Search Results (5,644)

The Jiaodong Peninsula constitutes a world-class gold province in eastern China, containing more than 5000 t of identified gold resources. The Jiaojia gold deposit is one of the largest deposits within this gold province, and mineralization is primarily distributed along the northern segment of the Jiaojia Fault. The structural characteristics and mineralization processes of the northern segment have been extensively documented. In contrast, the ore-forming mechanisms of the southern Jiaojia Fault remain poorly constrained, hindering further exploration targeting. We chose several gold deposits and one drill core along the Jiaojia Fault, then present whole-rock major and trace elements data to evaluate magmatic affinities and their ore-forming potential. The results show that the lithological differences in plutonic and stratigraphic units suggest that variations in petrogenesis may have exerted a fundamental control on mineralization styles. Almost all samples are characterized by enrichment in light rare earth elements, relative enrichment in Europium, and pronounced depletion in heavy rare earth elements. Alteration characteristics indicate the northern segment is dominated by advanced argillic alteration, whereas phyllic alteration is more prevalent in the southern segment. The rare earth elements discrimination plot clearly suggests differentiation from the northern and southern fault segments. Consequently, we propose that the northern segment records synorogenic arc magmatism, while the southern segment experienced both synorogenic and a subsequent intraplate extensional transitional stage. Full article

The geochronological framework of the Late Mesozoic volcanic succession in the Great Xing’an Range is crucial for understanding the tectonic regime transition in Northeast Asia. However, the ages and stratigraphic relationships of key volcanic units remain poorly constrained. This study presents zircon LA-ICP-MS U–Pb geochronological data from volcanic rocks above and below the basal unconformity of the Longjiang Formation in the Zhalantun–Jalaid Banner area, central Great Xing’an Range, aiming to determine the timing of volcanic activity, constrain the formation age of the unconformity, and explore its regional tectonic implications. The volcanic–stratigraphic succession in the study area, from base to top, comprises the Baiyingaolao Formation, the basal andesitic conglomerate of the Longjiang Formation, and the Longjiang Formation andesites. Geochronological results indicate that the underlying rhyolitic tuff of the Baiyingaolao Formation yields an age of 130.0 ± 0.1 Ma. Within the andesitic conglomerate overlying the unconformity, andesitic clasts yield an age of 135.8 ± 1.1 Ma, whereas the matrix provides a youngest detrital zircon population age of 130.7 ± 1.0 Ma, constraining the maximum depositional age of the conglomerate. The overlying andesite of the Longjiang Formation gives an eruption age of 125.6 ± 0.8 Ma. These data indicate that the main phase of Longjiang Formation volcanism occurred at ~125.6 Ma, and the basal conglomerate was deposited after ~130.7 Ma. Combined with the ~130 Ma age of the underlying Baiyingaolao Formation and the presence of weathering crusts and erosional surfaces between the two formations, the sedimentary hiatus and exhumation event represented by this unconformity are precisely constrained to have occurred between ~130 Ma and 125.6 Ma. The timing of this unconformity closely coincides with the regional transition in magmatic assemblages from bimodal to andesitic compositions, suggesting that it records a significant tectonic adjustment event in the Great Xing’an Range during the middle to late Early Cretaceous. This finding provides key chronological evidence for understanding the episodic tectonic evolution of Northeast Asia during the Late Mesozoic. Full article

