Sustainable Mining in the Era of Artificial Intelligence

The mining sector historically drove the global economy but at the expense of severe environmental and health repercussions,posing sustainability challenges[1]-[3].Recent advancements on artificial intelligence(AI)are revolutionizing mining through robotic and data-driven innovations[4]-[7].While AI offers mining industry advantages,it is crucial to acknowledge the potential risks associated with its widespread use.Over-reliance on AI may lead to a loss of human control over mining operations in the future,resulting in unpredictable consequences.

The influence of inter-band rock on rib spalling in longwall panel with large mining height

In order to improve rib stability,failure criteria and instability mode of a thick coal seam with inter-band rock layer are analysed in this study.A three-dimensional mechanical model is established for the rib by considering the rock layer.A safety factor is defined foy the rib,and it is observed that the safety factor exhibits a positive correlation with the thickness and strength of the inter-band rock.A calculation method for determining critical parameters of the rock layer is presented to ensure the rib stability.It is revealed that incomplete propagation of the fracture at the hard rock constitutes a fundamental prerequisite for ensuring the rib stability.The influence of the position of the inter-band rock in the coal seam on failure mechanism of the rib was thoroughly investigated by developing a series of physical models for the rib at the face area.The best position for the inter-band rock in the coal seam is at a height of 1.5 m away from the roof line,which tends to provide a good stability state for the rib.For different inter-band rock positions,two ways of controlling rib by increasing supports stiffness and flexible grouting reinforcement are proposed.

Using X Social Networks (formerly Twitter) and web news mining to predict the measles outbreak

Measles,an infectious disease caused by the measles virus,remains a significant public health concern worldwide due to its highly contagious nature and potential for severe complications[1].In addition to symptoms such as high fever,cough,Koplik spots,and rash,measles can lead to serious complications including pneumonia and myocarditis,particularly in vulnerable populations such as young children[1,2].

Game theory attack pricing for mining pools in blockchain-based IoT

The malicious mining pool can sacrifice part of its revenue to employ the computing power of blockchain network.The employed computing power carries out the pool mining attacks on the attacked mining pool.To realize the win-win game between the malicious mining pool and the employee,the paper proposes an Employment Attack Pricing Algorithm(EAPA)of mining pools in blockchain based on game theory.In the EAPA,the paper uses mathematical formulas to express the revenue of malicious mining pools under the employment attack,the revenue increment of malicious mining pools,and the revenue of the employee.It establishes a game model between the malicious mining pool and the employee under the employment attack.Then,the paper proposes an optimal computing power price selection strategy of employment attack based on model derivation.In the strategy,the malicious mining pool analyzes the conditions for the employment attack,and uses the derivative method to find the optimal utilization value of computing power,employees analyze the conditions for accepting employment,and use the derivative method to find the optimal reward value of computing power.Finally,the strategy finds the optimal employment computing power price to realize Nash equilibrium between the malicious mining pool and the employee under the current computing power allocation.The simulation results show that the EAPA could find the employment computing power price that realizes the win-win game between the malicious mining pool and the employee.The EAPA also maximizes the unit computing power revenue of employment and the unit computing power revenue of honest mining in malicious mining pool at the same time.The EAPA outperforms the state-of-the-art methods such as SPSUCP,DPSACP,and FPSUCP.

Spatial distribution and potential ecological and health risks associated with heavy metals in the Ijero-Ekiti mining site,Nigeria

