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With continuous increasing of mining activities, some problems, such as environmental issues, occupy a lot of space, and the risks caused by the instability of mine waste depots are far occurred than ever. One possible way to reduce mentioned problems is to stabilize and reuse mine wastes as road construction materials. On the other hand, the most significant parameter for pavement design, either using empirical or mechanistic–empirical methods, is the resilient modulus (Mr) of road materials, which shows the influence of repetitive loading on the stress–strain behavior of materials. To obtain iron ores, it is required to remove the soil resting on the iron ore storage in deeper layers. This soil is typically in the form of alluvium and is known as mine overburdens (MOs). In this study, after identification of the geotechnical characteristics of two types of MO of the Golgohar mine in Sirjan, Iran, these materials were stabilized by using three different percentages of Portland cement (5, 7, and 9%) and were cured for 7 and 28 days, respectively and the resilient modulus were measured using repetitive triaxial loading equipment at different stress levels. Results show that cement stabilization does not enhance the Mr significantly when bulk stress or confining pressure is low. As the bulk stress or confining pressure increase, the Mr of cement-stabilized MOs increases significantly compared to raw MOs. Another justification is that the Mr of cement-stabilized MOs is a function of bulk stress, and deviatoric stress has a negligible effect on the Mr. The comparison between different nonlinear models revealed that the 'Universal' model has the best fit with the measured Mr values of raw and stabilized MOs. [ABSTRACT FROM AUTHOR]

This paper argues that the failure to implement state technical education in Bolivia was one of the reasons for the country’s economic backwardness. The work makes a key contribution to the history of Bolivian education as it studies aspects not dealt with in the literature so far. First, it details the chronology of the development of technical education in Bolivia and analyses the types of education offered by the State. Second, it looks at the scope of the technical education that was available and whether this adapted to the need for specialised labour that the country’s production activities – which were still pre-industrial – may have had in the nineteenth century. Primary archival sources and periodical publications of the time have been used for this analysis. [ABSTRACT FROM AUTHOR]

In order to solve the problem of surrounding rock support difficulties encountered during TBM excavation in weak strata in coal mines, a steel segment support structure for TBM-excavated tunnels in coal mines was proposed. Full-scale model tests of the steel segment support structure were conducted under different lateral stress coefficients. The deformation and failure modes, bearing capacity, and strain distribution characteristics of the proposed roadway support structure were studied, and the factors influencing the bearing capacity of the support structure were determined, revealing the mechanism of the instability and failure of the support structure. Subsequently, numerical tests of the support structure were conducted to obtain parameters such as the axial force and bending moment, which were difficult to monitor in the full-scale model tests. The results showed that the support structure first experienced local instability at the joints and mid-span, leading to overall instability of the structure. The ultimate bearing capacities of the support structure were 3,972.2 kN and 2,763.2 kN for lateral stress coefficients of λ = 1.0 and 1.5, respectively. The ultimate bearing capacity decreases exponentially with increasing lateral stress coefficient, highlighting the importance of considering tectonic stress in design. Design parameters analysis reveals that rib plate thickness significantly influences bearing capacity, followed by rib plate width, while ring plate thickness has a minimal impact. [ABSTRACT FROM AUTHOR]

Introduction: In the excavation engineering of tunnels and mines in the western cold region, the unloading failure zone is mainly caused by stress release. This study aimed to investigate the deformation and failure mechanism of frozen weakly cemented sandstone (FWCS) when the initial principal stress σ3 was 3, 6, or 10 MPa. Methods: A conventional triaxial compression test and a triaxial unloading test with an unloading rate of 0.05 MPa/s were carried out. Based on the experimental data and mathematical analysis methods, the non-linear criterion was constructed and analyzed. The microfracture characteristics of the damaged surface were studied by scanning electron microscopy (SEM). Results: The results show that compared with conventional triaxial compression and room temperature triaxial compression tests, the strength and plastic deformation characteristics of FWCS during unloading were significantly weakened, with transverse deformation and volume strain increased, showing obvious dilatancy characteristics. Unloading reduced the cohesion of FWCS, increased the internal friction angle, and increased the risk of rock failure. Macroscopic and microscopic analysis revealed the failure mechanism of FWCS. The unloading stress ratio was introduced to establish relationships. A non-linear criterion based on the Mohr–Coulomb strength criterion was established, with the power function strength criterion being more accurate in describing the failure of FWCS. Discussion: This study provides valuable insights into the mechanical properties and failure mechanism of FWCS under unloading conditions, which is beneficial for the excavation engineering of tunnels and mines in the western cold region. [ABSTRACT FROM AUTHOR]

To reveal the rock burst mechanism, the stress and failure characteristics of coal-rock strata under different advancing speeds of mining working face were explored by theoretical analysis, simulation, and engineering monitoring. The relationship between energy accumulation and release was analyzed, and a reasonable mining speed according to specific projects was recommended. The theoretical analysis shows that as the mining speed increases from 4 to 15 m/d, the rheological coefficient of coal mass ranges from 0.9 to 0.4, and the elastic energy of coal mass accumulation varies from 100 to 900 kJ. Based on the simulation, there is a critical advancing speed, the iteration numbers of simulation are less than 15,000 per mining 10 m coal seam, the overburden structure is obvious, the abutment pressure in coal mass is large, and the accumulated energy is large, which is easy to cause strong rock burst. When the iteration number is greater than 15,000, the static force of coal mass increases slightly, but there is no obvious rock burst. Based on engineering monitoring, the mining speed of a mine is less than 8 m/d, and the periodic weighting distance is about 17 m; as the mining speed is greater than 10 m/d, and the periodic weighting distance is greater than 20 m; as the mining speed is 3–8 m/d, and the range of high stress in surrounding rock is 48 m; as the advancing speed is 8–12 m/d, and the high-stress range in surrounding rock is 80 m. Moreover, as the mining speed is less than 8 cut cycles, the micro seismic energy is less than 10,000 J; as the mining speed is 12 cut cycles, the micro-seismic energy is about 20,000 J. In summary, the advancing speed is positively correlated with the micro seismic event; as the mining speed increases, the accumulated elastic energy of surrounding rock is greater, which is easy to cause rock burst. The comprehensive analysis indicates the daily advance speed of the mine is not more than 12 cut cycles. [ABSTRACT FROM AUTHOR]

The document discusses the complexities of rock mechanics, focusing on stability issues in rock engineering and the conditions leading to rock failure. It highlights the importance of interdisciplinary approaches in addressing geotechnical challenges and presents the latest advancements in complex rock mechanics, including mining engineering, underground excavation, and computer technologies. The research papers cover a wide range of topics, such as mining-induced seismicity, hydraulic fracturing, and the mechanical properties of rocks, offering valuable insights into practical engineering applications and theoretical frameworks. [Extracted from the article]