Hydropower is a cornerstone of global renewable energy; however, reservoir sedimentation directly undermines its benefits and operational lifespan. A critical, often overlooked, aspect of sedimentation is the compaction of fine-grained deposits, which introduces systematic discrepancies between standard siltation calculation methods. This study addresses this gap by developing a machine learning-based model to quantify sediment compaction and correct siltation estimates using the Xiluodu Hydropower Station on the Jinsha River, China, as a case study from 2014 to 2020. Based on hydrological, sediment, and fixed-section monitoring data, we applied five machine learning algorithms (Linear Regression, Neural Network, Random Forest, Gradient Boosting, and Support Vector Regression) to establish a relationship between the compaction thickness and the following key predictors: Year, Cumulative Sediment Thickness, Annual Sediment Thickness, and Distance to the Dam. The results demonstrate that the Neural Network (NN) model significantly outperforms traditional models, effectively capturing complex, nonlinear compaction dynamics with strong predictive accuracy (test R² = 0.766, RMSE = 0.047 m) and no significant overfitting. SHAP analysis revealed the dominant influences of consolidation time (years) and overburden stress (Cumulative Sediment Thickness), linking the model’s predictions to fundamental geotechnical principles. Applying the NN model to correct for the cross-sectional volume method markedly improved its consistency with the independent sediment transport method, reducing the average relative difference from −33.7% to −6.5% (2016–2020). This study provides the first quantitative, continuous (198 km, 221 sections) assessment of reservoir-scale sediment compaction, confirming its widespread existence and demonstrating its critical role in the long-standing methodological discrepancies. Our study transformed compaction from an acknowledged phenomenon into a quantifiable correction, offering a novel, data-driven framework to enhance the accuracy of reservoir sedimentation assessments globally. Full article

Abandoned mining areas provide valuable opportunities to investigate ore-forming processes, supergene mineral transformations, and the geochemical behaviour of metals. In this sense, the old Preguiça mine (Beja, Portugal), exploited for Fe–Zn–Pb, was studied providing new mineralogical and geochemical data aimed at improving the understanding of the secondary mineral assemblages of this deposit. A total of 70 samples collected from three accessible underground levels (first, second and third) and mine waste, complemented by 16 samples from a deeper level (fourth) previously collected, were analysed using X-ray diffraction (XRD), scanning electron microscopy (SEM), and a portable X-ray fluorescence (pXRF) equipment. Mineralogical phases are dominated by a wide range of secondary oxides, carbonates, arsenates, vanadates, silicates, phosphates and sulphates, but remnants of primary sulphides were also found. The following minerals can be emphasised: goethite, hematite, calcite, dolomite, descloizite, willemite, mimetite, cerussite, smithsonite and fraipontite. The presence of massicot in the Preguiça mine, is described for the first time. Bulk geochemical analyses show high concentrations of Fe, Ca, Zn and Pb, consistent with the observed mineralogy. The presence of vanadium- and arsenic-bearing minerals highlights the occurrence of critical raw materials, supporting the importance of reassessing other abandoned mining areas in the context of sustainable resource management and strategic raw-material planning. Full article

Rare earth elements (REEs) play a critical role in provenance tracing and the environmental reconstruction of the Earth. However, systematic investigations into the geochemical behavior and fractionation mechanisms of REEs during halite crystallization in brine–salt systems remain limited. This study reports new trace element and REE data for Late Cretaceous halites from the Thakhek Basin, Laos. Ratios of Sr/Ba, Sr/Cu, and V/Cr indicate a marine origin for the halites, which formed under hot climatic and oscillating oxidizing–anoxic redox conditions. Both primary and secondary halites display uniform Post-Archean Australian Shale (PAAS)-normalized REE distribution patterns, characterized by relative enrichment in medium rare earth elements (MREE) and depletion in light (LREE) and heavy rare earth elements (HREE). Similar REE patterns are also observed in halites from other modern and ancient, continental and marine salt basins worldwide. These observations suggest that the influences of parent brine composition and external provenance supplies on REE fractionation are negligible, given the consistent source, salinity, and redox conditions recorded in these halites. Accordingly, REE fractionation in halite was largely controlled by crystallographic effects, with aqueous MREE preferentially incorporated into halite crystals during deposition. In addition, the relatively lower Zr/Hf ratios in secondary halites compared to primary halites further validate the utility of the Zr/Hf ratio for distinguishing authigenic halite from salt modified by diagenesis, weathering, dissolution, or recrystallization. While our results establish a fundamental REE distribution pattern for halite, further research is needed to better constrain the underlying fractionation mechanisms of REEs in evaporite minerals within brine–salt systems. Full article

