Search Results (91)

We report here, for the first time on the Nubian Shield, the western half of the Arabian–Nubian Shield (ANS), pegmatite-hosted pockets with a unique mineralogy, including pyroxmangite. It represents the second discovery on the ANS, where the first one was at Jabal Aja on the Arabian Shield, the eastern half of the ANS. One of the most remarkable aspects of pyroxmangite is its rarity and the potential economic value of its use in jewelry and decorative applications. Pegmatites are associated with A-type granites of the Gabal El-Bakriya intrusion (GEBI), Eastern Desert, Egypt. Mineralized pegmatites occur at the margin of the alkali-feldspar granite and exhibit gradational contacts with the host rocks. The pegmatites were emplaced as plugs and dikes within the intrusion and along its periphery. Pyroxmangite appears as coarse-grained, massive black aggregates or as disseminated crystals. The pegmatites are composed of K-feldspars and quartz, with subordinate amounts of albite, micas, and mafic minerals. Accessory phases include monazite-(Ce), zircon, fergusonite, xenotime, fluorite, pyrochlore, allanite, thorite, bastnäsite, samarskite, cassiterite, beryl, and pyrochlore. Pyroxmangite-bearing assemblages consist essentially of pyroxmangite and garnet, with accessory pyrochroite, quartz, zircon, magnetite, and fluorite. Geochemically, the pegmatites are highly evolved, with elevated SiO₂ content (76.51–80.69 wt.%) and variable concentrations of trace elements. They show significant enrichment in Nb (Nb > Ta), Y, REE, Zr, Th, U, and F, consistent with NYF-type pegmatites. REE contents range from 173.94 to 518.21 ppm, reflecting diverse accessory mineral assemblages. Tectonically, the pegmatites crystallized in a post-collisional setting, representing a late-stage differentiate of the A-type GEBI magma. Mineralization is concentrated in the apical and marginal zones of the granitic cupola and is dominated by barite, fluorite, Nb-Ta oxides, REE minerals, and uranium-bearing phases. The highly evolved granites, greisens, pegmatites, and quartz-fluorite veins of the GEBI have a high economic potential, deserving further exploration. Full article

To evaluate the feasibility of a virtual overlay tester (OT), a modeling approach was proposed based on the discrete element method (DEM). Simulations were conducted on three types of asphalt mixtures across three different thickness conditions. Through the analysis of the load/displacement curves, crack propagation paths, force chains, and contact force characteristics, it was observed that the peak loads decrease with increasing thicknesses, indicating a notable size effect. The complexity of the crack path was positively correlated with the particle size along the path and the fractal dimension. Coarse aggregates can inhibit crack propagation to some extent. Prior to reaching the peak load, compressive force chains in asphalt concrete-13 (AC13) and large stone porous asphalt mixture-30 (LSPM30) exhibited a symmetrical and divergent distribution along the crack, while tensile force chains formed an arch-like pattern. After the peak load, compressive force chains were symmetrically distributed in an arch shape along the crack. In stone mastic asphalt-13 (SMA13), compressive forces were transmitted along coarse aggregates, forming several continuous vertical paths. The proportion of strong compressive force chains to total compressive force chains across the three gradations ranged from 0.74 to 0.83, while the corresponding proportion for tensile force chains ranged from 0.72 to 0.78. Full article

Academic researchers in technical and policy fields tend to pay little attention to the metaphysical and ontological ‘priors’ that nevertheless structure and determine scientific strategies and results. Green political agendas rooted in ecological modernization (EM) are distinguished from antecedent visions predicated on biophysical limits. Net zero is shown to be rooted in a project of global EM. Ecomodernism is analyzed in relation to its principal actors, geopolitical context and underlying metaphysics and anthropology. It is driven by non-negotiable societal priorities (‘ends’), which themselves derive from a particular set of technical ‘means’. The top-down version of the Fourth Industrial Revolution (IR4.0) and new paradigm of global net zero constitute an integrated agenda of eco-modernism. Global net zero cannot hope to achieve its own metabolic goals in respect of either energy flows or the circular economy. A competing, bottom-up and distributed model of the IR4.0 could potentially achieve these targets without falling prey to the Jevons paradox. This potential turns on the greater capacity of low-overhead, prosumer models to nurture less materialist cultural priorities that are more communitarian and family-oriented. A smart energy system that emerges in the context of distributed, domestic and informal production is much more likely to mirror the complex, infinitely gradated and granular pattern of oscillating energy transfers that are characteristic of biological systems. From an ecological economic perspective, such a bottom-up approach to the IR4.0 is much more likely to see the orders of magnitude reduction in the unit energetic cost of social complexity envisaged, in principle, by net zero. Through this comprehensive review of the metaphysical and ontological priors of mainstream IR4.0, researchers in the linked fields of energy and circular economy are presented with a wider range of potential options less constrained by preconceived assumptions about the ‘ends’ of societal development and progress. Full article