The transient electromagnetic method (TEM) has a wide range of applications in the hydrogeological exploration of mining engineering. This method is highly sensitive to groundwater responses and provides reliable data for the prevention of water-related disasters, such as sudden water surges and gushes. However, there are currently a lack of comprehensive and systematic analyses and summaries regarding the characteristics of magnetic source transient electromagnetic coil devices. Based on the fixed characteristics of the field source, this paper categorizes magnetic source transient electromagnetic coil devices into fixed-source devices and moving-source devices. It provides an in-depth introduction and analysis of the working principles, technical characteristics, existing applications, and development trends of these two types of devices. This study provides important references for the selection and application of magnetic source transient electromagnetic coil devices. In the future, the development of magnetic source transient electromagnetic devices will focus on deeper measurement depths, higher lateral resolution, non-contact coupling, and efficient detection, moving towards multifunctionality, automation, and intelligence. This paper can provide a technical reference for the selection of magnetic source transient electromagnetic coil devices and their application in hydrogeological exploration of mining engineering. [ABSTRACT FROM AUTHOR]

In coal mining operations, it is often challenging to control the deformation of the roadway in front of the working face. The excessive stress from the surrounding rock of the working face and the difficulties in caving the goaf roof have led to a prominent factor that hinders safe and efficient production in coal mines. For this reason, a mechanical model of the stress field in the advance roadway of the working face is established, and the stress evolution law of the surrounding rock before and after cutting the roof of the roadway is analyzed. Key parameters such as cutting depth, cutting angle, and hole spacing are determined through theoretical calculation, numerical simulation with 3DEC numerical software, and field testing. A kind of roof cutting and pressure relief techniques (TCPAF) for enhanced roadway safeguarding in advance mining face is proposed, and its effectiveness is verified through field testing. The results indicate that the stress on the low-stress side of the leading roadway remains slightly increased, while on the high-stress side, stress decreases significantly, optimizing the stress environment of the surrounding rock. In addition, the research results provide a scientific basis for similar conditions of roadway deformation. [ABSTRACT FROM AUTHOR]

The accurate prediction of unconfined compressive strength (UCS) in rock samples is critical for the successful planning, design, and implementation of mining and civil engineering projects. UCS is crucial in assessing the stability and durability of rock masses, which directly influences the safety, efficiency, and cost-effectiveness of construction and excavation operations. Here's a refined version of your text for enhanced clarity and flow: in this part, the execution of the proposed model was compared for both single and hybrid configurations. Hybrid models included support vector regression (SVR) combined with the Seahorse Optimizer (SVSH) and SVR combined with the COOT optimization algorithm (SVCO). For training, 70% of the UCS dataset was utilized, while the remaining 30% was equally divided between testing (15%) and validation (15%). For the model evaluation, several metrics were considered in this work, including the R2, RMSE, WAPE, MAE, and RAE, which ensure fairness in the analysis. The closer the R2 value comes to 1, the better the performance. The error metrics should be close to 0 for better accuracy. From Table 2, one can observe that the result of the standalone SVR model gave an RMSE of 6.213 during training and 9.454 during testing, hence showing poor performance. However, the inclusion of optimization algorithms significantly improved the performance of the SVR framework. Among the hybrid models, the SVSH model had the best performance, with an R2 value of 0.998 and an RMSE of 1.261 during training. The SVCO model performed moderately, with an R2 value of 0.988 during training. [ABSTRACT FROM AUTHOR]

In the field of civil and mining engineering, blasting operations are widely and frequently used for rock excavation, However, some undesirable environmental problems induced by blasting operations cannot be ignored. Blast-induced flyrock is one important issue induced by blasting operation, which needs to be well predicted to identify the blasting zone's safety zone. This study introduces an adaptive weighted multi-kernel learning model (AW-MKL) to provide an accurate prediction of blast-induced flyrock distance in Sungun Copper Mine site. The proposed model uses a combination of multi-kernel learning (MKL) approach and adaptive weighting strategy based on weighted Euclidean distance and modified local outlier factor (MLOF) to maximally improve the predictive ability of kernel ridge regression (KRR). To demonstrate the superiority of the proposed approach, six machine learning models were developed as comparisons, i.e., KRR, RF, GBDT, SVM, M5 Tree, MARS and AdaBoost. The outcomes of the proposed method achieved the highest accuracy in testing phase, with RMSE of 2.05, MAE of 0.98 and VAF of 99.92, which confirmed the strong predictive capability of the proposed AW-MKL in predicting blast-induced flyrock distance. Highlights: An adaptive weighted multi-kernel learning model (AW-MKL) to predict blast induced flyrock. Improve the performance of kernel ridge regression (KRR) using the combination of multi-kernel learning (MKL) and adaptive weighting. Use MKL to reduce the effort devoted in determine optimal kernel. Measure the correlation between model input and training samples using weighted Euclidean distance. Propose a modified local outlier factor (MLOF) to evaluate the uncertainty of training samples. The proposed adaptive weighting strategy assign weights to training samples according to the weighted Euclidean distance and MLOF. [ABSTRACT FROM AUTHOR]

With the shallow resources dwindling, many countries have entered into deep mining one after another. Rock fracture caused by high stress mining disturbances is a significant concern. Destabilization caused by rock fracture not only diminishes productivity, but can also poses the risk of injuries and property damage. Therefore, it is of great significance to investigate the rock fracture mechanism of deep mining to ensure mining safety and improve production efficiency. This paper begins by summarizing key challenges associated with deep mining. Subsequently, it categorizes the outcomes of previous research on this issue into various themes, encompassing laboratory tests, theoretical analyses, numerical simulations and field measurement. This paper provides an overview of a number of representative studies that the growing scenarios and an increase in our understanding of this issue. A summary of the limitations of each contribution is presented, as well as the expected aspects that need to be optimized in the future research. It is found that our knowledge is far from complete, and there are still gaps to be narrowed, particularly concerning the theory of deep rock mechanics, identification of deformation and fracture in deep rock, establishment of three-dimension strength criterion, accuracy of numerical modelling and accuracy of field measurement. The review aims at providing researchers and engineers with a comprehensive understanding of the pertinent issue and guiding them for more in-depth exploration and research. Highlights: Deep mining poses significant challenges and risks due to rock rupture caused by high stress mining disturbances, which directly impact productivity, safety, and property. The review provides a comprehensive understanding of the key challenges associated with deep mining induced by high ground stress and categorizes previous research outcomes into various themes, including laboratory tests, theoretical analyses, numerical simulations, and field measurement. The study highlights the urgent need for a consensus on the concept of "deep" in deep rock mechanics, as it significantly affects the ground stress and requires specialized approaches beyond traditional rock mechanics theories and methods. The advancements in dynamic and static true triaxial apparatus offer crucial technology for accurately measuring various physical and mechanical properties of rocks under deep burial conditions, promoting the development of deep rock mechanics. The comparison and analysis of different strength criteria underscore the significance of establishing a three-dimensional strength criterion that considers geological structure, intermediate principal stress, lode angle, and excavation disturbance, enabling more accurate detection and understanding of the rock fracture mechanism in deep mining. This study focuses on the high ground stress in deep mining has some limitations. Therefore, other influencing factors in deep mining are prospected. [ABSTRACT FROM AUTHOR]