Oil and gas exploration conducted in the main fault zone of the Fuman Oilfield has yielded large-scale and high-production results. Against this background, the non-fault zone has emerged as a new domain for oil exploration endeavors. Nevertheless, the establishment of a unified sequence division scheme for the study area remains unachieved, primarily constrained by two key factors: first, the high costs associated with ultra-deep high-density coring operations; and second, the inconspicuous response characteristics exhibited by logging curves. This absence of a standardized scheme has further impeded the progress of oil and gas exploration in the non-main fault inter-region within the study area. Consequently, the present study is based on multi-source data, including seismic data, logging data, and field outcrop data. Magnetic susceptibility measurements from the cement plant section and natural gamma-ray logging data from the Yangjikan section were systematically analyzed to establish cyclostratigraphic frameworks. A sedimentary noise model (SNM) was employed to reconstruct Holocene sea-level fluctuations, enabling precise sequence stratigraphic subdivision within the Fuman Area. Results demonstrate that the Middle-Lower Ordovician Yijianfang–Penglaiba Formations retain robust astronomical cyclicity, validated by high-fidelity orbital forcing signals. Notably, the DYNOT (Dynamic Noise After Orbital Tuning) model effectively decouples orbital-driven sea-level oscillations from local depositional noise, offering a novel approach for sequence boundary identification. This methodology reveals a hierarchical sequence architecture comprising four third-order sequences and 11 fourth-order sequences within the Yijianfang–Penglaiba Formations. Such a framework provides critical insights into facies distribution patterns and non-fault-controlled exploration potential in the Fuman Basin. Full article

Identifying the specific sources of heavy metal accumulation in intensive agricultural landscapes is essential for ensuring soil sustainability and food security. In this study, we independently carried out a high-density regional geochemical survey and high-resolution field sampling in the Yangtze–Huaihe Watershed, Eastern China, and used the original sample dataset to distinguish between geogenic backgrounds and anthropogenic enrichments. By employing the APCS-MLR model, four distinct pollution sources were quantitatively identified: natural pedogenesis, agricultural activities, traffic emissions, and industrial inputs. Results demonstrated that while most heavy metal concentrations remained below national safety thresholds, Cd and Hg exhibited significant topsoil enrichment, signaling potential ecological risks. Source apportionment revealed that natural sources primarily controlled As, Cr, Ni, and Pb, with the contribution ranging from 41% to 70%. In contrast, traffic emissions (e.g., tire wear and fuel combustion) emerged as the dominant source for Cd (68%), Zn (55%), and Cu (34%), while industrial activities accounted for a substantial 89% of Hg accumulation via atmospheric deposition. Notably, despite the region’s intensive cultivation, agricultural practices played a surprisingly minor role in heavy metal accumulation. These findings highlight that the accumulations from traffic and industry now account for approximately 50% of the total heavy metal load in the region. Our results underscore the critical importance of high-resolution spatial data for precise source identification and suggest that implementing vegetative buffer zones and stricter industrial emission controls are imperative to mitigate further soil degradation in similar agricultural watersheds. Full article

Unmanned aerial vehicles (UAVs) are an alternative to traditional pesticide applications in orchards. Particularly, drones are an example of UAVs that have increased in popularity in recent years; however, relatively few studies have evaluated how spraying operation modes interact with other drone parameters within a single experimental framework. This study evaluated the effects of operation mode, application volume, flight height, and droplet size on spray coverage, droplet density, droplet spectra, and droplet size uniformity using the spraying drone DJI Agras T40 under a simulated canopy structure. A four-factorial experimental design was used; treatments included three operation modes (i.e., standard mode, fruit-tree mode, and spinning mode), two application volumes (i.e., 37.4 L/ha and 74.8 L/ha), two flight heights (i.e., 3 m and 5 m), and two droplet sizes (i.e., 150 μm and 300 μm). Operation mode was among the most influential factors affecting spray deposition quality. The spinning mode achieved the highest overall spray coverage (20.81%) and droplet density (172.44 drops/cm²), while the standard mode provided the most uniform spatial distribution. Results from the interaction analyses indicated that the parameter combination that produced the highest spray coverage within the tested ranges was an application volume of 74.8 L/ha, a flight height of 3 m, and a droplet size of 150 μm in the standard mode. For the fruit-tree mode, the highest spray coverage was observed at an application volume of 74.8 L/ha, a flight height of 5 m, and a droplet size of 300 μm. For the spinning mode, the combination associated with the highest spray coverage was 74.8 L/ha, 3 m, and 300 μm. In conclusion, the results provide data-driven guidance on how drone operational parameters influence spray deposition and can support future validation under commercial orchard conditions. Full article