Artisanal gold mining,a labor-intensive and antiquated technique,is a growing industry and the source of income for rural communities all over the world.However,artisanal gold mining has potential negative and long-term effects on economy,environment,and society.This study collected soil samples from 16 sample points including a control point to examine the pollution degrees and spatial distribution of heavy metals,as well as ecological and health risks associated with heavy metal pollution in the Ijero-Ekiti mining site,Nigeria.Geographical Information System(GIS)and remote sensing technologies were used to identify regions with high concentrations of heavy metals and assess the environmental impact of gold mining activities.The results show that the mean heavy metal concentrations of 16 soil pointa are 8.94(±5.97)mg/kg for As,0.18(±0.54)mg/kg for Cd,0.11(±1.06)mg/kg for Co,14.32(±3.43)mg/kg for Cr,6.89(±0.64)mg/kg for Cu,48.92(±11.77)mg/kg for Fe,135.81(±30.75)mg/kg for Mn,5.92(±0.96)mg/kg for Ni,5.72(±1.66)mg/kg for Pb,and 13.94(±1.38)mg/kg for Zn.The study reveals that heavy metal concentration in soils follows the order of Mn>Fe>Cr>Zn>As>Cu>Ni>Pb>Co>Cd.An analysis of soil samples indicates that 3 principal components(PCs)account for 70.008%of the total variance and there are strong positive correlations between various pairs of heavy metals.The total potential ecological risk index(309.599)in the study area is high.Non-carcinogenic risk suggests that there may be long-term health impacts on people who work in the mining areas due to chronic exposure to the environment.Based on the study,the hazard index of carcinogenic health risks associated with heavy metals through ingestion is 520.00×10^(–4).Dermal contact from As and Cr also increases the risk of cancer,with the highest hazard index value of 18.40×10^(–4).The lowest exposure pathway,with the hazard index value of 0.68×10^(–4),indicates that the inhalation of heavy metals has a comparatively low risk of cancer.This study recommends the formulation of policies to monitor the Ijero-Ekiti mining site and other regions in Nigeria where indiscriminate artisanal gold mining activities exist.

Mobility of Major and Trace Elements during the Bauxitization Processes in Ngaoundal Area (Adamawa Cameroon): Implication on Mining Perspectives

This study was focused to assess major and trace elements in bauxitic duricrusts from Ngaoundal and its surroundings in order to establish their mining interest. To this end, fieldworks, mineralogical and geochemical analyses were carried out. Four facies of duricrust were identified and characterized from the summit to the top of the slope of the Ngaoundal mountain: scoriaceous, pisolitic, nodular and massive. Mineralogical and geochemical analyses performed on 16 samples, revealed a significant concentration of Al2O3 mainly in the scoriaceous facies (over 45% in grade), moderate in Fe2O3 (averaging 23.69%) and SiO2 (averaging 21.7%). Trace elements were generally low, excluding Cr (421 ppm on average), Zr (327 ppm on average and V (213 ppm on average). In addition, the limited quantities of alkalis (Na2O, K2O) and alkaline earths metals (MgO, CaO) coupled with the very high values of Chemical Index of Alteration (CIA) and Mineralogical Index of Alteration (MIA), (more than 99%) attest to the intense weathering of the studied materials. Allitization and monosiallitization constituted the crystallochemical phenomena that have led to the development of bauxitic minerals. More than 90% of gibbsite in scoriaceous facies, 52.21% - 76.01% of kaolinite in pisolitic facies and more than 40% of hematite in nodular facies were quantified. The relationships between the constitutive components indicated their interdependency during the bauxitization phenomenon. The mineralogical and geochemical properties highlighted the mining interest of the studied duricrusts to be valorized.

A semi-infinite beam theoretical model on predicting rock slope subsidence induced by underground mining

When the mining goaf is close to the cliff,rock slope subsidence induced by underground mining is significantly affected by its boundary conditions.In this study,an analytical method is proposed by considering the key strata as a semi-infinite Euler-Bernoulli beam rested on a Winkler foundation with a local subsidence area.The analytical solutions of deflection are derived by analyzing the boundary and continuity conditions of the cliff.Then,the analytical solutions are verified by the results from experimental tests,FEM and InSAR,respectively.After that,the influence of changing parameters on deflections is studied with sensitivity analysis.The results show that the distance between goaf and cliff significantly affects the deflection of semi-infinite beam.The response of semi-infinite beam is obviously determined by the length of goaf and the bending stiffness of beam.The comparisons between semi-infinite beam and infinite beam illustrate the ascendancy of the improved model in such problems.