Aiming to address the challenges of determining the coal pillar's width and managing the significant deformation of the surrounding rock in the deep gob-side entry driving, the limiting equilibrium zone theory, employing the operational area of Dongpang Mine 21110 as the engineering setting, states that a coal pillar's appropriate width in the gob-side entry driving falls between 7.9 and 9.8 m. The pattern of vertical stress distribution and the extent of the plastic zone in the roadway for coal pillar widths of 7.0 m, 8.0 m, 9.0 m, and 10.0 m are analyzed, respectively, investigated using the numerical simulation method of FLAC3D. The acceptable coal pillar width in the deep gob-side entry driving is 8.0 m. Combined with the roadway surrounding rock borehole inspection results, the fracture development condition of the roadway's full-face surrounding rock is determined, and the asymmetric aberration characteristics, with significant surrounding rock damage depth at the coal pillar flank location, are obtained. Based on the theoretical calculations, an integrated proposal for a "non-symmetrical bolt and cable anchor" coupling support scheme for the surrounding rock in the gob-side entry driving is put forward. This was applied at the Dongpang coal mine site. Engineering practice shows that leaving an 8.0 m coal pillar width and adopting the "non-symmetrical bolt and cable anchor" support system design can control the deformation of the surrounding rock in the track entry at a reasonable range, which ensures the stability of the surrounding rock in the gob-side entry driving. [ABSTRACT FROM AUTHOR]

Underground coal excavation has caused a series of geological disasters and environmental problems, especially coal mining subsidence. Backfill-strip mining, which combines the advantages of strip mining and backfill mining, can reduce subsidence and improve the recovery rate of coal. Therefore, predicting the impact of backfill-strip mining on the surface environment and strata structure is essential for the better development of backfill-strip mining technology. Here, a scientific and comprehensive mechanical model is creatively proposed. The mechanical model is divided into two systems at the main key strata (MKS): the lower strata of the MKS are regarded as a rectangular plane mechanical model on the Winkler foundation, comprising spaced filling bodies and coal pillars, and the upper strata of the MKS are regarded as a space-layer mechanical model. First, the subsidence function of the MKS is proposed. Then, this function is transmitted to the space-layer mechanical model through the interface. Finally, the mechanical model is used to predict the subsidence of the strata and the surface. The feasibility of the model is verified by numerical simulation and similar material simulation, and the characteristics of strata movement are analyzed. Using the mechanical model, the influences of geological and mining conditions on strata movement are discussed. This provides theoretical guidance for the study of strata movement and mechanisms in backfill-strip mining. [ABSTRACT FROM AUTHOR]

Based on the engineering example of Linsheng coal mine, this paper uses TF1M3D computer simulation platform to systematically analyze the process of smoke flow spreading and air flow disorder disaster from the perspective of the whole mine network, and puts forward corresponding plans and measures. A small scale similar experiment was carried out to study the updraft flow fire in the mine. Through the analysis of the collected experimental data, the variation law of the air volume of the fire source in the main air path, side branch road and total air path with different air volume and the variation characteristics of the temperature at the monitoring point with time were obtained under different air volume conditions, and the critical air volume was fitted as 1.65 m3·s− 1. The CAD digital stereoscopic model of Linsheng mine was established, and the TF1M3D simulation platform was used to simulate the mine fire under normal ventilation condition. The preset fire source point of the conveyor belt roadway in the first west district of Linsheng coal mine was used to observe the change of air volume during the fire process.The smoke flow reversal phenomenon would occur when the fire occurred in the first west district. The reversed smoke flow will flow to the 503 face and cause contamination. In order to inhibit the reversal of smoke flow, the emergency plan is proposed to increase the number of fan rotation and set fire doors in appropriate places, which can effectively inhibit the diffusion of smoke and improve mine disaster resistance. [ABSTRACT FROM AUTHOR]

ABSTRACT To study the stress distribution law under different mining times and spaces of the protected coal pillar in the isolated working face, this paper takes a coal mine in Shanxi as the engineering background and adopts numerical simulation and theoretical analysis to obtain the stress distribution law of protecting coal pillar in the isolated working face during the tunneling period and the mining period of the working face, and proves the reasonable size of protecting coal pillar. The results show that the vertical stress and maximum principal stress increase correspondingly with the decrease of the protective coal pillar size under both stages, and the minimum value of the minimum principal stress occurs on the 8 m protective coal pillar; The values of the principal stress ratio and the principal stress deflection angle do not differ greatly in the protection of the coal pillar, and the fluctuation of the values is mainly concentrated in the vicinity of the back‐mining roadway; The second invariant of bias stress (J2) is mainly concentrated in the protective coal pillar near the side of the extraction zone, when the size of the protective coal pillar is reduced to 10 m, the J2 on the side of the extraction zone and the J2 on the side of the roadway are connected, and the whole protective coal pillar is under the influence of J2, which is basically the same as the damage pattern of the plastic zone; Based on the formula of limit balance theory to calculate the elastic core width of different sizes of protective coal pillars, and combined with the results of numerical simulation analysis, it finally concluded that the reasonable size of the protective coal pillar of this isolated island working face is 15 m. [ABSTRACT FROM AUTHOR]

Rock masses are formed through long-term, complex geological processes, and the presence of joints significantly reduces their strength and increases their deformation. Rock bolts effectively enhance the strength and stability of rock masses and are extensively utilized for reinforcement. According to field investigations, a significant portion of the damage to bolted rock masses stems from shear deformation at joint surfaces. Moreover, roughness affects friction and surface contact, thus influencing the shear behavior between rock and rock bolts. This study considers two crucial factors affecting the shear characteristics of bolted rock joints: joint surface roughness and normal stress. Using the Particle Flow Code discrete element numerical method, the Barton standard joint profile lines were input to establish numerical models of both unbolted and bolted rock joints for direct shear tests. Results reveal that the peak shear stress and stiffness of both unbolted and bolted rock joints increase with rising normal stress and joint roughness coefficient. The peak shear stress and stiffness of bolted rock joints are notably higher than those of unbolted ones, with a maximum increase of 17.5%. Crack development in bolted rock joints occurs in stages of rapid, slow, and stable development, whereas no distinct slow development stage is observed in unbolted rock joints. Additionally, micro cracks in both unbolted and bolted rock joints are primarily tensile cracks, originating around the joint surface and extending outward with increasing shear displacement. These findings offer valuable insights into the microscopic shear mechanics of bolted rock joints and provide practical references for engineering design and applications in rock reinforcement projects. [ABSTRACT FROM AUTHOR]