The study presents new data on the distribution, mapping, and morphostratigraphic characteristics of pediment deposits in the Montefeltro region (Italian Apennines), within the Val Marecchia Nappe. The Montefeltro landscape represents a clear example of morphology controlled by lithostructural features, with reliefs emerging from the surrounding terrain due to selective erosion. Its evolution has also been strongly influenced by climatic variations during the Middle–Late Pleistocene and the Holocene. Broad, gently sloping surfaces at the base of structural reliefs, together with associated debris deposits, are interpreted as erosional–depositional pediments formed under cold-climate, periglacial conditions during major Pleistocene glacial phases. Stratigraphic data from boreholes allowed the identification of pediment boundaries, thicknesses, and spatial extent, enabling reconstruction of the relict paleotopography and correlation with fluvial terraces. Two distinct lithological assemblages indicate different sediment sources and slope evolution pathways. Over time, pediments became disconnected from the present topography and were progressively dissected and terraced by fluvial incision, while recent slope adjustment is limited to modern drainage systems. This evolution reflects the combined influence of tectonic structure, lithology, and Quaternary climate change, confirming a regional trend of intensified fluvial deepening in the Marche Apennines. The study focuses on three representative areas: San Marino, Montecopiolo and Sassi Simone and Simoncello. Full article

Background/Objectives: Intramuscular fat deposition is a key determinant of beef quality in Japanese Black cattle, and the fat area ratio of the rib eye (FAR) is highly correlated with Beef Marbling Standard scores. Methods: To identify genetic variants underlying variation in the FAR, we conducted a genome-wide association study (GWAS) followed by whole-genome sequence–based fine mapping in a Hyogo Japanese Black population (n = 432). Animals were genotyped using the Illumina BovineSNP50v3 BeadChip, and association analysis was performed using residuals derived from a linear mixed model accounting for fixed and random effects. Results: A significant association signal was detected on BTA17 (λ = 1.09), with the top single nucleotide polymorphism (SNP) located at 17:72,329,662 (p = 3.60 × 10⁻⁶). To refine the candidate region, we analyzed whole-genome resequencing data from 42 Hyogo Japanese Black cattle and identified a distinct linkage disequilibrium (LD) block spanning 71–74 Mbp on BTA17. Among 4292 variants within genes showing LD (r² ≥ 0.1) with the top SNP, 96 variants with strong LD and predicted functional effects were selected for validation. Genotyping in the Hyogo population revealed that a missense variant in gamma-glutamyltransferase 1 (GGT1) (c.589G>A, p.Asp197Asn) showed the strongest association with FAR (p = 3.89 × 10⁻⁶). A 5′UTR variant in GGT1 (c. −256G>T) and a missense variant in solute carrier family 5 member 1 (SLC5A1) (c.32C>T, p.Thr11Met) also exhibited significant associations and strong LD with the top SNP (r² > 0.7). GGT1 is involved in glutathione metabolism, whereas SLC5A1 encodes a sodium–glucose cotransporter implicated in nutrient sensing and metabolic regulation. Conclusions: Although functional validation is required, these variants represent strong positional and biological candidates underlying the BTA17 quantitative trait loci (QTL). The identified polymorphisms may provide useful molecular markers for optimizing genetic improvement of marbling-related traits within the Hyogo Japanese Black population. Full article

