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Using a conceptual distinction between prospective and retrospective research, we analyze the international high-impact literature on tailings. This distinction differentiates between investigations concentrated on specific case studies, where the socio-environmental consequences of tailings are addressed or specific actions on them are documented, and the investigations that model interventions on tailings, propose new forms of design, management and remediation applicable to tailings. Using Natural Language Processing (NLP) tools, we covered all the publications registered in the Scopus database between 2010 and 2020 on mining tailings. Our research question ask for the temporal orientations in the international publication on mining tailings deposits between 2010 and 2020? Our results show an increase in the number of prospective investigations, which practically double the retrospective ones. However, at the level of citations, this difference is reduced and the most cited investigations in the retrospective perspective outnumber the most cited ones in the prospective perspective. We conclude by discussing the need to address the impact of prospective research on mining companies and overcoming resistance to innovation in the industry when there are no regulatory or legal obligations. In the same way, we call for an increase in the public contribution to maintain the independence of retrospective research, without neglecting the necessary construction of updated evidence on the socio-environmental consequences of mining tailings.
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In this work, we conducted a visualized bibliometric analysis to map the research trends of machine learning in engineering (MLE) based on articles indexed in the Web of Science Core Collection published between 2000 and 2019. The research distributions, knowledge bases, research hotspots, and research frontiers for MLE studies are revealed by using VOSviewer software and visualization technology. The growth of the literature related to MLE averaged 24.3% in the past two decades. A total of 3057 peer-reviewed papers from 96 countries published in 1299 different journals were identified. The USA was the most productive country, with 23.73% of the overall articles and 32.25% of the overall citations. The most active research organization was MIT, with 41 publications and 1079 citations, and the Journal of Machine Learning Research had the largest number of citations in the field of MLE. In particular, our findings indicate that the research issues of “random forests”, “support vector machine”, “extreme learning machine”, “deep learning”, “statistical learning theory”, and “Python machine learning” formed the knowledge bases of MLE from 2000 to 2019, while the research hotspots focused on applications of machine learning benchmark algorithms. Burst detection analysis results showed that more burst keywords emerged and had a higher frequency of change after 2010. This study provides an insight view of the overall research trends of MLE and may help researchers better understand this research field and predict its dynamic directions.
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Purpose This paper presents a review of the existing state-of-the-art literature on machine learning (ML) in logistics and supply chain management (LSCM) by analyzing the current literature, contemporary concepts, data and gaps and suggesting potential topics for future research. Design/methodology/approach A systematic/structured literature review in the subject discipline and a bibliometric analysis were organized. Information regarding industry involvement, geographic location, research design and methods, data analysis techniques, university, affiliation, publishers, authors, year of publications is documented. A wide collection of eight databases from 1994 to 2019 were explored using the keywords “Machine Learning” and “Logistics“, “Transportation” and “Supply Chain” in the title and/or abstract. A total of 110 articles were found, and information on a chain of variables was gathered. Findings Over the last few decades, the application of emerging technologies has attracted significant interest all around the world. Analysis of the collected data shows that only nine literature reviews have been published in this area. Further, key findings show that 53.8 per cent of publications were closely clustered on transportation and manufacturing industries and 54.7 per cent were centred on mathematical models and simulations . Neural network is applied in 22 papers as their exclusive algorithms. Finally, the main focuses of the current literature are on prediction and optimization , where detection is contributed by only seven articles. Research limitations/implications This review is limited to examining only academic sources available from Scopus, Elsevier, Web of Science, Emerald, JSTOR, SAGE, Springer, Taylor and Francis and Wiley which contain the words “Machine Learning” and “Logistics“, “Transportation” and “Supply Chain” in the title and/or abstract. Originality/value This paper provides a systematic insight into research trends in ML in both logistics and the supply chain.
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There are high technological and software demands associated with conducting Brain–Computer Interface (BCI) research. In order to accelerate the development and accessibility of BCIs, it is worthwhile to focus on open-source and community desired tooling. Python, a prominent computer language, has emerged as a language of choice for many research and engineering purposes. In this article, BciPy, an open-source, Python-based software for conducting BCI research is presented. It was developed with a focus on restoring communication using Event-Related Potential (ERP) spelling interfaces; however, it may be used for other non-spelling and non-ERP BCI paradigms. Major modules in this system include support for data acquisition, data queries, stimuli presentation, signal processing, signal viewing and modeling, language modeling, task building, and a simple Graphical User Interface (GUI).