Unlicensed taxis seriously disrupt the transportation market order, and threaten passenger safety. Therefore, this paper proposes a method for identifying unlicensed taxis based on travel characteristics. First, the vehicle mileage and operation time are calculated using traffic surveillance bayonet data, and variance analysis is applied to identification indicators for unlicensed taxis. Secondly, the mathematical model for identifying unlicensed taxis is established. The model is validated using the Hosmer–Lemeshow test, confusion matrix and ROC curve analysis. Finally, by applying methods such as geographic information matching, the spatiotemporal distribution characteristics of suspected unlicensed taxis in a city in Anhui Province are identified. The results show that the model effectively identifies suspected unlicensed taxis (ACC = 99.10%). The daily average mileage, daily average operating time, and number of operating days for suspected unlicensed taxis are significantly higher than those for private cars. Additionally, the suspected unlicensed taxis exhibit regular patterns in their travel origin–destination points and temporal distribution, enabling traffic management authorities to implement targeted regulatory measures. [ABSTRACT FROM AUTHOR]

High-temperature heat damage is a common phenomenon in the field of mine mining, and as the mining depth increases, the degree of underground heat damage is also increasing, which seriously restricts the productivity of the mine and affects the physical and mental health of workers. Based on the mining situation of mineral resources, this paper summarized the formation mechanism and heat dissipation characteristics of different heat sources of mine high-temperature heat damage and analyzed the influence of heat damage on the mine production process and human physiological and biochemical indicators. Then, we summarized the existing cooling technologies, mainly divided into non-artificial and artificial cooling technology. The cooling mechanism and application status of cooling technology were introduced and analyzed and compared the characteristics and application scope of each cooling technology, which have specific guiding and reference significance for the selection of cooling technology for different degrees of heat damage mines. Finally, building upon the low-temperature rock formation pre-cooling technology, a novel concept for quantifying the mine inlet airflow volume was advanced, along with the formulation of a relationship model that correlates the geometry of the roadway with the temperature alteration of the airflow. This development laid a theoretical foundation for harnessing the ground temperature effect in shallow roadways to regulate the temperature of the mine's inlet airflow, thereby enhancing the working environment at the mine's working face. [ABSTRACT FROM AUTHOR]

In the process of deep coal seam mining, the problem of coal–gas compound disasters is increasingly prominent, with the safe and efficient extraction of gas serving as the key to disaster reduction. A deep coal seam gas extraction project is a complex coupled system involving multiple physical fields, such as stress fields, gas flow fields, and energy. Constructing a systematic theoretical framework of multiphysics field coupling is crucial for improving the safety and efficiency of gas extraction. This paper examines all existing multiphysics field coupling theories. It then suggests a theoretical modeling framework that is based on three important scientific issues: the coal deformation law, the gas flow law, and the coal porosity and permeability spatiotemporal distribution law. We further analyze the application and development of the model in typical coal seam gas extraction engineering on this basis. Finally, this paper points out the shortcomings of the current research and looks forward to the future research directions for the coupled coal and gas multiphysics field model, aiming to provide a theoretical basis and guidance for the model's construction and application in gas extraction engineering. [ABSTRACT FROM AUTHOR]

Norfloxacin (NOR) is frequently detected in various water bodies and has the potential to promote the proliferation of NOR-resistant bacteria/genes in the environment. Efficiently removing residual NOR and NOR-resistant bacteria from contaminated water is critical to mitigating their environmental risks. This study investigated the ability of two common clay minerals, kaolinite and montmorillonite, to remove NOR and NOR-resistant bacteria from five different water environments (ultrapure water, simulated and real freshwater, and simulated and real seawater) and explored the underlying removal mechanisms. The results showed that both clays adsorbed NOR according to a pseudo-first-order kinetic model. In simulated and actual freshwater and seawater, the adsorption of NOR by kaolinite was 0.199, 0.120, 0.094, and 0.010 mg g−1, while montmorillonite adsorbed NOR at significantly higher levels, with values of 2.880, 2.208, 0.433, and 0.067 mg g−1, respectively. The primary mechanisms of adsorption included electrostatic interactions, cation exchange, and cation bonding and bridging. In addition to NOR sorption, culture tests revealed that montmorillonite exhibited significant antibacterial activity against NOR-resistant bacteria, achieving an inhibition ratio of 83.84 ± 4.01% when the initial concentrations of bacteria and montmorillonite were 1.68 ± 1.00 × 105 CFU·mL−1 and 40 mg mL−1, respectively. Remarkably, montmorillonite maintained its high sorption capacity and antibacterial activity even after multiple reuse cycles. These findings highlight the promising application potential of montmorillonite, particularly in terms of its storage and long-distance distribution capabilities, making it an effective material for removing both NOR and NOR-resistant bacteria from the environment. However, it is important to note that under estuarine conditions, clay-bound NOR could be released if water quality changes. Therefore, we conclude that strategies to degrade and remove antibiotics adsorbed onto clay minerals should be developed to prevent the release of antibiotics when clay particles enter the ocean, thus avoiding further environmental contamination. [ABSTRACT FROM AUTHOR]

Due to the difficulty in predicting the occurrence of rockburst in deep mining areas,this paper proposes that the use of Peridynamics to analyze the mechanical characteristics of coal-rock composite structures under loading conditions from the perspective of energy, Determine the impact tendency of coal rock composite structures by combining rock elastic deformation energy index (WET) and rock impact energy index (WCF); Use Lammps software to simulate the loading of composite structural materials and compare and verify with experimental results, to more accurately determine the tendency of rockburst occurrence in different coal-rock composite structures.The results indicate that after the specimen reaches the yield stress, the sample exhibits an "X" shaped failure. The coal body has a significant impact on the overall model's fragmentation, and different combination states and ratios can affect the degree of damage in the coal-rock composite structure. which has important theoretical value for rock mechanics research. The research results can reduce the occurrence of rockburst accidents, the difficulty of mine support, and the cost of mining engineering, as well as improve mine safety levels. [ABSTRACT FROM AUTHOR]

Analyzing geological profiles is of great importance for various applications such as natural resource management, environmental assessment, and mining engineering projects. This study presents a novel geostatistical approach for subsurface geological profile interpolation using a fractional kriging method enhanced by random forest regression. Using bedrock elevation data from 49 boreholes in a study area in southeast China, we first use random forest regression to predict and optimize variogram parameters. We then use the fractional kriging method to interpolate the data and analyze the variability. We also compare the proposed model with traditional methods, including linear regression, K-nearest neighbors, ordinary kriging, and fractional kriging, using cross-validation metrics. The results indicate that the proposed model reduces prediction errors and enhances spatial prediction reliability compared to other models. The MSE of the proposed model is 25% lower than that of ordinary kriging and 10% lower than that of fractional kriging. In addition, the execution time of the proposed model is slightly higher than other models. The findings suggest that the proposed model effectively captures complex subsurface spatial relationships, offering a reliable and precise solution for performing spatial interpolation tasks. [ABSTRACT FROM AUTHOR]