Existing studies have extensively investigated sand-rich shallow-water deltas. However, the sedimentary characteristics and internal architecture of mud-rich deltas remain poorly understood. In this study, two comparative flume experiments were conducted with sand–mud ratio as the key variable. High-resolution topographic data were acquired using a laser scanner to extract geometric parameters of the architectural elements. Three-dimensional architectural models were established and validated against the Ganjiang Delta (sand-rich) and the Ouchi River Delta (mud-rich) in China. The results reveal contrasting depositional styles: sand-rich deltas develop dense, laterally migrating braided channels with broad fan-shaped morphologies, forming blanket-like geometries that consist of vertically stacked and laterally amalgamated channel complexes with good connectivity; mud-rich deltas are characterized by stable channels with limited bifurcation, forming elongated finger-like morphologies with isolated, ribbon-like channel–mouth bar complexes that exhibit strong lateral heterogeneity and poor connectivity. These contrasting behaviors are governed by sediment cohesion: non-cohesive sands promote channel migration and dispersion, whereas cohesive silt and mud stabilize channels and focus sediment transport along main conduits. The experimental models successfully reproduce natural delta end-members, confirming the universal control of the sand–mud ratio. The established quantitative relationships provide a predictive basis for subsurface reservoir characterization and the formulation of differentiated development strategies. Full article

Background: Cardiac amyloidosis (CA) is an increasingly recognized cause of heart failure with preserved ejection fraction, resulting from myocardial deposition of misfolded amyloid fibrils derived predominantly from transthyretin (ATTR wild-type [ATTRwt] or variant [ATTRv]) or immunoglobulin light chains (AL). Despite advances in noninvasive imaging and disease-modifying therapies, delayed diagnosis remains common, and clinically actionable molecular biomarkers for early detection, phenotypic discrimination, and therapeutic monitoring are limited. MicroRNAs (miRNAs), small noncoding regulators of post-transcriptional gene expression, have emerged as key modulators of cardiovascular remodeling and systemic amyloid biology. Methods: We performed a comprehensive review of experimental, translational, and clinical studies to evaluate the role of miRNAs in transthyretin and light-chain cardiac amyloidosis, incorporating data from myocardial tissue analyses, circulating miRNA profiling, and mechanistic studies in cellular and animal models. Results: Dysregulated miRNA networks contribute to amyloid-induced cardiac injury by modulating mitochondrial energetics, oxidative stress, inflammation, fibrosis, proteostasis, and neurocardiac signaling. Specific miRNAs, including members of the miR-21, miR-29, and miR-30 families, as well as miR-150-5p and miR-339, have been associated with amyloid burden, adverse myocardial remodeling, plasma cell biology, and disease severity. Distinct circulating and tissue miRNA signatures differentiate transthyretin from light-chain cardiac amyloidosis and correlate with functional status, heart failure biomarkers, and clinical outcomes. Conclusions: MiRNAs represent promising diagnostic and prognostic biomarkers in cardiac amyloidosis and offer mechanistic insights into disease pathogenesis. Integration of miRNA profiling with multimodality imaging and emerging RNA-based therapeutics may enable earlier diagnosis and support precision management of amyloid-related heart failure. Full article

The Jiaodong gold concentration area, one of the most important gold metallogenic belts in China, has long been the focus of contentious debates regarding the genetic mechanisms and timing of gold mineralization. This study presents the new monazite U-Pb and pyrite Rb-Sr isotopic chronology data for the No. I ore zone of the Xidouya gold deposit, integrated with H-O-S isotopic geochemical analyses, to systematically investigate the mineralization age, ore-forming fluid sources and material provenance of the deposit. The main mineralization age of the deposit is constrained to 117 Ma, which is highly consistent with the regional mineralization peak of 120 ± 5 Ma in the Jiaodong gold concentration area. The δD values of the fluids range from −88.0‰ to −75.0‰ (mean = −82.6‰), while the δ¹⁸O_H2O values are calculated to be between 4.6‰ and 6.1‰. H-O isotopic data indicate that the ore-forming fluids of the Xidouya gold deposit originated from a mixed magmatic and meteoric source. As mineralization progressed from Stage I through Stage III, there was a detectable trend of increasing meteoric water involvement and a general decrease in δD and δ¹⁸O_H2O values. This signature indicates that the initial mineralizing system was dominated by primary magmatic water which subsequently underwent significant water–rock interaction with Early Cretaceous granitic bodies and progressive dilution by meteoric fluids in an open tectonic environment. Furthermore, sulfur isotopes (average δ³⁴S = +7.43‰) and the initial strontium isotope ratio (⁸⁷Sr/⁸⁶Sr = 0.71012) support a mixed-source model for the ore-forming materials, likely dominated by the anatexis of ancient crust with potential minor mantle-derived contributions. During the Early Cretaceous, lithospheric thinning and extension in the North China Craton (NCC) triggered large-scale magmatism and mineralization. The Xidouya gold deposit is a direct product of these regional tectono-magmatic-mineralizing events. This study provides new high-precision isotopic dating data for the Xidouya gold deposit, clarifies the evolutionary history of ore-forming fluids and the supply mechanism of ore-forming materials, and provides important theoretical insights and practical references for gold prospecting and exploration in the eastern part of the Jiaodong gold concentration area. Full article