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The lead–zinc areas of China have faced serious foulteousqulated heavy metal pollution. In this study, data on As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn concentrations in China’s lead–zinc mine tailings were collected and screened from published literature (2015–2020). The contamination assessments, geographical distributions, and health risk assessments of the eight heavy metals were analyzed. The results revealed that the mean concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn exceeded the corresponding background values for soils. Moreover, most of the lead–zinc mine tailing areas contaminated by heavy metals were located in the southern and eastern regions of China. The health risk assessment results indicated that oral ingestion was the main exposure route of heavy metals in the mine tailings, and children were more vulnerable to adverse effects. For a single metal, As and Pb presented high non-carcinogenic risks, and As and Cu presented the unacceptable carcinogenic risks. This study provides a timely analysis proving the urgent necessity of the treatment of heavy metal pollution in lead–zinc tailings in China.
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Motor imagery (MI) is particularly attractive in brain-computer interface (BCI) in the sense that it does not need any external stimuli. However, the overall performance is often severely affected by subject’s mental states. In this study, a method based on common feature analysis (CFA) was proposed for MI electroencephalogram (EEG) patterns recognition, which can not only improve the recognition accuracy but also help to find reliable and interpretable features associated with specific MI patterns. Evaluation using several open competition datasets justifies that the common features could more accurately identify MI characteristics and hence substantially benefit MI EEG patterns recognition.
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The present investigation aimed to understand dewatering amenability of the tailing slurry generated during the beneficiation of chromite ore. The tailing includes mainly ultrafine particles with a concentration of Cr⁺⁶ which causes environmental and storage issues. Several dewatering techniques were investigated, including settling by using two different thickeners (high rate thickening and paste thickening), pressure filtration, as well as classification by using hydrocyclone. This paper explains the results obtained in various stages of the dewatering process. Further, different dewatering circuits were examined for the effective dewatering of the tailing slurry, and the optimum solutions were discussed. It is also concluded that up to 97% of the water can be recovered and recycled from such tailing slurry by adopting an efficient dewatering circuit.
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Techniques for dry processing low-grade iron ores and tailings are being investigated. Dry desliming tests using a rotating wheel air classifier and factorial design were performed on a difficult-to-treat low-grade high-goethite Australian iron ore tailings. The results were compared with theoretically ideal size separation and a hydrocyclone desliming study using the same tailings. The air classifier performance was poorer than the hydrocyclone due to agglomerated particles in the feed, including fines coating coarser particles. The "fish hook" effect was observed and discussed. After dry desliming, the silica and alumina contents of a selected product were 30% and 26% lower, respectively.
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China is rich in titanium resources, which accounts for more than 35% of the world. But, until today, the industrial TiO2 recovery for ilmenite ore is slightly higher than 30% in the current pulsating high-gradient magnetic separation-flotation process (HGMS) so that a large amount of ilmenite value were lost in tailings. A centrifugal HGMS (CHGMS) method was introduced and a novel HGMS-flotation process combining the method was investigated to achieve an enhanced separation for Panzhihua ilmenite tailings in China. The results of this investigation indicate that this new process achieved a superior separation performance to the current one and produced a qualified ilmenite concentrate assaying 46.62% TiO2 at a significantly enhanced recovery reaching 40.42%. In the new process, the CHGMS separator concentrated ilmenites at high selectivity and produced a high-grade ilmenite concentrate fed to flotation cleaning process, which significantly benefited the enhanced separation for the ilmenite tailings. It was concluded that this new HGMS-flotation process is prospective in improving the separation performance for ilmenite from tailings.
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This article refers to a study in Tanzania on fringe benefits or welfare via the work contract1 where we will work both quantitatively and qualitatively. My focus is on the vital issue of combining methods or methodologies. There has been mixed views on the uses of triangulation in researches. Some authors argue that triangulation is just for increasing the wider and deep understanding of the study phenomenon, while others have argued that triangulation is actually used to increase the study accuracy, in this case triangulation is one of the validity measures. Triangulation is defined as the use of multiple methods mainly qualitative and quantitative methods in studying the same phenomenon for the purpose of increasing study credibility. This implies that triangulation is the combination of two or more methodological approaches, theoretical perspectives, data sources, investigators and analysis methods to study the same phenomenon.However, using both qualitative and quantitative paradigms in the same study has resulted into debate from some researchers arguing that the two paradigms differ epistemologically and ontologically. Nevertheless, both paradigms are designed towards understanding about a particular subject area of interest and both of them have strengths and weaknesses. Thus, when combined there is a great possibility of neutralizing the flaws of one method and strengthening the benefits of the other for the better research results. Thus, to reap the benefits of two paradigms and minimizing the drawbacks of each, the combination of the two approaches have been advocated in this article. The quality of our studies on welfare to combat poverty is crucial, and especially when we want our conclusions to matter in practice.