The increasing use of lithium-containing materials highlights the urgent need for their recycling to preserve resources and protect the environment. Lithium-containing slags, produced during the pyrometallurgical process in lithium-ion battery recycling, represent an essential resource for lithium recovery efforts. While multiple methods for lithium recycling exist, it is crucial to emphasize environmentally sustainable approaches. This study employs dry forced triboelectrification (FTC) to recover valuable components from slag powder, commonly known as engineered artificial minerals (EnAMs). The FTC method is used to change the charge of the target material and achieve a neutral state while other materials remain charged. The downstream electrostatic separator enables the charged particles to be separated from the target material, which in this study is lithium aluminate. The results show that the method is effective, and lithium aluminate can be successfully enriched. [ABSTRACT FROM AUTHOR]

Ground-based Interferometric Synthetic Aperture Radar (GB-InSAR) is a valuable technique for monitoring deformation of landslides. GB-InSAR can construct high-resolution 2D images in a range-doppler plane. However, it is difficult for geo-engineers who are unfamiliar with radar monitoring geometry to interpret the results. Geometric mapping method has been applied to the co-registration of terrain models and radar images for the deformation zonation, but the mismatching correction with GB-InSAR and terrain model is not fully investigated by existing researches. To address this issue, this paper proposes a method exploiting an optimum linear transformation based on ground control points (GCPs). The proposed method was evaluated on simulated data and a field campaign in an open pit mine. The deformation mapping result of the method was verified by a collapse event. The method proposed in this paper has an RMSE value ranging from 0.502 to 0.720 m (@700 m average monitoring range) when the average density of the terrain point cloud is 0.5 m. Although this method cannot accurately evaluate the antenna footprint vector deflection parameters, it can meet the needs of coarse matching calibration in relatively flat slope sub-target areas of open-pit mines for engineering applications. [ABSTRACT FROM AUTHOR]

The efficient production of γ-aminobutyric acid (GABA) at a neutral pH remains a challenge due to the pH sensitivity of glutamate decarboxylase (GAD) enzymes. Our study addressed this limitation by identifying and engineering GAD enzymes with high activity under neutral conditions. Through gene mining, we discovered a wild-type GAD from Enterococcus faecalis (EfGAD) with high activity at pH 7.0 and, using zero-shot (ZS) predictor-guided mutagenesis and C-terminal truncation, we developed an EfGAD variant with a significantly enhanced catalytic efficiency. This variant demonstrated a 1.3-fold increase in GABA production (~300 g/L) from monosodium glutamate (MSG) compared to the wild-type EfGAD in 5 L bioreactor experiments. The ability to operate at a neutral pH without the need for acidic conditions reduces production costs and facilitates scalability. Our findings underscore the potential of integrating machine learning tools for enzyme optimization and provide a sustainable approach to GABA biosynthesis using MSG as a substrate. [ABSTRACT FROM AUTHOR]

This experimental study investigates the impact of different silicon-to-alumina (Si/Al) ratios on geopolymers synthesized from metakaolin. Various ratios of Si/Al (1:1, 1.5:1, 2:1, 3:1, 4:1, and 5:1) were employed, nano-silica was the source material to alter the Si ratio. Microstructure and strength were analysed using SEM, XRD, NMR, and compressive strength testing Geopolymerization, a sustainable material synthesis process, was investigated using FTIR spectroscopy and computational modeling. The dissolution rates of aluminum and silicon molecules, as well as the formation of N-A-S-H gel, were studied. Results revealed that a Si/Al ratio of 2:1 significantly enhanced the dissolution of silicon and aluminum, leading to the formation of Si-O-T bonds and superior compressive strength. Computational analysis confirmed that the mechanical performance was primarily attributed to the formation of N-A-S-H gel, rather than zeolitic nuclei or silicate derivatives. These findings provide valuable insights for the application of geopolymerization in valorizing mine tailings, which often exhibit high Si/Al ratios. [ABSTRACT FROM AUTHOR]

In recent years, technological advances and widespread monitoring equipment have led to significant time-series data in the mining industry, especially for hydraulic support pressure. This data is vital for miner safety and predicting pressure cycles. However, the harsh conditions of coal mines often degrade data quality, making anomaly detection essential. This study introduces an anomaly detection model based on Dynamic Time Warping (DTW) and convolutional autoencoders to identify anomalies in hydraulic support data. The model's encoder consists of three convolutional layers and two pooling layers, while the decoder comprises five transposed convolutional layers, compressing sequence length to one-fourth of the original. By setting a 5-min sampling interval, with each sample containing 288 time steps and using a sliding window with a stride of 72, an optimal dataset is generated. Training results indicate that the model successfully detects anomaly points and subsequences, accurately learning and simulating normal operational patterns of hydraulic supports, achieving early anomaly detection. The model performs stably on both training and validation sets, with the reconstruction error (MSE) reduced to 0.001. For anomaly detection in the test set, we used the sum of the mean and standard deviation of the reconstruction error from the validation set as the detection threshold (0.0041). The results show that the mode of the number of anomaly points in the test samples is 8, with an average of approximately 10. Furthermore, this study analyzes the model's limitations under specific conditions and proposes improvements to enhance accuracy and robustness. Highlights: This is the first study to perform anomaly detection on hydraulic support data in the mining sector. A novel anomaly detection model based on DTW and convolutional autoencoders is proposed. The model effectively learned the regular patterns of hydraulic support operation, and the anomaly detection performed consistently well on both the training and validation sets. The DTW method was used to evaluate different methods for generating datasets, and the most beneficial dataset for the results was selected. [ABSTRACT FROM AUTHOR]

Slags generated from pyrometallurgical processing of spent Li-ion batteries are reservoirs of Li compounds that, on recycling, can reintegrate Li into the material stream. In this context, γ-LiAlO2 is a promising candidate that potentially increases recycling efficiency due to its high Li content and favorable morphology for separation. However, its solidification kinetics depends on melt compositions and cooling strategies. The Engineered Artificial Minerals approach aims to optimize process conditions that maximize the desired solid phases. To realize this goal, understanding the coupled influence of external cooling kinetics and internal kinetics of solid/liquid interface migration and mass and thermal diffusion on solidification is critical. In this work, the solidification of γ-LiAlO2 from a Li2O-Al2O3 melt is computationally investigated by applying a non-equilibrium thermodynamic model to understand the influence of varying processing conditions on crystallization kinetics. A strategy is illustrated that allows the effective utilization of thermodynamic information obtained by the CALPHAD approach and molecular dynamics-generated diffusion coefficients to simulate kinetic-dependent solidification. Model calculations revealed that melts with compositions close to γ-LiAlO2 remain comparatively unaffected by the external heat extraction strategies due to rapid internal kinetic processes. Kinetic limitations, especially diffusion, become significant for high cooling rates as the melt composition deviates from the stoichiometric compound. [ABSTRACT FROM AUTHOR]

