Search Results (23,389)

This study investigates the concept of landscape services (LS), which integrate environmental and sociocultural dimensions of sustainable development. Recognizing landscapes as essential to daily life and well-being, the research aims to support sustainable spatial planning by analyzing both their potential and their actual use. The study has three main objectives: (1) to assess the potential of 16 selected landscape types to provide six key LS through expert evaluation; (2) to determine actual LS usage patterns among the local community (residents); and (3) to identify agreements and discrepancies between expert assessments and resident use. The services analyzed include providing space for daily activities; regulating spatial structure through diversity and compositional richness; enhancing physical and mental health; enabling passive and active recreation; supporting personal fulfillment; and fostering social interaction. Expert-based surveys and participatory mapping with residents were used to assess the provision and use of LS. The results indicate consistent evaluations for forest and historical urban landscapes (high potential and use) and mining and transportation landscapes (low potential and use). However, significant differences emerged for mountain LS, rated highly by experts but used minimally by residents. These insights highlight the importance of aligning expert planning with community needs to promote sustainable land use policies and reduce spatial conflicts. Full article

The abandoned goaf resulting from coal resource integration in China poses a significant threat to coal mine safety. The transient electromagnetic method (TEM) has emerged as a crucial technology for detecting goafs in coal mines due to its adaptable equipment and efficient implementation. In recent years, small-loop TEM has demonstrated high resolution and adaptability in challenging terrains with vegetation, such as coal mine ponding areas, karst regions, and reservoir seepage scenarios. By considering the sedimentary characteristics of coal seams and addressing the resistivity changes encountered in single-point inversion, a joint optimization inversion process incorporating lateral weighting factors and vertical roughness constraints has been developed to enhance the connectivity between adjacent survey points and improve the continuity of inversion outcomes. Through an OCCAM inversion approach, the regularization factor is dynamically determined by evaluating the norms of the data objective function and model objective function in each iteration, thereby reducing the reliance of inversion results on the initial model. Using the Xiaolong Coal Mine as a geological context, the impact of lateral and vertical weighting factors on the inversion outcomes of high- and low-resistivity structural models is examined through a control variable method. The analysis reveals that optimal inversion results are achieved with a combination of a lateral weighting factor of 0.5 and a vertical weighting factor of 0.1, ensuring both result continuity and accurate depiction of vertical and lateral electrical interfaces. The practical application of this approach validates its effectiveness, offering theoretical support and technical assurance for old goaf detection in coal mines, thereby holding significant engineering value. Full article

This paper examines Krivelj, a copper mining village in Serbia, as a critical yet overlooked node within global extractive networks. Despite supplying copper essential for renewable energy and sustainable architecture, Krivelj experiences severe ecological disruption, forced relocations, and socio-spatial destabilization, becoming a “sacrifice zone”—an area deliberately subjected to harm for broader economic interests. Employing a hybrid methodology that combines ethnographic fieldwork with Geographic Information Systems (GISs), this study spatializes narratives of extractive violence collected from residents through walking interviews, field sketches, and annotated aerial imagery. By integrating satellite data, legal documents, environmental sensors, and lived testimonies, it uncovers the concept of “slow violence,” where incremental harm occurs through bureaucratic neglect, ambient pollution, and legal ambiguity. Critiquing the abstraction of Planetary Urbanization theory, this research employs countertopography and forensic spatial analysis to propose a counter-cartographic framework that integrates geospatial analysis with local narratives. It demonstrates how global mining finance manifests locally through tangible experiences, such as respiratory illnesses and disrupted community relationships, emphasizing the potential of counter-cartography as a tool for visualizing and contesting systemic injustice. Full article

This article analyzes the operating principle of the BMM sensor emitter in order to improve the accuracy of the wireless determination of the BMM sensor coordinates under a massif of destroyed rock in the context of the problem of determining the shift of rocks during gold ore mining. Using numerical simulations, FEM has been developed to develop digital models reflecting individual cases of the propagation of the magnetic field of the emitter located in various geological conditions and positions relative to the rock surface and the vertical axis. The accuracy of determining the coordinates of the radio beacon in the rock has been analyzed, and data on the deviation of the coordinates of the peaks of the magnetic field strength from the radio beacon axis have been obtained in cases of a heterogeneous composition of the rock massif, the influence of the deviation of the emitter axis angle from the vertical, the influence of the unevenness of the collapse relief, and the influence of the superposition of fields from different radiation sources. A study has been carried out to determine the direction of the radio beacon search based on the resulting vector of the emitter’s magnetic field strength. Full article

