Search Results (104)

Karst collapse columns (KCCs) represent key concealed hazard-inducing factors that threaten the safety of coal mines in North China. To clarify their primary controlling geological factors and evolutionary processes, this study focuses on KCCs in the Hancheng Mining Area, situated on the southeastern margin of the Ordos Basin, China. A comprehensive methodological approach—integrating field surveys, petrographic and mineralogical identification, geochemical analysis, and structural interpretation—was employed to investigate the dominant factors controlling KCC development and their evolutionary mechanisms. The results indicate the following: (1) Thick-bedded dolomites of the 5th Member of the Majiagou Formation (Middle Ordovician Series) serve as the material foundation for karstification. These dolomites were deposited in an oxidized shallow-water tidal flat setting, which endowed them with favorable lithological properties for subsequent dissolution. (2) NE-SW trending erosional grooves within the paleogeomorphology of the Ordovician top surface functioned as preferential flow paths for karst water, channeling fluid movement and intensifying localized dissolution. (3) Multi-phase tectonic activities, particularly extensional deformation during the Himalayan orogeny, created the necessary stress conditions to trigger cave collapse. (4) KCCs undergo a multi-stage formation and evolution process: Starting with the Majiagou Formation’s 5th Member dolomites as the primary lithology, initial modification occurred via Caledonian weathering–crust karstification. Subsequently, compressional tectonism during the Yanshanian orogeny generated void spaces that facilitated deep-seated dissolution. Rapid uplift in the Paleogene exacerbated vertical dissolution, leading to extensive cavity development, which ultimately collapsed under the extensional tectonic regime of the Neogene. This study provides theoretical support for predicting and mitigating sudden water inrushes caused by KCCs in the Hancheng Mining Area. Furthermore, it offers novel insights and a scientific basis for advancing understanding of the developmental mechanisms of North China-type KCCs. Full article

Macellicephaloides Uschakov, 1955 (Annelida: Polynoidae) is a genus of deep-sea polychaetes characterized by a specialized pharynx bearing two pairs of jaws (with the dorsal pair fused) and three pairs of lateral papillae, the middle pair of which is greatly elongated, and remarkable adaptability to diverse deep-sea habitats. Most species in this genus inhabit abyssal depths (>7200 m), with high diversity in western Pacific trenches, while a few occur in relatively shallow habitats such as deep-sea seamounts and hydrothermal vents. This paper presents a new species, Macellicephaloides lingshuiensis sp. nov., found in deep-sea cold seeps in the South China Sea, representing the shallowest distribution record for the genus to date and the first record from cold seep environments. The classification and phylogeny of Macellicephaloides and related genera have long been the subject of debate. A previous study suggested that Macellicephaloides is nested within the Macellicephala clade, but our analyses—based on 13 mitochondrial protein-coding genes, 12S, 16S, 18S, 28S rRNA, and ITS1-ITS2 sequences—tentatively indicate that these two genera form independent evolutionary clades. Additionally, our phylogeny indicates a close evolutionary relationship between deep-sea Macellicephaloides and cave-dwelling polynoids (e.g., Gesiella), highlighting ecological connections between deep-sea and cave habitats. These conclusions are supported by morphological comparisons and genetic distance analyses. Although the subfamily Macellicephalinae is recovered as a monophyletic group, intergeneric phylogenetic relationships within it remain unresolved, highlighting the need for additional data from more species and genera. We amend the generic diagnosis of Macellicephaloides and provide an identification key to all valid species in the genus. This study clarifies the taxonomy and phylogeny of Macellicephaloides and related taxa, emphasizing the importance of continued sampling in understudied deep-sea habitats to enhance our understanding of their biodiversity. Full article

Drawing on archaeological evidence, early ethnographic accounts, and historical documents, this article offers initial reflections on the possible past uses and meanings of a set of black drawings found deep within a cave in what is now known as the Sierra Mixe of Oaxaca, Mexico. Following this investigative approach, it explores the role of rock art as an interface between orality, imagery, and text in the context of ancient Mesoamerica. To understand the possible ontological perceptions of the creators of these images in the past, it is suggested that this imagery functioned as inscriptions in a dialogue with spatially related unfired figures modelled in clay, which are exceptionally well-preserved in this subterranean space. An interplay of media on various supports is proposed, wherein two-dimensional images and three-dimensional figures may have been used as a combined system for transmitting and circulating intergenerational cultural knowledge, serving as an anchor for collective memory. In this context, rock imagery played a role in a broader communication system in Mesoamerica. Full article

