Dispersal Trains Research Articles

Threshold Filtering for Detecting Label Inference Attacks in Vertical Federated Learning

Federated learning, as an emerging machine-learning method, has received widespread attention because it allows users to train locally during the training process and uses relevant cryptographic knowledge to safeguard the privacy of data during model aggregation. However, existing federated learning is also susceptible to privacy breaches, e.g., label inference attacks against vertical federated learning scenarios, where an adversary is able to reason about the labels of other participants based on the trained model, leading to serious privacy breaches. In this paper, we design a detection method for label inference attacks in vertical federated learning scenarios, which is able to detect the attacks based on the principles of the attacks. We design a threshold-filtering detection method based on the principle of attack to determine that the model is under attack when the threshold value is greater than a set parameter. Furthermore, we have created six threat model classifications based on different a priori conditions of the adversary to comprehensively analyze the adversary’s attacks. In addition to the detection method of attacks, the extent of attacks on the model and the effectiveness of the defense can also be evaluated. The evaluation module will experimentally measure the changes in the relevant metrics such as the accuracy of the attack, the F1 score, and the change in the accuracy after the defense method. For example, detection in the full connected neural network model assesses the attack and defense effectiveness of the model with an attack accuracy of 86.72% in the breast cancer Wisconsin dataset and an F1 score of 0.743, which is reduced to 36.36% after dispersed training. This ensures that users have an overall grasp of the extent to which the training model is under attack before deploying the model.

Gold in eskers and gyttja overlying auriferous till, Regnault deposit, Quebec

The Regnault gold deposit in Quebec, Canada, was discovered by Kenorland Minerals North America Ltd in 2020 following identification of a gold-in-till dispersal train. In 2022, two non-traditional media – eskers and organic lake-bottom mud (gyttja) – were sampled to determine if they likewise contained gold anomalies that vectored the mineral deposit. Striking, coherent (mappable) anomalies exist in both media. The gold-in-esker dispersal train has a similar pathfinder element association as the gold-in-till dispersal train (e.g. Te, W) but contains approximately twice the gold (average 73 ppb Au) in the <63 µm fraction. It is hypothesized to be a meltwater-sorted version of the gold-in-till train, sourced from the erosional esker corridor some 3 km upflow. By contrast, the gold-in-gyttja dispersal train is substantially different to both the gold-in-esker and gold-in-till dispersal trains. It has lost significant association with pathfinder elements, contains an order of magnitude less gold (average 4.2 ppb Au), and is tentatively hypothesized to have a hydromorphic origin, sourced primarily from the gold-in-till dispersal train. The main takeaway from the study is that the sampling of any of these three media – eskers, gyttja or till – could have conceivably led to the discovery.

Till Geochemistry as a Vector to Metasomatic Iron and Alkali-Calcic Systems and Associated Deposits in the Great Bear Magmatic Zone, Northwest Territories, Canada

Recent advances in the characterization of metasomatic iron and alkali-calcic (MIAC) systems with associated iron-oxide apatite (IOA) prospects and iron-oxide–copper–gold (IOCG) and metasomatic cobalt deposits of the Great Bear magmatic zone were used to determine if the geochemistry of glacial sediments can unveil pathfinder elements indicative of mineralization and associated alteration. Analysis of variance within bedrock lithogeochemical (n = 707 samples) and till geochemical datasets (n = 92 samples) are compared. Results show that Fe, Co, Ni, Cu, As, Mo, Bi, La, Th, U, and W were identified as potential vectoring elements in different fractions of till due to their anomalous concentrations down-ice of various mineralized outcrops within the study area. For instance, Fe, Co, Cu, and Mo were established as the most useful vectoring elements in the locally derived till (<2 km down-ice) near the Sue Dianne IOCG deposit, and Fe, Co, Ni, Cu, Mo, W, Bi, and U near the Fab IOCG prospect. At the Sue Dianne deposit, the ratios of near-total (4-acid digestion) versus partial (modified aqua regia digestion) concentrations in the silt + clay-sized till fraction (<0.063 mm) for both La and Th reflect the mineralization alteration signature and define a more consistent dispersal train from mineralization compared to element concentrations mapped alone. Additional testing in an area of continuous till cover near an isolated point source is recommended to further develop the elemental ratio method for exploration of MIAC systems.