Local scour around bridge piers is one of the primary causes of structural failure in bridges. Therefore, this study focuses on addressing the estimation of maximum scour depth (d_sm), which is essential for safe and resilient bridge design. Many studies in the last eight decades have included metadata collection and developed around 80 empirical formulas using various scour-affecting parameters of different ranges. To date, a total of 33 formulas have been comparatively analyzed and ranked based on their predictive accuracy. In this study, novel formulas using semi-empirical methods and gene expression programming (GEP) have been developed alongside an artificial neural network (ANN) model to accurately estimate d_sm using 768 observed data points collected from published work, along with eight newly conducted experimental data points in the laboratory. These new formulas/models are systematically compared with 74 empirical literature formulas for their predictive capability. The influential parameters for predicting d_sm are flow intensity, flow shallowness, sediment gradation, sediment coarseness, time, constriction ratio, and Froude number. Performances of the formulas are compared using different statistical metrics such as the coefficient of determination, Nash–Sutcliffe efficiency, mean bias error, and root-mean-squared error. The Gauss–Newton method is employed to solve the nonlinear least-squares problem to develop the semi-empirical formula that outperforms the literature formulas, except the formula from GEP, in terms of statistical performance metrics. However, the feed-forward ANN model outperformed the semi-empirical model during testing and validation phases, respectively, with higher CD (0.790 vs. 0.756), NSE (0.783 vs. 0.750), lower RMSE (0.289 vs. 0.301), and greater prediction accuracy (64.655% vs. 61.935%), providing approximately 15–18% greater accuracy with minimal errors and narrower uncertainty bands. Using user-friendly tools and a strong semi-empirical model, which requires no coding skills, can assist designers and engineers in making accurate predictions in practical bridge design and safety planning. Full article

Rapid expansion of global transportation infrastructure leads to the accumulation of vast quantities of reclaimed asphalt pavement (RAP). Recycling RAP is essential for reducing environmental impacts. However, current recycling practices typically limit RAP content to below 30%. Increasing RAP content in asphalt mixtures—especially beyond 50%—offers a more sustainable approach, but also introduces challenges in performance, design, and implementation. This study presents a case in which the hot central plant recycling asphalt mixture containing 50% RAP, enhanced with an active rejuvenating agent, was used for the lower layer of the Jianghe Expressway. The aggregate gradation was designed using the Marshall method, with the optimal asphalt–aggregate ratio determined to be 3%. The average compaction degree was 98.9%, the infiltration coefficient ranged from 6.43 mL/min to 23.77 mL/min, and the standard deviation of flatness did not exceed 1.0. However, material shoving was observed during paving, suggesting that, with appropriate adjustments, the technique can be optimized for large-scale implementation. The gradation of the RAP material showed minimal deviation from the design gradation, remaining within ±5%. The compaction scheme with eight roller passes and a loose paving coefficient of 1.35 yielded superior compaction performance. Full article