Occupational heat stress represents an increasing challenge to safety and operational performance in underground mining, where elevated temperatures, humidity, and limited ventilation are common. This study proposes an integrated framework to analyze the systemic impact of heat stress on human reliability in mining operations. We conducted a systematic literature review to identify empirical studies addressing thermal exposure, extracting key operational functions for modeling. These functions were structured using the Functional Resonance Analysis Method (FRAM) to reveal interdependencies and performance variability. Human reliability was evaluated using Fuzzy CREAM, which quantified the degree of contextual control associated with each function. Finally, we applied the Gaussian Analytic Hierarchy Process (AHP) to prioritize functions based on thermal impact, contextual reliability, and systemic connectivity. The results showed that functions involving subjective or complex judgment, such as assessing thermal stress or identifying psychophysiological indicators, exhibited lower reliability and higher vulnerability. In contrast, monitoring and control functions based on standardized procedures were more stable and resilient. This combined approach identified critical points of systemic fragility and offers a robust decision-support tool for prioritizing thermal risk mitigation. The findings contribute to advancing the scientific understanding of heat stress impacts in mining and support the development of targeted interventions to enhance human performance and safety in extreme environments. Full article

Landslide displacement prediction is crucial for disaster mitigation, yet traditional methods often fail to capture the complex, non-stationary spatiotemporal dynamics of slope evolution. This study introduces an enhanced prediction framework that integrates multi-scale signal processing with dynamic, geology-aware graph modeling. The proposed methodology first employs the Maximum Overlap Discrete Wavelet Transform (MODWT) to denoise raw Global Navigation Satellite System (GNSS)-monitored displacement time series data, enhancing the underlying deformation features. Subsequently, a geology-aware graph is constructed, using the temporal correlation of displacement series as a practical proxy for physical relatedness between monitoring nodes. The framework’s core innovation lies in a dynamic graph optimization model with low-rank constraints, which adaptively refines the graph topology to reflect time-varying inter-sensor dependencies driven by factors like mining activities. Experiments conducted on a real-world dataset from an active open-pit mine demonstrate the framework’s superior performance. The DCRNN-proposed model achieved the highest accuracy among eight competing models, recording a Root Mean Square Error (RMSE) of 2.773 mm in the Vertical direction, a 39.1% reduction compared to its baseline. This study validates that the proposed dynamic graph optimization approach provides a robust and significantly more accurate solution for landslide prediction in complex, real-world engineering environments. Full article

Maximizing the efficient utilization of critical apatite resources through flotation necessitates the exploration of effective and innovative collectors. This study investigates the potential of a fatty acid mixture (FAM) synthesized from saturated palmitic and stearic acids, monounsaturated oleic and palmitoleic acids, and polyunsaturated linoleic acid. The saponified collector FAM and the depressant sodium alginate (NaAl) achieved a direct flotation of apatite from calcite and quartz (97% apatite, 10% calcite, and 7% quartz). The flotation performance with the tested combination exhibited a highly effective enrichment of apatite, mainly from calcite, which aligns with the surface chemistry assessments. Adsorption tests and zeta potential measurements confirmed the micro-flotation results. They provided compelling evidence of a chemisorption interaction between Ca²⁺ sites on calcite and the carboxyl and hydroxyl groups of NaAl. FTIR analyses suggested a reaction between the apatite surface and the carboxyl groups of saturated and unsaturated acid groups in FAM, even those conditioned with NaAl before, facilitating the complex formation. Remarkably, the synergistic effect of the functional groups demonstrates dual functionality, serving as both a hydrophilic entity for calcite and a hydrophobic entity for apatite flotation. The universal mechanism unveils substantial potential for the extensive application of FAM within apatite flotation. Full article