Study on the Safety and Prevention Technology of Coal Mining under the River in Xingyuan Coal Mine

Coal mining-induced surface subsidence poses significant ecological and infrastructural challenges, necessitating a comprehensive study to ensure safe mining practices, particularly in underwater conditions. This project aims to address the extensive impact of coal mining on the environment, infrastructure, and overall safety, focusing on the Shigong River area above the working face. The study employs qualitative and quantitative analyses, along with on-site engineering measurements, to gather data on crucial parameters such as coal seam characteristics, roof rock lithology, thickness, water resistance, and structural damage degree. The research encompasses a multidisciplinary approach, involving mining, geology, hydrogeology, geophysical exploration, rock mechanics, mine surveying, and computational mathematics. The importance of effective safety measures and prevention techniques is emphasized, laying the foundation for research focused on the Xingyun coal mine. The brief concludes by highlighting the potential economic and social benefits of this project and its contribution to valuable experience for future subsea coal mining.

Land Use and Land Cover Dynamics in the Eseka Alluvial Gold Mining District, Centre Region, Cameroon

Local populations in Cameroon thrive on forest resources and the flow of ecosystem services they provide are pivotal in sustaining national economy, improving people’s lives, safeguarding biodiversity, and mitigating the impacts of environmental changes. The exploitation of these resources invariably leads to deforestation and forest degradation. This study was designed to evaluate land use land cover change (LULCC) in the Eseka alluvial gold mining district with the aid of Landsat images. In the investigation of forest cover change, four Landsat satellite images for (1990, 2002, 2015 and 2022) were used. Ground-truthing also helped to identify the activities carried out by the local population and to determine agents, drivers and pressures of land use and land cover change. Four main land cover classes namely: forest, agricultural land, settlement/mining camps and water bodies were selected. Between 1990 and 2022, the proportion of forest decreased from 98% to 34% while those of agricultural land and settlement/mining camps increased from 2% to 60% and 0.54% to 6% respectively. Analysis showed ongoing deforestation with forest cover loss of ~98,263 ha in 32 years giving a cover change percentage of 63.94%. Kappa coefficient for the study period ranged from 0.92 to 0.99. Forest cover loss could be attributed to farming activities, wood extraction and alluvial gold mining activities. Economic motives notably the need to increase household income from a frequent demand for farm and wood products in neighbouring towns and the quest for gold were the main drivers of these activities. Hence, this study assesses the impact of human activities from the mining sector on the forest ecosystem in a bid to inform mitigation policies.

Experimental investigation of the inhibition of deep-sea mining sediment plumes by polyaluminum chloride

Deep-sea sediment disturbance may occur when collecting polymetallic nodules,resulting in the creation of plumes that could have a negative impact on the ecological environment.This study aims to investigate the potential solution of using polyaluminum chloride(PAC)in the water jet.The effects of PAC are examined through a self-designed simulation system for deep-sea polymetallic nodule collection and sediment samples from a potential deep-sea mining area.The experimental results showed that the optimal PAC dose was found to be 0.75 g/L.Compared with the test conditions without the addition of PAC,the presence of PAC leads to a reduction in volume,lower characteristic turbidity,smaller diffusion velocity,and shorter settling time of the plume.This indicates that PAC inhibits the entire development process of the plume.The addition of PAC leads to the flocculation of mm-sized particles,resulting in the formation of cm-sized flocs.The flocculation of particles decreases the rate of erosion on the seabed by around 30%.This reduction in erosion helps to decrease the formation of plumes.Additionally,when the size of suspended particles increases,it reduces the scale at which they diffuse.Furthermore,the settling velocity of flocs(around 10^(-2) m/s)is much higher that of compared to sediment particles(around 10^(-5) m/s),which effectively reduces the amount of time the plume remains in suspension.

Multiparameter Numerical Investigation of Two Types of Moving Interactions Between the Deep-Sea Mining Vehicle Track Plate and Seabed Soil:Digging and Rotating Motions

To ensure the safe performance of deep-sea mining vehicles(DSMVs),it is necessary to study the mechanical characteristics of the interaction between the seabed soil and the track plate.The rotation and digging motions of the track plate are important links in the contact between the driving mechanism of the DSMV and seabed soil.In this study,a numerical simulation is conducted using the coupled Eulerian–Lagrangian(CEL)large deformation numerical method to investigate the interaction between the track plate of the DSMV and the seabed soil under two working conditions:rotating condition and digging condition.First,a soil numerical model is established based on the elastoplastic mechanical characterization using the basic physical and mechanical properties of the seabed soil obtained by in situ sampling.Subsequently,the soil disturbance mechanism and the dynamic mechanical response of the track plate under rotating and digging conditions are obtained through the analysis of the sensitivity of the motion parameters,the grouser structure,the layered soil features and the soil heterogeneity.The results indicate that the above parameters remarkably influence the interaction between the DSMV and the seabed soil.Therefore,it is important to consider the rotating and digging motion of the DSMV in practical engineering to develop a detailed optimization design of the track plate.