Water inrush is a common disaster in submarine mining. The key to preventing this disaster is to restrict the water‐conducting fissure propagation induced by mining from forming a flow channel to communicate with the overlying aquifer. The mechanical behavior of hydraulic fractures under stress disturbance lies at the heart of the problem. Hence, the multiple parallel bond—grain‐based model (multi Pb‐GBM) is introduced to explore the hydraulic fracture evolution law of crystalline granite under the influence of stress disturbance. The results show that: hydraulic fracturing under stress disturbance is clearly affected by the stress wave frequency; the higher the frequency is, the more difficult it is to crack, but the crack propagation speed is faster after crack initiation; the propagation direction of a crack is deflected towards the propagation direction of the stress wave and the crack dip angle is controlled by the maximum principal stress; the internal crystal boundary of the same mineral is the most stable one among the three contacts, the contact boundary between different minerals being the most fragile one. This research not only has a practical application value to seabed mining engineering, but also has important theoretical significance in enriching deep rock mechanics theory. [ABSTRACT FROM AUTHOR]

This study built truck productivity prediction models incorporating real-site weather conditions at varying temporal resolutions. The best models were combined with SHapley Additive exPlanations to offer quantitative and qualitative analysis for input variables' effect on the model outputs. The results showed that mining engineers can make more accurate predictions of truck productivity at the weekly resolution compared with other resolutions. The three most influential input parameters were haul distance, empty speed, and ambient temperature. Extreme weather, such as strong wind speed, heavy precipitation, and extreme relative humidity, had a certain effect on truck-shovel allocation. Meanwhile, a unified graphical user interface was developed to predict mine truck productivity. [ABSTRACT FROM AUTHOR]

Low-alloy CrNiMo cast steels are often used in the caterpillar boards of excavators in mining engineering machinery due to their good mechanical properties and low cost. Three CrNiMo cast steels with different carbon contents (0.20%, 0.29%, and 0.35% by weight) were developed in this work. The mechanical properties of ingots of these cast steels can be optimized by heat-treated quenching and tempering (QT) and surface induction hardening (QTIH). The wear behavior of QT and QTIH specimens was evaluated under dynamic load and ring block conditions. The results show that the QT specimens exhibit a good mechanical performance and wear resistance. Compared to the QT specimens, the wear resistance can be further improved by QTIH treatment. The wear weight loss of QTIH specimens decreased by 42.7% and 73.2% under dynamic load and ring block wear tests, respectively. Additionally, the strength increased while plasticity and toughness decreased with increasing carbon content. Notably, when the carbon content is 0.29%, the CrNiMo cast steel exhibits an excellent combination of strength, ductility, and wear resistance. [ABSTRACT FROM AUTHOR]

Currently used machine diagnostic systems are based on very modern solutions based on the acquisition and recording of their operating parameters in real time. Increasingly available and high-tech sensor systems mean that the number of recorded parameters is increasing and their quality is improving. These data are mainly used to assess the technical condition of machines and the processes they perform. In mining, these data can also be used to assess and, at a later stage, improve the safety of the underground mining process. Referring to this issue, the paper presents examples of the use of diagnostic systems for powered roof supports and longwall shearers to assess the safety status of the underground hard coal mining process. In the case of the wall support, the focus was on measuring the pressures in the stands of its individual sections. Temporary changes in the values of these pressures constitute a valuable source of information regarding the interaction of the support with the rock mass. In particular, this concerns the identification of the effects of the informational impact of the rock mass on the longwall excavation protected by the support. The research results presented in the paper, especially in the case of very dangerous dynamic impacts, indicate the possibility of both diagnosing the operating condition of the section and identifying symptoms of exposure to such events. This undoubtedly significantly expands the possibilities of using the measured pressures. Diagnostic signals from a longwall shearer are also widely used. The current intensities drawn by its motors while cutting the rock mass, as well as the advance speed and its position in the wall make it possible to analyze these parameters and their changes before, during and after the occurrence of various types of events. These data enable the assessment of the effects of the rock mass on its operational efficiency and safety status. It also enables the identification of symptoms that precede the occurrence of such events. The presented examples indicate the need for a broader and more holistic approach to the use of diagnostic parameters of mining machines. In particular, this concerns the study of the cooperation between the support and the rock mass and its influence on the efficiency and safety of the rock mass mining process. The subject matter addressed relates to very important and current issues, and the developed methodology and obtained results should be applied in practice as soon as possible. [ABSTRACT FROM AUTHOR]

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Abstract In coal mining operations, the stable operation of hydraulic supports is crucial for ensuring mine safety. However, the nonlinear, non-stationary characteristics and noise interference in hydraulic support pressure data pose significant challenges for anomaly detection and fault diagnosis. This study proposes an anomaly detection and failure identification method based on Gated Recurrent Unit Autoencoder (GRU-AE), aimed at achieving anomaly detection in hydraulic support pressure data and equipment failure early warning. Through in-depth analysis of data from two coal mines in China, we systematically evaluated the model’s key parameters. The study revealed that window size had a limited impact on model performance, with a window length of 144 demonstrating optimal comprehensive performance in both anomaly detection and failure mode identification. The study also investigated the effectiveness of teacher forcing techniques. Although this technique can accelerate model convergence, it may lead to training instability and reduced generalization capability, requiring careful consideration in practical applications. Our proposed Recurrent Reconstruction Network model demonstrated excellent performance in complex coal mine hydraulic support data, effectively identifying anomalous regions and potential equipment failure characteristics while revealing potential deviations between model predictions and actual data, demonstrating its superior learning capability for periodic data patterns and equipment failure characteristics. Experimental results validated the effectiveness of the GRU-AE model in hydraulic support pressure anomaly detection and equipment fault diagnosis, providing an innovative technical solution for coal mine safety monitoring.