Based on mechanical experiments conducted on bulk raw coal and coal of different types in order to explore the correlations between the fractal dimension and the grain size gradation and strength parameters of coal samples, the fractal statistics method was used to statistically analyze the grain size distribution characteristics of tectonic soft coal, while fractal theory was applied to study the grain size fractal characteristics of tectonic soft coals of categories III–V. The results of this study show that coal types III–V have increasing fractal dimension numbers, and the content of coarse particles decreases with an increasing fractal dimension number. Within this sampling range, the Class V coal is better graded, and the fractal dimension number decreases as the distance of the sampling point from the fault zone increases. In the direct shear experiments, the internal friction angle of the bulk raw coal decreased linearly with an increasing fractal dimension number, and the regularity of the cohesive force and the fractal dimension number was not strong, but the adhesion cohesion of the types of coal exhibited a positive exponential relationship with the fractal dimension, and the relationship between the internal friction angle and the fractal dimension was not strong. There was a positive exponential relationship, and the internal friction angle was relatively stable. The uniaxial compressive strength of the types of coal exhibited a good correlation with the coefficient of firmness of the coal samples and the fractal dimension, and the coefficient of firmness of the coal samples was the main factor influencing the uniaxial compressive strength of the types of coal compared with the particle size gradation. Full article

With the continuous depletion of natural river sand resources and the escalating ecological degradation caused by excessive sand mining, manufactured sand has emerged as a sustainable and environmentally favorable alternative aggregate, playing an increasingly important role in the advancement of green construction materials. Nevertheless, the shrinkage behavior of manufactured sand concrete (MSC) exhibits significant deviations from that of conventional natural sand concrete due to differences in the material characteristics. Existing shrinkage prediction models—such as ACI 209, CEB-FIP 2010, B3, and GL 2000—fail to adequately incorporate the specific properties and substitution effects of manufactured sand, thereby limiting their predictive accuracy and applicability. To bridge this gap, the present study conducted a systematic evaluation of the four aforementioned classical shrinkage prediction models based on experimental data from MSC specimens incorporating varying replacement rates of manufactured sand. The findings revealed that models such as B3 and CEB-FIP 2010 neglected the influence of critical characteristics of manufactured sand—namely, particle morphology, gradation, and stone powder content—on the cementitious matrix and interfacial transition zone, which led to substantial prediction discrepancies. Accordingly, a nonlinear regression-based correction function was developed, introducing the manufactured sand content as a key influencing variable to recalibrate and enhance the ACI 209 and GL 2000 models for a more accurate application to MSC. The modified models exhibited markedly improved fitting performance and predictive robustness across the full range of manufactured sand replacement ratios (0–100%), thereby offering a more reliable framework for modeling the shrinkage development of MSC. Full article

HPMC, regulating slurry properties, is widely used in cement-based materials. Research on the application of HPMC in gangue slurry is still in its early stages. Moreover, the interactive effects of various factors on gangue slurry performance have not been thoroughly investigated. The work examined the effects of slurry concentration (X₁), maximum gangue particle size (X₂), and HPMC dosage (X₃) on slurry performance using response surface methodology (RSM). The microstructure of the slurry was characterized via scanning electron microscopy (SEM) and polarized light microscopy (PLM), while low-field nuclear magnetic resonance (LF-NMR) was employed to analyze water distribution. Additionally, industrial field tests were conducted. The results are presented below. (1) X₁ and X₃ exhibited a negative correlation with layering degree and slump flow, while X₂ showed a positive correlation. Slurry concentration had the greatest impact on slurry performance, followed by maximum particle size and HPMC dosage. HPMC significantly improved slurry stability, imposing the minimum negative influence on fluidity. Interaction terms X₁X₂ and X₁X₃ significantly affected layering degree and slump flow, while X₂X₃ significantly affected layering degree instead of slump flow. (2) Derived from the RSM, the statistical models for layering degree and slump flow define the optimal slurry mix proportions. The gangue gradation index ranged from 0.40 to 0.428, with different gradations requiring specific slurry concentration and HPMC dosages. (3) HPMC promoted the formation of a 3D floc network structure of fine particles through adsorption-bridging effects. The spatial supporting effect of the floc network inhibited the sedimentation of coarse particles, which enhanced the stability of the slurry. Meanwhile, HPMC only converted a small amount of free water into floc water, which had a minimal impact on fluidity. HPMC addition achieved the synergistic optimization of slurry stability and fluidity. (4) Field industrial trials confirmed that HPMC-optimized gangue slurry demonstrated significant improvements in both stability and flowability. The optimized slurry achieved blockage-free pipeline transportation, with a maximum spreading radius exceeding 60 m in the goaf and a maximum single-borehole backfilling volume of 2200 m³. Full article