Hyperspectral images (HSIs), with their rich spectral information, are widely used in remote sensing; yet the inherent trade-off between spectral and spatial resolution in imaging systems often limits spatial details. Single-image hyperspectral super-resolution (HSI-SR) seeks to recover high-resolution HSIs from a single low-resolution input, but the high dimensionality and spectral redundancy of HSIs make this task challenging. In HSIs, spectral signatures and spatial textures often exhibit intrinsic symmetries, and preserving these symmetries provides additional physical constraints that enhance reconstruction fidelity and robustness. To address these challenges, we propose the Dynamic Spectral Collaborative Super-Resolution Network (DSCSRN), an end-to-end framework that integrates physical modeling with deep learning and explicitly embeds spatial–spectral symmetry priors into the network architecture. DSCSRN processes low-resolution HSIs with a Cascaded Residual Spectral Decomposition Network (CRSDN) to compress redundant channels while preserving spatial structures, generating accurate abundance maps. These maps are refined by two Synergistic Progressive Feature Refinement Modules (SPFRMs), which progressively enhance spatial textures and spectral details via a multi-scale dual-domain collaborative attention mechanism. The Dynamic Endmember Adjustment Module (DEAM) then adaptively updates spectral endmembers according to scene context, overcoming the limitations of fixed-endmember assumptions. Grounded in the Linear Mixture Model (LMM), this unmixing–recovery–reconstruction pipeline restores subtle spectral variations alongside improved spatial resolution. Experiments on the Chikusei, Pavia Center, and CAVE datasets show that DSCSRN outperforms state-of-the-art methods in both perceptual quality and quantitative performance, achieving an average PSNR of 43.42 and a SAM of 1.75 (×4 scale) on Chikusei. The integration of symmetry principles offers a unifying perspective aligned with the intrinsic structure of HSIs, producing reconstructions that are both accurate and structurally consistent. Full article

Bats are ecologically vital mammals, serving as pollinators, seed dispersers, and bioindicators of ecosystem health. Many species inhabit natural caves, which offer optimal conditions for survival but present challenges for direct ecological monitoring due to their dark, complex, and inaccessible environments. Traditional monitoring methods, such as mist-netting, are invasive and limited in scope, highlighting the need for non-intrusive alternatives. In this work, we present a portable multisensor platform designed to operate in underground habitats. The system captures multimodal data, including near-infrared (NIR) imagery, ultrasonic audio, 3D structural data, and RGB video. Focusing on NIR imagery, we evaluate the effectiveness of the YOLO object detection framework for automated bat detection and counting. Experiments were conducted using a dataset of NIR images collected in natural shelters. Three YOLO variants (v10, v11, and v12) were trained and tested on this dataset. The models achieved high detection accuracy, with YOLO v12m reaching a mean average precision (mAP) of 0.981. These results demonstrate that combining NIR imaging with deep learning enables accurate and non-invasive monitoring of bats in challenging environments. The proposed approach offers a scalable tool for ecological research and conservation, supporting population assessment and behavioral studies without disturbing bat colonies. Full article

Underground mining environments are highly hazardous, often prone to gas explosions, cave-ins, and fires that may trap miners during emergencies. The accurate, real-time localization of miners is vital for effective self-escape and rescue operations. Although the Mine Improvement and New Emergency Response (MINER) Act of 2006 mandates communication and tracking systems, most current solutions rely on low-power devices and line-of-sight methods that are ineffective in GPS-denied, dynamic subsurface conditions. Delay-Tolerant Networking (DTN) has emerged as a promising alternative by supporting message relay through intermittent links. In this work, we propose a deep learning framework that combines Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks to predict miner locations using simulated DTN-based movement data. The model was trained on a simulated dataset of 1,048,575 miner movement entries, predicting miner locations across 26 pillar classes. It achieved an 89% accuracy, an 89% recall, and an 83% F1-score, demonstrating strong performance for real-time underground miner localization. These results demonstrate the model’s potential for the real-time localization of trapped miners in GPS-denied environments, supporting enhanced self-escape and rescue operations. Future work will focus on validating the model with real-world data and deploying it for operational use in mines. Full article