Abstract The drilling rate index (DRI) of rocks is important for optimizing drilling operations, as it informs the choice of appropriate methods and equipment, ultimately improving the efficiency of rock excavation projects. This study presents a hybrid machine learning approach to predict the DRI of rocks accurately. By integrating grey wolf optimization with support vector machine (GWO-SVM), random forest (GWO-RF), and extreme gradient boosting (GWO-XGBoost) models, the aim was to enhance predictive accuracy. Among these, the GWO-XGBoost model exhibited superior predictive performance, achieving a coefficient of determination (R²) of 0.999, mean absolute error (MAE) of 0.00043, root mean square error (RMSE) of 1.98017, and severity index (SI) of 0.0350 during training. Testing results confirmed its accuracy with R² of 0.999, MAE of 0.00038, RMSE of 1.80790, and SI of 0.0312. Furthermore, the GWO-XGBoost model outperformed the other models in terms of precision, recall, f1-score, and multi-class confusion matrix results for each DRI class. The GWO-RF model also demonstrated high accuracy, ranking second, while the GWO-SVM model showed comparatively lower performance. This research aims to advance rock excavation practices by providing a highly accurate and reliable tool for DRI prediction. The results highlight the significant potential of the GWO-XGBoost model in improving DRI predictions, offering valuable intuitions and practical applications in the field.

Comminution processes play a pivotal role in diverse applications, ranging from food processing, to mining and materials engineering. The pharmaceutical industry is no exception, with an increased focus on particle engineering to overcome the growing challenges related to the complexity of new drug molecules such as poor water solubility or stability issues. Additionally, the preparation of powders for pulmonary, transdermal, topical, ophthalmic, oral or parenteral administration often requires specific particle size requirements. Thus, milling technologies offer an excellent option for controlling particle size, improving the stability, dissolution, absorption rate, and bioavailability of poorly water-soluble drugs. They also contribute to enhancing pharmaceutical forms and overall product performance. This review highlights the different types of technologies used for comminution, the respective advantages and drawbacks, as well as connected topics including feed material properties, analytical techniques, process analytical technology, process safety, new top-down technologies and key information to consider when selecting a technology. Thus, an in-depth approach of comminution in the pharmaceutical industry is presented. This compilation serves as a source of comprehensive information for those who decide to initiate research projects in this field, or to update their existing literature knowledge and understanding. [ABSTRACT FROM AUTHOR]

In rock and mining engineering, it is essential to predict rock cuttability and drillability for estimating drilling costs, selecting suitable drilling/cutting machine and tools, and achieving high productivity. To predict the drillability and cuttability, many destructive methods have been developed. However, they are often expensive and time-consuming. To explore a non-destructive method, this paper builds a series of empirical relationships between rock characteristic impedance and its drillability and cuttability indices by using a large quantity of measured data from various laboratory and field tests in previous publications. The relationships between rock’s UCS (uniaxial compressive strength) and its drillability and cuttability indices are also built for comparison. The results indicate that: (1) the penetration rates of both percussive drilling and rotary drilling depend on rock characteristic impedance, and they decrease with increasing impedance. (2) The specific energies in percussive drilling, rotary drilling and cutting all increase with increasing rock impedance. (3) Most of current drillability indices such as alfa, DRI, CLI and Shore hardness have a certain relationship with rock impedance. (4) Characteristic impedance has a more confident relation with drillability and cuttability than the UCS. Since determination of rock impedance does not necessarily require a destructive method, characteristic impedance has a great potential to be taken as an index to predict rock drillability and cuttability. [ABSTRACT FROM AUTHOR]

Rockburst is a common dynamic geological disaster in underground mining and tunneling engineering, characterized by randomness, abruptness, and impact. Short-term evaluation of rockburst potential plays an outsize role in ensuring the safety of workers, equipment, and projects. As is well known, microseismic monitoring serves as a reliable short-term early-warning technique for rockburst. However, the large amount of microseismic data brings many challenges to traditional manual analysis, such as the timeliness of data processing and the accuracy of rockburst prediction. To this end, this study integrates artificial intelligence with microseismic monitoring. On the basis of a comprehensive consideration of class imbalance and multicollinearity, an innovative modeling framework that combines local outlier factor-guided synthetic minority oversampling and an extremely randomized forest with C5.0 decision trees is proposed for the short-term evaluation of rockburst potential. To determine the optimal hyperparameters, the whale optimization algorithm is embedded. To prove the efficacy of the model, a total of 93 rockburst cases are collected from various engineering projects. The results show that the proposed approach achieves an accuracy of 90.91% and a macro F1-score of 0.9141. Additionally, the local F1-scores on low-intensity and high-intensity rockburst are 0.9600 and 0.9474, respectively. Finally, the advantages of the proposed approach are further validated through an extended comparative analysis. The insights derived from this research provide a reference for microseismic data-based short-term rockburst prediction when faced with class imbalance and multicollinearity. [ABSTRACT FROM AUTHOR]

Anchor rock bolts are among the essential support components employed in coal mine support engineering. Measuring the axial load of the supporting anchor bolts constitutes an important foundation for evaluating the support effect and the mechanical state of the surrounding rock. The existing methods for measuring the axial load of rock bolts have difficulty meeting the actual demands in terms of accuracy and means. Therefore, we propose a novel inverse method for determining the axial load of rock bolts. On the basis of the dynamic relationship between the axial load of the anchor bolt and the strain of the plate, a calculation model for the inverse analysis of the axial load from the plate strain is presented, and it is verified and corrected through finite element analysis and indoor physical experiments. By combining the calculation model with the digital image correlation method, a low costinversion of the axial load of the anchor bolt in actual support engineering is achieved. The experimental results demonstrate that the average errors of the load inversion of anchor bolts in three different states via the theory and method proposed in this paper are less than 8.8% (4 kN), 3.6% (3.2 kN), and 14.7% (5.5 kN), respectively, and the average error of the axial load of the rock bolts in the proposed method is only 4.23 kN. It possesses relatively high accuracy and can be effectively applied in the actual production processes of mines. [ABSTRACT FROM AUTHOR]

Rockburst, one of the leading types of disaster in mining and rock engineering causing serious injuries and the loss of property, frequently occurs, involving various features and complex evolutionary mechanisms. Compared to rockbursts occurring at mining faces, those occurring in main roadways cause more serious problems for mine production. This paper first analyzes the characteristics of rockbursts in main roadways using two case studies involving the Gaojiapu and Cuimu coal mines. The causes of rockbursts in main roadways were studied using microseismic monitoring, energy density cloud maps, and seismic velocity tomography. During the mining of the 22306 working face in the Cuimu coal mine, targeted measures, such as deep-hole blasting of the roof strata and deep-hole blasting of the coal seam, were implemented to prevent rockbursts in the main roadways. The effectiveness of these measures was verified through long-term analysis of tremor activities. The study found that the influence of mining at two working faces on both sides of main roadways was significantly greater than that from a single-sided working face. The intensity of the tremor activities occurring near the main roadways was correlated with the distance from the working face to the main roadways. The closer the working face was to the main roadways, the stronger the tremor activities were near the main roadways. According to the distribution range of the tremors, the influence area of working face mining exceeded 800 m, with tremors distributed linearly along the main roadways. Even five months after the completion of working face mining, there were still a large number of tremors near the main roadways, which gradually disappeared after another five months. Mining activities were the main reason for the occurrence of main roadway rockbursts and the stress concentration within the main roadways themselves was another reason for the occurrence of rockbursts. The influence of working face mining could be reduced by deep-hole blasting of roof strata and the stress concentration within main roadways themselves could be reduced by large-diameter drilling. Those joint preventive measures effectively prevented the occurrence of rockbursts in main roadways. This study is of important theoretical and practical significance for further studies of rockburst mechanisms and prevention in regard to main roadways in coal mines, and the findings are significant in terms of the enhancement of safety in coal mines. [ABSTRACT FROM AUTHOR]