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Studies on ecological modernization have produced a fruitful discussion concerning the connection between society and nature based on the evolution of socio-political institutions. However, the question from the individual’s perspective and their evaluation of the environmental institutions’ modernization remains unsystematically explored. This paper introduces the actor’s narratives on what I called time and space restructuration to define a sensitive method to explore the socio-ecological controversies produced by the enactment of a new environmental institution at the national level. The paper reconstructs the social discourse in relation to the exponential growth of Chilean extractive industries, which run in parallel with the government’s intent to ensure high levels of sustainability through institutional changes that occurred between 1990 and 2015. The main argument proposes that rendering the ecological modernization as a final stage of institutional improvement obscures a controversial reorganization of actions and roles at the environmental level. From this perspective, the clash between different organizations of time and space at the environmental level, among different social actors, offers a valid perspective on the re-emergence of socio-ecological conflicts.
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Gold mining is a major source of metal and metalloid emissions into the environment. Studies were carried out in Krugersdorp, South Africa, to evaluate the ecological and human health risks associated with exposure to metals and metalloids in mine tailings contaminated soils. Concentrations of arsenic (As), cadmium (Cd), chromium (Cr), cobalt (Co), copper (Cu), lead (Pb), manganese (Mn), nickel (Ni), and zinc (Zn) in soil samples from the area varied with the highest contamination factors (expressed as ratio of metal or metalloid concentration in the tailings contaminated soil to that of the control site) observed for As (3.5x10²), Co (2.8x10²) and Ni (1.1x10²). Potential ecological risk index values for metals and metalloids determined from soil metal and metalloid concentrations and their respective risk factors were correspondingly highest for As (3.5x10³) and Co (1.4x10³), whereas Mn (0.6) presented the lowest ecological risk. Human health risk was assessed using Hazard Quotient (HQ), Chronic Hazard Index (CHI) and carcinogenic risk levels, where values of HQ > 1, CHI > 1 and carcinogenic risk values > 1×10⁻⁴ represent elevated risks. Values for HQ indicated high exposure-related risk for As (53.7), Cr (14.8), Ni (2.2), Zn (2.64) and Mn (1.67). Children were more at risk from heavy metal and metalloid exposure than adults. Cancer-related risks associated with metal and metalloid exposure among children were also higher than in adults with cancer risk values of 3×10⁻² and 4×10⁻² for As and Ni respectively among children, and 5×10⁻³ and 4×10⁻³ for As and Ni respectively among adults. There is significant potential ecological and human health risk associated with metal and metalloid exposure from contaminated soils around gold mine tailings dumps. This could be a potential contributing factor to a setback in the health of residents in informal settlements dominating this mining area as the immune systems of some of these residents are already compromised by high HIV prevalence.
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Quartz mill tailings are produced in a huge amount per year in China. Therefore, now there is an urgent demand for utilization of the quartz mill. In the present research, the quartz mill tailings was used as a filler for metakaolin-based geopolymer to restraint the shrinkage and improve mechanical property. This work studied the influence of quartz mill tailings on the properties of geopolymer prepared by alkali-activated metakaolin. Performance of geopolymer incorporated with quartz mill tailings were addressed in terms of workability, compressive and flexural strength, and drying shrinkage at different ages. Further, X-ray Diffraction, Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR) and Mercury Intrusion Porosimetry (MIP) were applied to investigate the relevant microstructure. The results indicated that addition of quartz mill tailings increased the viscosity of the paste, and meanwhile decreased the flowability of geopolymer. Up to 20 % of the tailings can replace metakaolin to prepare geopolymer without a negative effect on the mechanical property. Up to 30 % of quartz mill tailings had a role to decrease the drying shrinkage. Besides, weight loss ratio of geopolymer decreased gradually with increasing dosage of the quartz mill tailings. Addition of the quartz mill tailings did not change the mineral composition of alkali-activated metakaolin, and meanwhile the amorphous or semi-crystalline phase has been found. MIP and FTIR results showed that moderate addition of quartz mill tailings optimized the microstructure of geopolymer. Therefore, quartz mill tailings can replace metakaolin up to 20 % to prepare geopolymer.
Article
Three moss (Pleurozium spp., Polytrichum spp., and Rhytidiadelphus spp.) and two lichen (Hypogymnia physodes and Pseudevernia furfuracea) taxons covered in the bags were used to monitor air quality. Bags were exposed at the different distances from the tailing pond because of insufficient security and source of heavy metal pollution. Moss/lichen bags were exposed for six weeks at 0-, 50-, 100-, 150- and 200-m distances from Slovinky tailing pond, in the main wind direction (down the valley). Accumulation ability of heavy metals expressed by relative accumulation factor (RAF) increases in the order of Polytrichum spp.<H. physodes <Pleurozium spp.<P. furfuracea <Rhytidiadelphus spp. Moss/lichen species showed different accumulation capacity for individual heavy metals. Rhytidiadelphus spp. was found to possess the significantly highest (P < 0.01) ability to accumulate Cd, Zn, Ni, Mn and Fe. The highest RAF values of Pb, Zn, Ni and Fe were determined in samples exposed at 200-m distance from pollution source.