Background/Objectives: This study aimed to evaluate pancreatic steatosis and its association with the triglyceride index in patients with pheochromocytoma and paraganglioma (PPGL). Methods: In this retrospective single-center study conducted between 2 January 2019 and 30 April 2024, thirty-three patients with confirmed PPGL and thirty-three age-, sex-, and body mass index (BMI)-matched healthy controls were evaluated. The mean age of the study population was 49.7 ± 12.3 years, and 32 participants (48.5%) were female. Pancreatic fat infiltration was assessed via computed tomography (CT). Body composition parameters, including visceral fat area (VFA), subcutaneous fat area (SFA), skeletal muscle area (SMA), and skeletal muscle area index (SMAI), were also measured. Laboratory data, including lipid profiles, glucose, hemoglobin A1c (HbA1c), and triglyceride index (TyG), were analyzed. Results: Pancreatic steatosis, as indicated by significantly lower pancreatic attenuation values, was markedly higher in the PPGL group compared to controls (p < 0.001). No significant differences were observed between the groups in terms of VFA (p = 0.218), SFA (p = 0.413), SMA (p = 0.669), or SMAI (p = 0.562). Pancreatic fat was positively correlated with triglyceride levels, VLDL, TyG index, BMI, and VFA. No correlation was found between catecholamine levels and pancreatic steatosis. Conclusions: Our findings indicate an increase in pancreatic steatosis in patients with PPGL, suggesting a potential association between catecholamine excess and the development of ectopic fat deposition. These results support considering pancreatic fat as a marker of metabolic dysfunction in PPGL. Full article

As mineral exploration increasingly targets deeper and more geologically complex terrains, the need for reliable predictive models becomes critical to mitigating exploration risk and improving cost efficiency. Correspondingly, the effectiveness of deep mineral exploration strategies depends substantially on the effectiveness and precision of three-dimensional mineral prospectivity mapping (3D MPM) models. However, the inherent spatial non-stationarity—where ore grade variability changes across geological domains—and the strongly skewed distribution of high-grade samples present a dual challenge. Conventional methods, which primarily rely on mean-based regression, often struggle to adequately address this dual challenge, limiting their predictive performance in complex geological settings. To address these issues, this paper proposes a pinball-loss-guided, global–local fusion Transformer model within a unified framework for 3D MPM. It leverages a multi-head self-attention mechanism with global–local fusion to capture long-range dependencies and global geological contexts, while incorporating local feature extraction modules to adaptively model spatially varying mineralization controls, jointly optimized through a pinball loss function to address mineralization distribution skewness. The proposed framework was first rigorously evaluated using the Xiadian gold deposit as a case study. Bootstrap analysis of the ablation experiments confirmed its predictive performance in terms of quantile-specific accuracy and prediction interval (PI) calibration. Ten rounds of random data splits provided further confirmation of the model’s stability. Subsequently, the validated model was applied to prospectivity mapping in unexplored regions, leading to the delineation of several high-potential exploration targets. Finally, comparative analyses with state-of-the-art machine learning methods were conducted, which further validated the competitive fitting capability of the proposed framework. Full article