are critical for promoting sustainable biodiversity, especially in the conservation of unmanaged wildlife. To address this, this study focused on designing and optimizing an ecological network tailored to the preservation of the Xinjiang desert lacertid lizard (Eremias multiocellata). This study integrated a dual-model approach, applying the InVEST model for habitat quality assessment and the MaxEnt model for suitable habitat prediction. An overlay analysis identified 15 core ecological source areas spanning 126,044 km², primarily located in the desert–grassland transition zones of the central and western study areas. A total of 34 ecological corridors were established utilizing the minimum cumulative resistance model, totaling 3764 km in length. These include 11 long corridors, 17 short corridors, and 6 potential corridors. Additionally, 100 strategic points were identified: 41 pinch points, 38 barrier points, and 21 stepping stones. This study identifies priority areas and obstacles affecting the ecological connectivity of the species’ habitats and highlights the importance of small habitat patches for long-term species dispersal and habitat expansion, providing more comprehensive guidance for sustainable development and species conservation. Furthermore, the methodology provides valuable insights into biodiversity conservation and the optimization of the natural habitat spatial layout in desert ecosystems, along with novel methods for managing and conserving other unmonitored animal species in various ecosystems. Full article

This research has been performed to optimize the management of cultivated land fragmentation in the Henan Section of the Yellow River Basin, (“the research area”), coordinate the contradiction between increasing food demand and environmental constraints, maintain regional food security, and promote agricultural and rural modernization. The spatial and temporal evolution characteristics have been summarized by calculating the fragmentation index of the cultivated land landscape, and the driving factors explored with geographical detectors. Results show the following: (1) between 2000 and 2023, the landscape fragmentation index of cultivated land in the research region exhibited a pattern of initial decline followed by a subsequent rise. It decreased by 69.33% from 2000 to 2015 and increased by 138.42% from 2015 to 2023. Over the period from 2000 to 2023, the cultivated land landscape fragmentation index in the study area saw an overall reduction of 26.87%. (2) ”The reduction in cultivated land area and the decrease in landscape fragmentation” index accounted for 82.46% in the county unit. (3) The kernel density curve of the cultivated land landscape fragmentation index showed a unimodal distribution, but the shape was flat. The regions with a fragmentation index mainly range from 4 to 6. The regional cultivated land fragmentation distribution was more dispersed. (4) The average altitude, the distance from the Yellow River, the proportion of the construction land area and population density are the main driving factors. The combined impact of the proportion of the construction land area and population density contributes more than 46% to the cultivated land landscape fragmentation index. The interaction among various factors exerts a more pronounced effect than any individual factor alone. The intensity of the main interaction factors reaches above 0.67. The findings of this study can serve as a theoretical foundation for the sustainable utilization and development of cultivated land resources, as well as for ecological protection and construction in the Henan segment of the Yellow River Basin. Full article

This paper provides an in-depth analysis of the microstructural characteristics and the chemical content of Polybutylene Terephthalate (PBT) composites that have different contents of Glass Fiber (GF). Blending of VALOX 420 (30 wt% GF/PBT) with unreinforced VALOX 310 allowed the composites to be prepared, with control of the concentration and distribution of the GF. The GF reinforcement and PBT matrix were characterized by an advanced microstructural spectrum and spatial analysis to show the influence of fiber density, dispersion, and chemical composition on performance. Findings indicate that GF content has a profound effect on microstructural properties and damage processes, especially traction effects in various regions of the specimen. These results highlight the significance of accurate control of GF during fabrication to maximize durability and performance, which can be used to inform the design of superior PBT/GF composites in challenging engineering applications. The implications of these results are relevant to a number of high-performance sectors, especially in automotive, electrical, and consumer electronic industries, where PBT/GF composites are found in extensive use because of their outstanding mechanical strength, dimensional stability, and thermal resistance. The main novelty of the current research is both the microstructural and chemical assessment of PBT/GF composites in different fiber contents, and this aspect is rather insufficiently studied in the literature. Although the mechanical performance or macro-level aging effects have been previously assessed, the Literature usually did not combine elemental spectroscopy or spatial microstructural mapping to correlate the fiber distribution with the damage mechanisms. Further, despite the importance of GF reinforcement in achieving the right balance between mechanical, thermal, and electrical performance, not much has been conducted in detail to describe the correlation between the microstructure and the evolution of damage in short-fiber composites. Conversely, this paper will use the superior spatial elemental analysis to bring out the effects of GF content and dispersion on micro-mechanisms like interfacial traction, cracking of the matrix, and fiber fracture. We, to the best of our knowledge, are the first to systematically combine chemical spectrum analysis with spatial mapping of PBT/GF systems with varied fiber contents—this allows us to give actionable information on material design and optimized manufacturing procedures. Full article