To study hydrogeological characteristics after the occurrence of abnormal water bursts from the weak water-rich (permeable) aquifer of the Changxing Formation limestone overlying deep working faces during production in Guizhou karst landform mining areas, hydrogeological data covering the exploration and production periods of the Xinhua mining region in Jinsha County, Guizhou Province, were collected. On the basis of surface and underground drilling, geophysical exploration techniques, empirical equations, and indoor material simulation methods, the hydrogeological evolution characteristics of the Changxing Formation limestone in the mining region after mining damage to coalbed 9 were studied. The research results indicated that the ratio of the height of the roof failure fracture zone (as obtained via numerical simulation and ground borehole detection) to the mining height exceeded 25.78, which is far greater than the empirical model calculation values (from 13.0 to 15.8). After mining the underlying coalbed 9, an abnormal water-rich area developed in the Changxing Formation limestone, and mining damage fractures led to the connection of the original dissolution fissures and karst caves within the limestone, resulting in the weak water-rich (permeable) aquifer of the Changxing Formation limestone becoming a strong water-rich (permeable) aquifer, which served as the water source for mine water bursts. Over time, after mining damage occurrence, the voids in the Changxing Formation limestone were gradually filled with various substances, yielding water storage space and connectivity decreases. The specific yield decreased with an increasing water burst time and interval after the cessation of mining in the supply area, and the correlation coefficient R was 0.964, indicating a high degree of correlation between the two parameters. Full article

As a type of distinctive pit on Mars, skylights are entrances to subsurface lava caves. They are very important for studying volcanic activity and potential preserved water ice, and are also considered as potential sites for human extraterrestrial bases in the future. Most skylights are manually identified, which has low efficiency and is highly subjective. Although deep learning methods have recently been used to identify skylights, they face challenges of few effective samples and low identification accuracy. In this article, 151 positive samples and 920 negative samples based on the MRO-HiRISE image data was used to create an initial skylight dataset, which contained few positive samples. To augment the initial dataset, StyleGAN2-ADA was selected to synthesize some positive samples and generated an augmented dataset with 896 samples. On the basis of the augmented skylight dataset, we proposed YOLOv9-Skylight for skylight identification by incorporating Inner-EIoU loss and DySample to enhance localization accuracy and feature extracting ability. Compared with YOLOv9, the P, R, and the F1 of YOLOv9-Skylight were improved by about 9.1%, 2.8%, and 5.6%, respectively. Compared with other mainstream models such as YOLOv5, YOLOv10, Faster R-CNN, Mask R-CNN, and DETR, YOLOv9-Skylight achieved the highest accuracy (F1 = 92.5%), which shows a strong performance in skylight identification. Full article

The Mutanchis, known by their derogatory exonymic term ‘Lepcha’, are autochthonous to Sikkim, India. The name ‘Mutanchi’ derives from the phrase ‘Mutanchi Rumkup Rongkup’, eliciting the response ‘Achulay’, meaning ‘Beloved children of It-bu-mu, who have come from the snowy peaks’. The nomenclature prompts an ontological understanding rooted in the community’s eco-geographical context. Despite possessing a well-developed script categorised within the Tibeto-Burman language family, the Mutanchis remain a largely oral community. Their diminishing, scarcely documented repository of Mutanchi clan narratives underscores this orality. As a Mutanchi, I recognise these narratives as a medium for expressing Indigenous value systems upheld by my community and specific villages. Mutanchi clan narratives embody spiritual and cultural significance, yet their fantastic rationale reveals complex epistemological tensions. Ideally, each Mutanchi clan reveres a chyu (peak), lhep (cave), and doh (lake), which are propitiated annually and on specific occasions. The transmigration of an apil (soul) is tied to these three sacred spatial geographies, unique to each clan. Additionally, clan etiological explanations, situated within natural or supernatural habitats, manifest beliefs, values, and norms rooted in a deep ecology. This article presents an ecosophical study of selected Mutanchi clan narratives from Dzongu, North Sikkim—a region that partially lies within the UNESCO Khangchendzonga Man-Biosphere Reserve. Conducted in close consultation with clan members and in adherence to the ethical protocols, this study examines clans in Dzongu governed by Indigenous knowledge systems embedded in their narratives, highlighting biocentric perspectives that shape Mutanchi lifeways. Full article