Mechanical stability of pillars is crucial for the safety of underground engineering. Understanding the failure process of rock pillars upon uniaxial compression may help predict its failure. This study investigates the failure process of sandstone, coal and granite under uniaxial compression using acoustic emission (AE) monitoring. A developed AE method, i.e., microcrack cumulative summation curve method, was applied to identify whether tensile or shear microcracks dominated during rock deformation to failure. This method was validated through Brazilian and direct shear tests. Our results showed that a) sandstone samples experienced shear faulting failure with AE analysis indicating an initial dominance of tensile microcracks, followed by shear microcracks, likely due to grains movements and intra- and inter-granular microcrack development; b) granite samples exhibited tensile failure, with transgranular microcracks developing along the axial compression direction, intense wing microcracks, and a potential transition from tensile to shear microcracking dominating process as indicated by AE analysis; c) coal samples displayed mixed shear-tensile failure, possibly dominated by the orientation of calcite veins where microcracks initiated, developed and coalesced, as suggested by AE and microstructure analysis. Using the power-law singularity theory for failure warning, our analysis demonstrated that lateral strain and AE count can accurately predict failure times for sandstone (15 ~ 22% early) and granite (8 ~ 12% early) samples. However, this method is less effective for coal samples due to their discontinuous failure processes. Our research highlights that combining microcrack development with failure prediction analyses effectively reveals physical failure processes in typical rocks, offering practical application for mining engineering. Highlights: A verified AE microcrack cumulative summation curve method was applied to reveal the failure process of rock materials. Microcracking behavior for sandstone, coal and granite under uniaxial compression was analyzed to reveal likely mechanisms for failure modes. Lateral strain and AE count are effective parameters for early warning and failure time prediction of rocks via power-law singularity theory. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms of crack propagation and failure behavior in rocks is fundamental for geotechnical engineering and mining applications. This study employs a coupled damage model based on the Smoothed Particle Hydrodynamics (SPH) method that integrates the Drucker–Prager and Grady–Kipp models. This mixed failure model is then implemented to simulate the crack propagation morphology and failure modes in uniaxial compression tests of flawed rock samples, and validated against multiple experimental observations. The numerical results exhibit good agreement with experimental observations from the literature in terms of the initiation and propagation of tensile and shear fractures, as well as the final failure morphology. Additionally, this work incorporates contact algorithms to simulate the loading plates, thereby better representing the actual experimental conditions encountered in uniaxial compression tests. Furthermore, a comprehensive parametric study is conducted to investigate the influence of key factors, such as pre-flaw geometry, cohesion, friction at the loading plate interface, and discretization parameters, on the simulated fracture processes and mechanical response. The outcomes indicate the proposed coupled damage model within the SPH framework can accurately capture complex fracture patterns and failure mechanisms in uniaxial compression of flawed rocks. This work demonstrates the capability of the SPH-based mixed-mode failure model to provide insights into rock fracture and failure mechanisms. Highlights: A coupled damage model integrating the Drucker–Prager and Grady–Kipp criteria within a smoothed particle hydrodynamics (SPH) framework is applied to simulate both shear and tensile failure modes in rocks firstly. The model is validated against more experimental observations, demonstrating the model's ability to reproduce the crack propagation and characteristic stress–strain behavior. This work presents a comprehensive parametric study investigating the influence of key factors, such as pre-flaw geometry, cohesion, friction at the loading plate interface, and discretization parameters, on the simulated fracture processes and mechanical response. These systematic investigations provide valuable insights into the governing mechanisms and highlight the importance of proper model calibration for accurate predictions. This work incorporates contact algorithms to simulate the loading plates, thereby better representing the actual experimental conditions encountered in uniaxial compression tests. The tensile wing cracks subjected to uniaxial compression, oriented vertically towards the top boundary of the specimen, are successfully captured. [ABSTRACT FROM AUTHOR]

There have been significant advances in literature mining, allowing for the extraction of target information from the literature. However, biological literature often includes biological pathway images that are difficult to extract in an easily editable format. To address this challenge, this study aims to develop a machine learning framework called the "Extraction of Biological Pathway Information" (EBPI). The framework automates the search for relevant publications, extracts biological pathway information from images within the literature, including genes, enzymes, and metabolites, and generates the output in a tabular format. For this, this framework determines the direction of biochemical reactions, and detects and classifies texts within biological pathway images. Performance of EBPI was evaluated by comparing the extracted pathway information with manually curated pathway maps. EBPI will be useful for extracting biological pathway information from the literature in a high-throughput manner, and can be used for pathway studies, including metabolic engineering. • EBPI extracts biological pathway information from literature images. • EBPI uses machine learning to detect arrows and classify detected texts from images. • EBPI demonstrates reasonable performance compared to manually created pathway maps. • EBPI uncovers biochemical reactions not found in representative pathway databases. • EBPI aids in studying pathways within images from a large volume of literature. [ABSTRACT FROM AUTHOR]

Rockmass in deep mining is highly susceptible to large-scale collapses under high stress and blast-induced disturbances, leading to casualties and economic losses. To investigate the evolution characteristics of goaf instability and the types of seismic sources that induce instability, an experiment on goaf instability was designed under uniaxial compression conditions based on actual mining operations. The entire experimental process was monitored using digital image correlation analysis and acoustic emission monitoring. By calculating the digital speckle field on the surface of the rock specimen during the experiment, the evolution characteristics of the deformation and strain fields from the beginning of loading to complete failure were analyzed. The study explored the dynamic behavior of cracks from initiation to propagation and eventually inducing large-scale collapse. The results show that the instability process of the goaf begins with the formation of tensile cracks. As stress increases, shear cracks occur in the specimen, leading to macroscopic failure. Furthermore, based on the differences in overall microfracture types measured by RA-AF characteristic parameters during specimen failure, large amplitude acoustic emission events corresponding to the formation of dominant macroscopic cracks were selected, and the focal mechanisms of these events were inverted. The results indicate that shear failure sources are significantly more prevalent than tensile failure sources in acoustic emission events leading to goaf instability. These findings can provide useful guidance for the support design and the prevention and control of rockmass instability disasters. [ABSTRACT FROM AUTHOR]