Vegetation characteristics and soil properties of artificially remediated grasslands:The case study of the Shimenhe mining area in Qilian Mountains,northwest China

The mining of limestone mines plays a crucial role in societal and economic advancement.However,mining activities have led to destructive variations in grassland ecology and soil,causing numerous environmental problems,and effective artificial restoration measures have been used to restore grasslands in the Shimenhe mining areas to different degrees.In this study,we investigated,examined and analyzed plant community structure and its correlation with soil properties across varying degrees of alpine grassland restoration in Qilian Mountains Shimenhe restoration mines using the sample method,and studied the changes in species diversity using five diversity indexes(Simpson index,Shannon index,Margalef index,Dominance index and Evenness index).This study showed that the plant community characteristics with high recovered degree(HRD)>middle recovered degree(MRD)>low recovered degree(LRD)>very low recovered degree(VLRD),11 plant genera comprising 11 species across 10 families were identified.Dominant families with robust ecological adaptability included Leguminosae,Rosaceae,Gramineae,Asteraceae,and Salicaceae.The highest Simpson,Shannon,Margalef and Evenness index of HRD grassland community species were 0.82,1.96,1.66 and 0.89,respectively.The highest Dominance index of VLRD grassland community species was 0.34,which required several restoration methods such as spraying and mulching.Soil pH and EC tended to decrease with increasing restoration,SOC,SMC,TP,AP,NH4-N,TN,AN and NO3-N tended to increase and the content of soil environmental factors contributed to vegetation growth across various restoration levels the mine grassland.In conclusion,our study indicated that the community structure gradually diversified and soil properties changed positively with the increase of restoration degrees in the Qilian Mountains Shimenhe mine,and the best results of HRD restoration were obtained.This study provides the theoretical basis for the restoration and conservation of grasslands in mining areas by demonstrating examined the correlation between plant characteristics and soil properties in restored grasslands in alpine mining areas.

Comparative Analysis of the Factors Influencing Metro Passenger Arrival Volumes in Wuhan, China, and Lagos, Nigeria: An Application of Association Rule Mining and Neural Network Models

This study explores the factors influencing metro passengers’ arrival volume in Wuhan, China, and Lagos, Nigeria, by examining weather, time of day, waiting time, travel behavior, arrival patterns, and metro satisfaction. It addresses a significant research gap in understanding metro passengers’ dynamics across cultural and geographical contexts. It employs questionnaires, field observations, and advanced data analysis techniques like association rule mining and neural network modeling. Key findings include a correlation between rainy weather, shorter waiting times, and higher arrival volumes. Neural network models showed high predictive accuracy, with waiting time, metro satisfaction, and weather being significant factors in Lagos Light Rail Blue Line Metro. In contrast, arrival patterns, weather, and time of day were more influential in Wuhan Metro Line 5. Results suggest that improving metro satisfaction and reducing waiting times could increase arrival volumes in Lagos Metro while adjusting schedules for weather and peak times could optimize flow in Wuhan Metro. These insights are valuable for transportation planning, passenger arrival volume management, and enhancing user experiences, potentially benefiting urban transportation sustainability and development goals.