The deep carbonate reservoirs in the Tarim Basin, Xinjiang, China, are widely developed with multi-scale complex reservoir spaces such as fractures, pores, and karst caves under the coupling of abnormal high pressure, diagenesis, karst, and tectonics and have strong heterogeneity. Among them, fracture–cavity carbonate reservoirs are one of the main reservoir types. Revealing the petrophysical characteristics of fracture–cavity carbonate reservoirs can provide a theoretical basis for the log interpretation and geophysical prediction of deep reservoirs, which holds significant implications for deep hydrocarbon exploration and production. In this study, based on the mineral composition and complex pore structure of carbonate rocks in the Tarim Basin, we comprehensively applied classical petrophysical models, including Voigt–Reuss–Hill, DEM (Differential Effective Medium), Hudson, Wood, and Gassmann, to establish a fracture–cavity petrophysical model tailored to the target block. This model effectively characterizes the complex pore structure of deep carbonate rocks and addresses the applicability limitations of conventional models in heterogeneous reservoirs. The discrepancies between the model-predicted elastic moduli, longitudinal and shear wave velocities (Vp and Vs), and laboratory measurements are within 4%, validating the model’s reliability. Petrophysical template analysis demonstrates that P-wave impedance (Ip) and the Vp/Vs ratio increase with water saturation but decrease with fracture density. A higher fracture density amplifies the fluid effect on the elastic properties of reservoir samples. The Vp/Vs ratio is more sensitive to pore fluids than to fractures, whereas Ip is more sensitive to fracture density. Regions with higher fracture and pore development exhibit greater hydrocarbon storage potential. Therefore, this petrophysical model and its quantitative templates can provide theoretical and technical support for predicting geological sweet spots in deep carbonate reservoirs. Full article

With the increasing depth of coal mining operations, the repeated extraction of multiple coal seams has led to serious safety threats to mines, including secondary roof fracturing, interlayer separation-induced water hazards, and intense mine pressure. Due to the limited research available on the roof failure laws of gently inclined coal seam groups, this study focuses on the Yindonggou Coal Mine and employs a comprehensive approach combining theoretical analysis, numerical simulation, and field measurement. Theoretical calculations indicate that after the mining of Seam 1, the caving zone height ranges from 6.69 to 11.09 m, and the height of the water-conducting fracture zone ranges from 29.59 to 40.79 m. After Coal Seam 2 is mined, the caving zone extends 24.05–33.47 m above the roof of Coal Seam 1, and the fracture zone develops for up to 74.10–94.94 m. Following the mining of Seam 4, the caving zone expands to 30.73–40.15 m above the roof of Coal Seam 1, and the fracture zone reaches 92.26–113.10 m. The numerical simulation results show that after mining Seam 1, the caving zone height is 8.4 m, and the fracture zone reaches 36 m. After Seam 2 is mined, the caving zone extends to 27 m above the roof of Coal Seam 1 and the fracture zone extends to 89 m. After Seam 4 is mined, the caving zone expands to 40 m above the roof of Coal Seam 1 and the fracture zone develops to 112.6 m. The field measurements validate the following findings: a loss of flushing fluid during drilling indicates that after Coal Seam 4 is mined, the fracture zone develops up to 110.5 m above the roof of Coal Seam 1, and the caving zone reaches 47.5 m. Optical imaging logging shows the fracture zone developing to 114.5 m and the caving zone extending to 48.1 m above the roof of Coal Seam 1. The results demonstrate good consistency among these theoretical calculations, numerical simulations, and field measurements. This study reveals a progressive development pattern of roof failure during the repeated mining of gently inclined coal seam groups, providing a theoretical foundation for water hazard prevention and mine pressure control in deep multi-seam mining operations. Full article

El Malpais National Monument in New Mexico, USA, is a landscape of significant cultural and geological importance, characterized by extensive lava flows, caves, and cinder cones. Despite its harsh terrain, El Malpais holds deep cultural and spiritual meanings for Native American communities, including the Acoma, Zuni, Laguna, and Navajo tribes, whose cosmologies and histories are interwoven with this landscape. Employing a mixed-methods approach combining ethnographic fieldwork with comparative literature studies, this paper documents how these Indigenous groups perceive and interpret interconnected geological features as sacred and meaningful parts of their ancestral heritage. The findings reveal that volcanic landscapes are central not only to cultural origin narratives but also to ongoing rituals, resource use, and pilgrimage practices. This interconnectedness is exemplified by the cultural links between El Malpais and adjacent Mount Taylor, highlighting how geological features form a unified sacred geography. This study positions El Malpais as a culturally animated landscape, where Indigenous epistemologies and spiritual relationships with volcanic landforms challenge conventional notions of geoheritage and call for relational, community-informed approaches to heritage management. Full article