Accurately predicting the permeability of coarse-grained soils is crucial for ensuring geotechnical safety and performance. In this study, 64 coarse-grained soil (CGS) samples were designed using a negative exponential gradation equation (NEGE), and computational fluid dynamics–discrete element method (CFD-DEM) coupled seepage simulations were conducted to generate a permeability coefficient (k) dataset comprising 256 entries under varying porosity and gradation conditions. Three machine learning models—a neural network model (BPNN), a regression model (GPR), and a tree-based model (RF)—were employed to predict k, with hyperparameters optimized via particle swarm optimization (PSO) and four-fold cross-validation applied to improve generalization. Gray relational analysis (GRA) revealed that all input parameters (α, β, d_max, n) significantly influence k (R > 0.6). The interquartile range (IQR) method confirmed data suitability for modeling. Among the models, BPNN achieved the best performance (R² = 0.99, MAE = 1.5, RMSE = 2.9, U₉₅ = 0.4), effectively capturing the complex nonlinear relationship between gradation and permeability. GPR (R² = 0.92) was hindered by kernel selection and noise sensitivity, while RF (R² = 0.97) was limited by its discrete regression nature. Compared to a traditional empirical model (R² = 0.9031), BPNN improved prediction accuracy by 10.13%, demonstrating the advantage of data-driven methods for evaluating CGS permeability. Full article

The presence of residual non-aqueous phase liquid (NAPL) in low-permeability lens aquifers of ten results in a “tailing” effect, ecological deterioration and poor sustainability, which is a primary factor contributing to remediation failures at NAPL-contaminated sites. This issue is largely due to the poorly understood mechanisms by which NAPL residuals interact with low-permeability lens aquifers. To elucidate these mechanisms, this study conducted a series of column experiments, varying the permeability contrast (Kmn), lens sizes (ϕ), and hydraulic gradients (I). Complementary techniques such as mercury intrusion porosimetry and particle size analysis were employed to characterize the aquifer and lens materials. The data obtained include the residual NAPL saturation (Sr), groundwater flow velocity (V), pore size distribution, particle size, and gradation under different experimental conditions. Sensitivity analyses using range and variance analyses identified the following order of effect on NAPL residuals in low-permeability lens aquifers: Kmn > ϕ > I. Correlation analyses further suggest that the governing mechanisms are predominantly mediated by changes in the average particle size, macroporosity (pores > 60 μm), mesoporosity (pores = 30~60 μm), and microporosity (pores = 2~30 μm), as well as abrupt changes in pore size at the interface between the lens and the aquifer, in addition to V. This study can provide a theoretical basis for green, low-carbon, and sustainable development, such as pollution remediation and ecological environment security. Full article

The precise identification of diseases in tomato leaves is of great importance for precise target pesticide application in a complex background scenario. Existing models often have difficulty capturing long-range dependencies and fine-grained features in images, leading to poor recognition where there are complex backgrounds. To tackle this challenge, this study proposed using YOLO-BSMamba detection mode. We proposed that a Hybrid Convolutional Mamba module (HCMamba) is integrated within the neck network, with the aim of improving feature representation by leveraging the capture global contextual dependencies capabilities of the State Space Model (SSM) and discerning the localized spatial feature capabilities of convolution. Furthermore, we introduced the Similarity-Based Attention Mechanism into the C2f module to improve the model’s feature extraction capabilities by focusing on disease-indicative leaf areas and reducing background noise. The weighted bidirectional feature pyramid network (BiFPN) was utilized to replace the feature-fusion component of the network, thereby enhancing the model’s detection performance for lesions exhibiting heterogeneous symptomatic gradations and enabling the model to effectively integrate features from different scales. Research results showed that the YOLO-BSMamba achieved an F1 score, mAP@0.5, and mAP@0.5:0.95 of 81.9%, 86.7%, and 72.0%, respectively, which represents an improvement of 3.0%, 4.8%, and 4.3%, respectively, compared to YOLOv8s. Compared to other YOLO series models, it achieves the best mAP@0.5 and F1 score. This study provides a robust and reliable method for tomato leaf disease recognition, which is expected to improve target pesticide efficiency, and further enhance crop monitoring and management in precision agriculture. Full article