Accurately estimating aboveground carbon storage (AGC) of urban vegetation remains a major challenge, due to the heterogeneity and vertical complexity of urban environments, where traditional forest-based remote sensing models often perform poorly. This study integrates multimodal remote sensing data and incorporates two three-dimensional structural features—mean tree height ($H_{mean}$) and canopy cover ratio (CCR)—in addition to conventional spectral and textural variables. To minimize redundancy, the Boruta algorithm was applied for feature selection, and four machine learning models (SVR, RF, XGBoost, and CatBoost) were evaluated. Results demonstrate that under multimodal data fusion, three-dimensional features emerge as the dominant predictors, with XGBoost using Boruta-selected variables achieving the highest accuracy (R² = 0.701, RMSE = 0.894 tC/400 m²). Spatial mapping of AGC revealed a “high-aggregation, low-dispersion” pattern, with the model performing best in large, continuous green spaces, while accuracy declined in fragmented or small-scale vegetation patches. Overall, this study highlights the potential of machine learning with multi-source variable inputs for fine-scale urban AGC estimation, emphasizes the importance of three-dimensional vegetation indicators, and provides practical insights for urban carbon assessment and green infrastructure planning. Full article

Hydrothermal vents are “oases” of biological productivity and endemicity on the seafloor. Chemosynthetic communities at deep-sea hydrothermal vents are characterized by high abundance and endemism. The distribution of species among these isolated habitats supports regional biodiversity and stability, so understanding the fundamental processes is a key target of conservation. Larval dispersal resulting from deep-ocean circulations is one of the major factors influencing the diversity and distributions of vent animals. By combining a biophysical model with biological larvae traits, we quantify potential larval dispersal of vent species via ocean circulation in the Azores Triple Junction. Here we present results from a biophysical model of larval dispersal run for the hydrothermal vent benthic mussel Bathymodiolus azoricus. Several scenarios were implemented, based on similar data sets, although changing values for one or two parameters, such as swimming behaviour and planktonic larvae duration. Results showed that larvae retention is the most common pattern from the Azores Triple Junction vent fields mussel. The Rainbow vent field is rather isolated, being the sink population of the Menez Gwen and Lucky Strike but with a very low number of larvae exchange. Results are discussed in the framework of spatial management to maintain the populations after an impact by natural or human disturbance. Full article

Free water surface constructed wetlands can be effective systems for contaminant removal, but their performance is sensitive to interactions among flow dynamics, vegetation, and bed topography. This study presents a numerical investigation into how heterogeneous bed topographies influence hydraulic and contaminant transport behavior in a rectangular wetland. Topographies were generated using a correlated pseudo-random pattern generator, and flow and solute transport were simulated with a two-dimensional, depth-averaged model. Residence time distributions and contaminant removal efficiencies were analyzed as functions of the variance and correlation length of the bed elevation. Results indicate that increasing the variability of bed elevation leads to greater dispersion in residence times, reducing hydraulic efficiency. Moreover, as the variability of bed elevation increases, so does the spread in hydraulic performance among wetlands with the same statistical topographic parameters, indicating a growing sensitivity of flow behavior to the specific spatial configurations of bed features. Larger spatial correlation lengths were found to reduce the residence time variance, as shorter correlation lengths promoted complex flow structures with lateral dead zones and internal islands. Contaminant removal efficiency, evaluated under the assumption of uniform vegetation, was influenced by bed topography, with variations becoming more pronounced under conditions of lower vegetation density. The results underscore the significant impact of bed topography on hydraulic behavior and contaminant removal performance, highlighting the importance of careful topographic design to ensure high wetland efficiency. Full article