Fungal lytic polysaccharide monooxygenases (LPMOs) have revolutionized the field of biomass degradation by introducing an oxidative mechanism that complements traditional hydrolytic enzymes. These copper-dependent enzymes catalyze the cleavage of glycosidic bonds in recalcitrant polysaccharides such as cellulose, hemicellulose, and chitin, through the activation of molecular oxygen (O₂) or hydrogen peroxide (H₂O₂). Their catalytic versatility is intricately modulated by structural features, including the histidine brace active site, surface-binding loops, and, in some cases, appended carbohydrate-binding modules (CBMs). The oxidation pattern, whether at the C1, C4, or both positions, is dictated by subtle variations in loop architecture, amino acid microenvironments, and substrate interactions. LPMOs are embedded in a highly synergistic fungal enzymatic system, working alongside cellulases, hemicellulases, lignin-modifying enzymes, and oxidoreductases to enable efficient lignocellulose decomposition. Industrial applications of fungal LPMOs are rapidly expanding, with key roles in second-generation biofuels, biorefineries, textile processing, food and feed industries, and the development of sustainable biomaterials. Recent advances in genome mining, protein engineering, and heterologous expression are accelerating the discovery of novel LPMOs with improved functionalities. Understanding the balance between O₂- and H₂O₂-driven mechanisms remains critical for optimizing their catalytic efficiency while mitigating oxidative inactivation. As the demand for sustainable biotechnological solutions grows, this narrative review highlights how fungal LPMOs function as indispensable biocatalysts for the future of the Circular Bioeconomy and green industrial processes. Full article

This work investigated the ion exchange technique for selective separation of rare earth elements (REE) from acid mine drainage (AMD), using different column systems, pH values, and eluent concentrations. Systematic analysis of pH and eluent concentration showed that an initial pH of 6.0 and 0.02 mol L⁻¹ NH₄EDTA are the optimal conditions, achieving 98.4% heavy REE purity in the initial stage (0 to 10 bed volumes). This represents a 32-fold increase compared to the original AMD (6.7% heavy REE). The speciation of REE and impurities was determined by Visual Minteq 4.0 software using pH 2.0, which corresponds to the pH at the inlet of the fractionation column. Under this condition, La and Nd and the impurities (Ca, Mg, and Mn) remained in the fractionation column, while Al was partially retained. In addition, the heavy REE (Y and Dy) were mainly in the form of REE-EDTA complexes and not as free cations, which made fractionation more feasible. The fractionation column minimized impurities, retaining 100% of Ca and 67% of Al, generating a liquor concentrated in heavy REE. This sustainable approach adopted herein meets the critical needs for scalable recovery of REE from diluted effluents, representing a circular economy strategy for critical metals. Full article

This paper presents a critical and comprehensive review of the application of mining waste, specifically waste rock and tailings, in asphalt pavements, with the aim of synthesizing performance outcomes and identifying key research gaps. A systematic literature search yielded a final dataset of 41 peer-reviewed articles for detailed analysis. Bibliometric analysis indicates a notable upward trend in annual publications, reflecting growing academic and practical interest in this field. Performance-based evaluations demonstrate that mining wastes, particularly iron and copper tailings, have the potential to enhance the high-temperature performance (i.e., rutting resistance) of asphalt binders and mixtures when utilized as fillers or aggregates. However, their effects on fatigue life, low-temperature cracking, and moisture susceptibility are inconsistent, largely influenced by the physicochemical properties and dosage of the specific waste material. Despite promising results, critical knowledge gaps remain, particularly in relation to long-term durability, comprehensive environmental and economic Life-Cycle Assessments (LCA), and the inherent variability of waste materials. This review underscores the substantial potential of mining wastes as sustainable alternatives to conventional pavement materials, while emphasizing the need for further multidisciplinary research to support their broader implementation. Full article

Environmental sustainability and responsible resource utilization are critical global challenges. In this work, we present a sustainable and circular-economy-based approach for synthesizing CuFe₂O₄ nanoparticles by directly utilizing copper oxide minerals sourced from Chilean mining operations. Copper sulfate (CuSO₄) was extracted from these minerals through acid leaching and used as a precursor for nanoparticle synthesis via both chemical co-precipitation and microwave-assisted methods. The influence of different precipitating agents—NaOH, Na₂CO₃, and NaF—was systematically evaluated. XRD and FESEM analyses revealed that NaOH produced the most phase-pure and well-dispersed nanoparticles, while NaF resulted in secondary phase formation. The microwave-assisted method further improved particle uniformity and reduced agglomeration due to rapid and homogeneous heating. Electrochemical characterization was conducted to assess the suitability of the synthesized CuFe₂O₄ for supercapacitor applications. Cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD) measurements confirmed pseudocapacitive behavior, with a specific capacitance of up to 1000 F/g at 2 A/g. These findings highlight the potential of CuFe₂O₄ as a low-cost, high-performance electrode material for energy storage. This study underscores the feasibility of converting primary mined minerals into functional nanomaterials while promoting sustainable mineral valorization. The approach can be extended to other critical metals and mineral residues, including tailings, supporting the broader goals of a circular economy and environmental remediation. Full article