Understanding the coupled evolution mechanisms of stress, fracture, and seepage fields in overburden strata is critical for preventing water inrush disasters during fully mechanized mining in deep coal seams, particularly under complex hydrogeological conditions. To address this challenge, this study integrates laboratory experiments with FLAC3D numerical simulations to systematically investigate the multi-field coupling behavior in the Luotuoshan coal mine. Three types of coal rock samples—raw coal/rock (bending subsidence zone), fractured coal/rock (fracture zone), and broken rock (caved zone)—were subjected to triaxial permeability tests under varying stress conditions. The experimental results quantitatively revealed distinct permeability evolution patterns: the fractured samples exhibited a 23–48 × higher initial permeability (28.03 mD for coal, 13.54 mD for rock) than the intact samples (0.50 mD for coal, 0.21 mD for rock), while the broken rock showed exponential permeability decay (120.32 mD to 23.72 mD) under compaction. A dynamic permeability updating algorithm was developed using FISH scripting language, embedding stress-dependent permeability models (R² > 0.99) into FLAC3D to enable real-time coupling of stress–fracture–seepage fields during face advancement simulations. The key findings demonstrate four distinct evolutionary stages of pore water pressure: (1) static equilibrium (0–100 m advance), (2) fracture expansion (120–200 m, 484% permeability surge), (3) seepage channel formation (200–300 m, 81.67 mD peak permeability), and (4) high-risk water inrush (300–400 m, 23.72 mD stabilized permeability). The simulated fracture zone height reached 55 m, directly connecting with the overlying sandstone aquifer (9 m thick, 1 MPa pressure), validating field-observed water inrush thresholds. This methodology provides a quantitative framework for predicting water-conducting fracture zone development and optimizing real-time water hazard prevention strategies in similar deep mining conditions. Full article

This study investigates the exacerbated strata pressure manifestations induced by high-intensity mining in medium-deep weakly cemented coal seams in western China. An integrated research methodology combining theoretical analysis, field measurements, and numerical simulation was employed to develop a mechanical model of overburden fracture structures in weakly cemented mining faces, systematically revealing the dynamic effects of face advance rate on strata pressure behavior. The results demonstrate that the advance rate not only significantly governs the evolutionary patterns of roof caving and weighting intervals but also exhibits nonlinear correlations with the distribution characteristics of abutment pressure. Furthermore, microseismic parameters effectively characterize the response of strata pressure intensity to advance rate variations. The proposed dynamic control methodology provides both theoretical foundations for safe mining in weakly cemented strata and innovative technical solutions for ground control in deep high-intensity mining operations. Full article

This study examines speleothems, sediments, rock, and water to assess geochemical and mineralogical processes in deep karst systems. Focusing on Slovačka jama cave (−1320 m deep) and the Velebita cave system (−1026 m deep), we identify elemental and mineralogical anomalies that provide valuable records of element transport, mineral formation, and paleoenvironmental changes. Heavy metal anomalies (Al, B, Co, Mn, Na, Tl, Ba, Be, Cr, Cu, Fe, K, Pb, Rb, Ti, U, Zn) at 300–400 m of depth in Slovačka jama indicate a complex interplay of geological conditions, geomorphological processes, atmospheric deposition, and potential anthropogenic influences. Factor analysis reveals two elemental associations: (1) Fe, Pb, Cu, and Zn, linked to terrigenous aluminosilicates, and (2) Cd, Cr, Mo, and Ni, suggesting airborne or geological sources. Mineralogical analysis confirms the dominance of calcite, with quartz, clay minerals, feldspars, magnetite, and goethite also detected. High magnetic susceptibility values in sediment-rich samples suggest Fe-rich mineral inputs from weathering, biogenic activity, or industrial sources. Ba anomalies in feldspar-rich samples and Sr accumulation at depth indicate distinct geochemical processes. These findings enhance our understanding of deep karst geochemistry, crucial for paleoenvironmental reconstructions and groundwater protection. Full article