Dynamic evaluation of digital and green development policies based on text mining of the PMC framework

Aiming to identify policy topics and their evolutionary logic that enhance the digital and green development(dual development)of traditional manufacturing enterprises,address weaknesses in current policies,and provide resources for refining dual development policies,a total of 15954 dual development-related policies issued by national and various departmental authorities in China from January 2000 to August 2023 were analyzed.Based on topic modeling techniques and the policy modeling consistency(PMC)framework,the evolution of policy topics was visualized,and a dynamic assessment of the policies was conducted.The results show that the digital and green development policy framework is progressively refined,and the governance philosophy shifts from a“regulatory government”paradigm to a“service-oriented government”.The support pattern evolves from“dispersed matching”to“integrated symbiosis”.However,there are still significant deficiencies in departmental cooperation,balanced measures,coordinated links,and multi-stakeholder participation.Future policy improvements should,therefore,focus on guiding multi-stakeholder participation,enhancing public demand orientation,and addressing the entire value chain.These steps aim to create an open and shared digital industry ecosystem to promote the coordinated dual development of traditional manufacturing enterprises.

Identified the hydrochemical and the sulfur cycle process in subsidence area of Pingyu mining area using multi-isotopes combined with hydrochemistry methods

Groundwater serves as an important water source for residents in and around mining areas.To achieve scientific planning and efficient utilization of water resources in mining areas,it is essential to figure out the chemical formation process and the ground water sulfur cycle that transpire after the coal mining activities.Based on studies of hydrochemistry and D,^(18)O-H_(2)O,^(34)S-SO_(4)isotopes,this study applied principal component analysis,ion ratio and other methods in its attempts to reveal the hydrogeochemical action and sulfur cycle in the subsidence area of Pingyu mining area.The study discovered that,in the studied area,precipitation provides the major supply of groundwater and the main water chemistry effects are dominated by oxidation dissolution of sulfide minerals as well as the dissolution of carbonate and silicate rocks.The sulfate in groundwater primarily originates from oxidation and dissolution of sulfide minerals in coal-bearing strata and human activities.The mixed sulfate formed by the oxidation of sulfide minerals and by human activities continuously recharges the groundwater,promoting the dissolution of carbonate rock and silicate rock in the process.

Forecasting the Academic Performance by Leveraging Educational Data Mining

The study aims to recognize how efficiently Educational DataMining(EDM)integrates into Artificial Intelligence(AI)to develop skills for predicting students’performance.The study used a survey questionnaire and collected data from 300 undergraduate students of Al Neelain University.The first step’s initial population placements were created using Particle Swarm Optimization(PSO).Then,using adaptive feature space search,Educational Grey Wolf Optimization(EGWO)was employed to choose the optimal attribute combination.The second stage uses the SVMclassifier to forecast classification accuracy.Different classifiers were utilized to evaluate the performance of students.According to the results,it was revealed that AI could forecast the final grades of students with an accuracy rate of 97%on the test dataset.Furthermore,the present study showed that successful students could be selected by the Decision Tree model with an efficiency rate of 87.50%and could be categorized as having equal information ratio gain after the semester.While the random forest provided an accuracy of 28%.These findings indicate the higher accuracy rate in the results when these models were implemented on the data set which provides significantly accurate results as compared to a linear regression model with accuracy(12%).The study concluded that the methodology used in this study can prove to be helpful for students and teachers in upgrading academic performance,reducing chances of failure,and taking appropriate steps at the right time to raise the standards of education.The study also motivates academics to assess and discover EDM at several other universities.

Tailings Dam Mining, Theoretical Considerations, and Circular Economy: A Review

Mining in tailings dams has emerged as a strategic alternative for mining companies for both economic and environmental reasons. Owing to technological limitations in recent decades, many of these dams have high metal contents, emphasizing the need to evaluate the quality of these residues, especially considering the technological advancements in current concentration plants. An economic viability analysis associated with reusing these materials is crucial. From an environmental point of view, improving mining techniques for dams by considering both safety and feasibility is an advantageous option in decommissioning processes and alignment in the circular economy. In this context, representing these tailings in terms of grade quality and granulometry, as well as the associated contaminants, is essential. Geostatistical estimation and simulation methods are valuable tools for modeling tailings bodies, but they require a reliable sampling campaign to ensure acceptably low errors. From an operational perspective, tailings recovery can be conducted via dry methods, such as mechanical excavation, or hydraulic methods, such as dredging or hydraulic blasting. Dredging is a commonly used method, and cutter suction dredgers, which require pumping to transport fragmented material, are the most commonly used tools. In this paper, some practical applications of geostatistical methods for resource quantification in tailings dams will be discussed. Additionally, the main mining methods for tailings recovery in dams will be presented. Emphasis will be given to the dredging method, along with the key analysis parameters for sizing dredgers, pumps, and pipelines.