Vibroflotation has proven to be an effective method for treating loose and unevenly graded coral sand foundations formed through hydraulic filling. In this study, a series of model tests were conducted to investigate the effects of particle gradations on the response of coral sand foundation reinforced by vibroflotation. The main focus was on analyzing the changes in excess pore water pressure (EPWP) and horizontal earth pressure. Cone penetration tests (CPTs) were then used to evaluate the effectiveness of vibroflotation. The results indicate that the maximum settlement occurs after the first vibroflotation, with surface settlement significantly increasing as the distance to the vibro-point decreases. The reinforcement range expands radially, and the foundation can achieve a medium or dense state after vibroflotation. During the penetration stage, the EPWP rapidly peaks and increases with depth. Shallow foundations exhibit a higher excess pore pressure ratio compared to deep foundations. Foundations with lower coarse particle content show higher EPWPs compared to those with higher coarse particle content. Lower vibration frequency results in diminished reinforcement effects in foundations with high coarse particle content and increases the difficulty of penetration. Additionally, the residual soil pressure in foundations with high coarse particle content significantly rises after three vibroflotation reinforcements. The increase in strength after reinforcement is more pronounced because the foundation has a greater coarse particle content. The reinforcement effect diminishes with increasing distance from the vibrator. Full article

Rock fragmentation is a key indicator for evaluating the effects of rock blasting and directly impacts subsequent excavation efficiency. However, predicting rock fragmentation outcomes is challenging due to the complex physical and chemical processes involved in explosive detonation. In this study, a simulation and analysis method for rock blasting fragmentation effects was developed by integrating the finite element method with image processing technology. To validate the reliability of this method, onsite blasting experiments were conducted. Furthermore, the rock blasting parameter of blast hole spacing was optimized based on this proposed method. The results showed that explosive blasting processes vary depending on the charge. Specifically, using water as a decoupling medium led to better blasting outcomes compared to air-decoupled charges. Due to the directional effects along the cylindrical charge, the explosive loading on the blast hole wall first increases and then stabilizes. The method’s feasibility is supported by the good agreement between the gradation curves of rock fragments obtained through onsite sieving tests and simulations in the 50–300 mm range. Additionally, the approach was used to optimize blasting parameters, ensuring that the fragment size distribution curve met the project requirements. Overall, this method can be used for research and analysis of rock blasting fragmentation. Full article

This study analyzes the dynamics of China’s fruit industry using a range of analytical tools, including the location Gini coefficient, industry concentration ratio, spatial autocorrelation index, specialization index, and the industry gravity model. It explores the industry’s evolving characteristics and trends since the economic reforms, culminating in a trajectory map that highlights shifts in the industry’s gravitational center. This study also offers a qualitative analysis of the factors influencing the agglomeration and relocation of fruit production centers. The findings show a steady increase in both total output and yields per unit area within China’s fruit industry over time. Although the overall degree of agglomeration has decreased, regional agglomeration effects remain significant. Furthermore, the data reveal significant spatial autocorrelation in fruit production, indicating a long-term westward shift in core production areas. Different geographic areas exhibit varying levels of gradational shifts, with marked differences in production concentration patterns across different fruit types. This study provides a comprehensive framework for understanding production agglomeration, integrating interdisciplinary methods from statistics and geography. Full article

We report a graded index chalcogenide glass (As₂Se₃)-based photonic crystal fiber having a solid core. The proposed PCF has ultra-high numerical aperture value reaching up to 1.82 for the explored wavelength range of 1.8–10 μm in the mid-infrared region. The value of numerical aperture increases as the pitch increase from 0.92 to 0.96 to 1 micrometer, at a particular value of wavelength. With this high value of numerical aperture, a PCF is capable of gathering a high amount of light in its core. With negative dispersion reaching up to −2000 ps/km/nm at 4.8 µm, the fiber acts as a dispersion-compensating fiber, with confinement loss being close to zero for higher values of wavelength. The confinement loss of the designed PCF is also significantly less and it decreases as the wavelength increases. Also, the value of dispersion is significantly less due to the regular variation in the size of the holes in the transverse direction, as compared to the design when there is no gradation. The design has been optimized with an appropriate value of the perfectly matched layer to achieve the best results. Full article