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This paper presents the comprehensive stability analysis of the rock-fill tailing dam constructed at Rampura Agucha zinc mine in Rajasthan, India. The results of the feasibility study carried out prior to the expansion of the dam height from existing 27 to 51 m have been presented. The final cross-section of the tailing dam was arrived based on the extensive stability analysis considering both the upstream and downstream methods of embankment rising. The factor of safety values was calculated from Bishop’s simplified method, Janbu’s method and Spencer’s method by considering the circular failure surfaces. Further, the dynamic stability analyses were also carried out using the pseudostatic approach. The results from the limit equilibrium approaches were validated with the shear strength reduction technique using finite difference-based Fast Lagrangian Analysis of Continua in 2D analysis. The factor of safety values calculated from the different approaches was found to be in good agreement with each other. ...
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This study demonstrates an efficient synthesis of highly reactive silica using hydrometallurgical processing of serpentinite tailings. Proposed process uses two-stage (acid and alkaline) leaching of serpentinite tailings and precipitation of silica from the sodium metasilicate solution using hydrochloric acid. The alkaline leaching and the effect of impurities on the precipitation of amorphous silica under the conditions of maximum sol stability were examined in detail.The proposed route is technologically advantageous because the product did not contain residues of the original raw serpentinite and was characterised by high purity (99.4 wt. % SiO2), large specific area (541 m2 g−1) and consistent quality. Moreover, less sensitivity to the presence of impurities and longer gelation times, offering a longer time period for manipulating the product in the final stages of the process, were achieved. The total yield of silicon in the overall process was 90–91 %.
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A mining impacted cropland was studied in order to assess its As pollution level and the derived environmental and health risks. Profile soil samples (0-50cm) and rye plant samples were collected at different distances (0-150m) from the near mine dump and analyzed for their As content and distribution. These cropland soils were sandy, acidic and poor in organic matter and Fe/Al oxides. The soil total As concentrations (38-177mgkg(-1)) and, especially, the soil soluble As concentrations (0.48-4.1mgkg(-1)) importantly exceeded their safe limits for agricultural use of soils. Moreover, the soil As contents more prone to be mobilized could rise up to 25-69% of total As levels as determined using (NH4)2SO4, NH4H2PO4 and (NH4)2C2O4·H2O as sequential extractants. Arsenic in rye plants was primarily distributed in roots (3.4-18.8mgkg(-1)), with restricted translocation to shoots (TF=0.05-0.26) and grains (TF=<0.02-0.14). The mechanism for this excluder behavior should be likely related to arsenate reduction to arsenite in roots, followed by its complexation with thiols, as suggested by the high arsenite level in rye roots (up to 95% of the total As content) and the negative correlation between thiol concentrations in rye roots and As concentrations in rye shoots (|R|=0.770; p<0.01). Accordingly, in spite of the high mobile and mobilizable As contents in soils, As concentrations in rye above-ground tissues comply with the European regulation on undesirable substances in animal feed. Likewise, rye grain As concentrations were below its maximum tolerable concentration in cereals established by international legislation.
Article
The aim of mine tailings management strategy is to protect the environment and humans from risks associated with mine tailings. It seems inevitable that future production from lower grade ores in mines will increase, generating a higher tonnage of tailings. Approximately 14 billion tonnes of tailings were produced globally by the mining industry in 2010. The need for a comprehensive framework for mine tailings management (including dewatering) that promotes sustainable development is therefore becoming increasingly recognised by the mining industry. In this paper, we review existing frameworks for tailings management and propose an improved framework that considers key sustainable development pillars: technological, economic, environmental, policy, and social aspects. This framework will be able to guide the mining sector to choose its mine tailings management strategy based on sustainable development concepts. It incorporates a range of tools for determining trade-offs inherent in different tailings management methods during operation and throughout the Life of Mine (LOM); these include Life Cycle Assessment (LCA), Net Present Value (NPV), Hierarchy System Model (HSM), and Decision Analysis. In particular, this proposed recognises the highly case-specific of tailings management by explicitly integrating physicochemical characterisation of tailings properties as a first step. In future, the framework could be expanded through integration of reuse/recycle principles of industrial symbiosis.