This study explores the determinants of startup intention within the context of e-commerce platform-based startups in South Korea. We employ an extended technology acceptance model (TAM) that integrates individual, social, and entrepreneurial characteristics. A two-step analytical approach is applied, combining variable extraction through data mining and hypothesis testing using structural equation modeling. The results indicate that personal and social factors—such as entrepreneurial mindset and social influence—positively affect perceived usefulness, while job relevance and exposure to successful startup models enhance perceived ease of use. In contrast, security concerns and technological barriers negatively impact these relationships, posing critical obstacles to platform-based startups. This study extends the TAM framework to the platform-based startup context, offering theoretical contributions and proposing policy implications, including promoting digital literacy, developing entrepreneurial networks, and addressing security and regulatory issues. These insights offer a deeper understanding of how platform environments shape entrepreneurial behavior, providing practical guidance for startup founders, developers, and policymakers. Full article

Acid mine drainage (AMD) remains a critical environmental challenge in South Africa due to its severe impact on water quality, ecosystems and public health. Numerous studies on AMD management, treatment and resource recovery have been conducted over the past 20 years. This study presents a comprehensive review of research activities on AMD in South Africa from 1998 to 2025, highlighting key trends, emerging challenges and future directions. The study reveals a significant focus on passive and active treatment methods, environmental remediation and the recovery of valuable resources, such as iron, rare earth elements (REEs) and gypsum. A bibliometric analysis was conducted to identify the most influential studies and thematic research areas over the years. Bibliometric tools (Biblioshiny and VOSviewer) were used to analyse the data that was extracted from the PubMed database. The findings indicate that research production has increased significantly over time, with substantial contributions from top academics and institutions. Advanced treatment technologies, the use of artificial intelligence and circular economy strategies for resource recovery are among the new research prospects identified in this study. Despite substantial progress, persistent challenges, such as scalability, economic viability and policy implementation, remain. Furthermore, few technologies have moved beyond pilot-scale implementation, underscoring the need for greater investment in field-scale research and technology transfer. This study recommends stronger industry–academic collaboration, the development of standardised treatment protocols and enhanced government policy support to facilitate sustainable AMD management. The study emphasises the necessity of data-driven approaches, sustainable technology and interdisciplinary cooperation to address AMD’s socioeconomic and environmental effects in the ensuing decades. Full article

Accurate dynamic flow statistics for trackless vehicles are critical for efficiently scheduling trackless transportation systems in underground mining. However, traditional discrete time-point methods suffer from “time membership discontinuity” due to RFID timestamp sparsity. This study proposes a fuzzy five-region membership (FZFM) model to address this issue by subdividing time intervals into five characteristic regions and constructing a composite Gaussian–quadratic membership function. The model dynamically assigns weights to adjacent segments based on temporal distances, ensuring smooth transitions between time intervals while preserving flow conservation. When validated on a 29-day RFID dataset from a large coal mine, FZFM eliminated conservation bias, reduced the boundary mutation index by 11.1% compared with traditional absolute segmentation, and maintained high computational efficiency, proving suitable for real-time systems. The method effectively mitigates abrupt flow jumps at segment boundaries, providing continuous and robust flow distributions for intelligent scheduling algorithms in complex underground logistics systems. Full article

In order to improve the inversion accuracy of electrical resistivity tomography (ERT) and overcome the limitations of traditional linear methods, this paper proposes an improved shuffled frog leaping algorithm (SFLA). First, an equilibrium grouping strategy is designed to balance the contribution weight of each subgroup to the global optimal solution, suppressing the local optimum traps caused by the dominance of high-quality groups. Second, an adaptive movement operator is constructed to dynamically regulate the step size of the search, enhancing the guiding effect of the optimal solution. In synthetic data tests of three typical electrical models, including a high-resistivity anomaly with 5% random noise, a normal fault, and a reverse fault, the improved algorithm shows an approximately 2.3 times higher accuracy in boundary identification of the anomaly body compared to the least squares (LS) method and standard SFLA. Additionally, the root mean square error is reduced by 57%. In the engineering validation at the Baota Mountain mining area in Jurong, the improved SFLA inversion clearly reveals the undulating bedrock morphology. At a measuring point 55 m along the profile, the bedrock depth is 14.05 m (ZK3 verification value 12.0 m, error 17%), and at 96 m, the depth is 6.9 m (ZK2 verification value 6.7 m, error 3.0%). The characteristic of deeper bedrock to the south and shallower to the north is highly consistent with the terrain and drilling data (RMSE = 1.053). This algorithm provides reliable technical support for precise detection of complex geological structures using ERT. Full article