The Ban on Illegal Mining in Ghana: Environmental and Socio-Economic Effect on Local Communities

The study was conducted to assess the effects of small-scale (artisanal) gold mining and its social and economic implications on the people in Amansie West District of Ghana. The artisanal gold mining communities were studied using secondary data from scholarly articles and journals, books, conference papers, research reports, policy documents, working papers, and briefs. Descriptive and systematic analyses were conducted. The result indicated that youth aged between 21 - 30 were most likely to engage in illegal mining operations in the selected study areas. The study revealed that farmland had been destroyed, making farming difficult for the inhabitants. It is evident from the review that dug-out pits from mining serve as breeding grounds for mosquitoes and death traps for humans. The study, therefore, accentuates the need for illegal small-scale gold mining to be formalised and strategic interventions and policies proposed for the protection of Ghana’s Natural resources. Furthermore, community members should be involved in policy-making and environmental protection issues to help control the menace of landscape destruction. Although the ban on illegal gold mining activity by the government has caused more people to lose their jobs leading to livelihood challenges in mining communities, it is a step in the right direction, as the ban seeks to halt and check the illegal small-scale mining sector. The study recommended alternative livelihood and income-generating projects such as beekeeping, mushroom culture, grasscutter rearing, and agroforestry technologies including the growth of economic fruit trees as alternative livelihood ventures.

Analysis of the Risk of Water Breakout in the Bottom Plate of High-Intensity Mining of Extra-Thick Coal Seams

In order to clarify the danger of water breakout in the bottom plate of extra-thick coal seam mining, 2202 working face of a mine in the west is taken as the research object, and it is proposed to use the on-site monitoring means combining borehole peeping and microseismic monitoring, combined with the theoretical analysis to analyze the danger of water breakout in the bottom plate. The results show that: 1) the theoretically calculated maximum damage depth of the bottom plate is 27.5 m, and its layer is located above the Austrian ash aquifer, which has the danger of water breakout;2) the drill hole peeping at the bottom plate of the working face shows that the depth of the bottom plate fissure development reaches 26 m, and the integrity of the water barrier layer has been damaged, so there is the risk of water breakout;3) for the microseismic monitoring of the anomalous area, the bottom plate of the return air downstream channel occurs in the field with a one-week lag, which shows that microseismic monitoring events may reflect the water breakout of the underground. This shows that the microseismic monitoring events can reflect the changes of the underground flow field, which can provide a reference basis for the early warning of water breakout. The research results can provide reference for the prediction of sudden water hazard.

Kinetics of Neutralization of Polymetallic Mining Discharges from the Perkoa Zinc Deposit in Central-Western Burkina Faso

Oxidized and acidic mining discharges(pH between 4 and 5)from the Perkoa zinc mine in Burkina Faso consisting of waste rock,crusher rejects and mining tailings were sampled and used for neutralization tests with calcareous dolomite(for six months).The mining discharges and the calcareous dolomite were previously characterized.Columns of 60 cm length and 15 cm diameter were used for the tests.Then,2.62 kg of calcareous dolomite was deposited on the mining discharges in each column.Two liters of deionized water are added every 15 days to each column.Samples were taken at the outlet of the columns at time intervals and then analyzed to assess the evolution of pH,electrical conductivity and contents of PHEs(Potentially Harmful Elements)over time.Following the neutralization tests on solid mining discharges,neutralization tests were also carried out on acid leachates resulting from the oxidation of these same solid mining discharges with calcareous dolomite.The results show that calcareous dolomite is very effective for the neutralization of SR(Sterile Discharges)and the precipitation of PHEs contained therein.It is also effective in buffering acidic effluents from these sterile discharges.As for other mining discharges(crusher rejects and mining residues),although calcareous dolomite is not effective in neutralizing these oxidized and acidic solid discharges,it is however effective in precipitating PHEs such as arsenic and lead.Calcareous dolomite is also effective in buffering acid leachates from these oxidized and acidic mining discharges(crusher rejects and mining tailings).