Tracing Detrital Epidote Derived from Alteration Halos to Porphyry Cu Deposits in Glaciated Terrains: The Search for Covered Mineralization

Abstract Distal alteration related to porphyry Cu mineralization is typically characterized by an abundance of green minerals, such as epidote, tremolite, and chlorite, within the propylitic and sodic-calcic alteration zones and extends far outside (>1 km) the mineralized zone(s). Glacial erosion and dispersal derived from rocks affected by propylitic and sodic-calcic alteration have resulted in the development of extensive dispersal trains of epidote in till (glacial sediment) that can reach 8 to 330 km2 as observed at four porphyry Cu study sites in the Quesnel terrane of south-central British Columbia: Highland Valley Copper, Gibraltar, Mount Polley, and Woodjam deposits. At each of these sites, epidote is more abundant in heavy mineral concentrates of till collected directly over and down-ice from mineralization and associated alteration. Epidote grains in till with >0.6 ppm Sb and >8 ppm As (as determined by laser ablation-inductively coupled plasma-mass spectrometry) are attributed to a porphyry alteration provenance. There is a greater abundance of epidote grains with high concentrations of trace elements (>12 ppm Cu, >2,700 ppm Mn, >7 ppm Zn, and >37 ppm Pb) in each porphyry district compared to background regions. This trace element signature recorded in till epidote grains is heterogeneously distributed in these districts and is interpreted to reflect varying degrees of metal enrichment from a porphyry fluid source. Tracing the source of the epidote in the till (i.e., geochemically tying it to porphyry-related propylitic and/or sodic-calcic alteration), coupled with porphyry vectoring tools in bedrock, will aid in the detection of concealed porphyry Cu mineralization in glaciated terrains.

Review of till geochemistry and indicator mineral methods for mineral exploration in glaciated terrain

Since the 1970s, till geochemical and indicator mineral methods for mineral exploration, provenance studies and environmental research in glaciated terrain have been developed, tested and refined. This review summarizes these methods, focusing on field and laboratory methods for till geochemical, indicator mineral and boulder surveys. This review of protocols is intended as a guide for the mineral exploration industry and publicly funded agencies. It summarizes till as a sample medium, and describes the formation of glacial dispersal trains, along with methods for till sample collection, sample processing, matrix geochemistry, indicator mineral analyses, quality assurance/quality control procedures and data reporting and interpretation. The methods described here can be used to conduct reconnaissance- to deposit-scale till sampling surveys to assess mineral resource potential and establish environmental baselines. Supplementary material: Appendix A – Photographs of till types described in text; Appendix B – Logistical and geological factors to consider in till sample survey design; Appendix C – Photographs of glaciate terrain types described in text; and Appendix D – Till sample processing and analysis flow charts are available at https://doi.org/10.6084/m9.figshare.c.6786087 Thematic collection: This article is part of the Reviews in Exploration Geochemistry collection available at: https://www.lyellcollection.org/topic/collections/reviews-in-exploration-geochemistry

Beyond model splitting: Preventing label inference attacks in vertical federated learning with dispersed training

Federated learning is an emerging paradigm that enables multiple organizations to jointly train a model without revealing their private data. As an important variant, vertical federated learning (VFL) deals with cases in which collaborating organizations own data of the same set of users but with disjoint features. It is generally regarded that VFL is more secure than horizontal federated learning. However, recent research (USENIX Security’22) reveals that it is still possible to conduct label inference attacks in VFL, in which attacker can acquire privately owned labels of other participants; even VFL constructed with model splitting (the kind of VFL architecture with higher security guarantee) cannot escape it. To solve this issue, in this paper, we propose the dispersed training framework. It utilizes secret sharing to break the correlations between the bottom model and the training data. Accordingly, even if the attacker receives the gradients in the training phase, he is incapable to deduce the feature representation of labels from the bottom model. Besides, we design a customized model aggregation method such that the shared model can be privately combined, and the linearity of secret sharing schemes ensures the training accuracy to be preserved. Theoretical and experimental analyses indicate the satisfactory performance and effectiveness of our framework.

SEQUENTIAL EXTRACTION OF SUBSTANCES WITH KNOWN Au SPECIATION – AN EXPERIMENTAL DATA

A study has been conducted on the features of distriburion of Au among the fractions of a 7-step sequential extraction procedure using model substances that are similar in composition to natural organic matter from the dispersion train of sulfide tailings. Use has been made of model substances with known Au speciations: bulk native gold, nanoscale native gold, Au-containing pyrite, humic acids, and Fe(III) oxides/hydroxides, which served as the basis for preparing mixtures with low-Au filler substances (quartz, limestone, humic acids, Fe(III) oxides/hydroxides). It has been stated that several Au species are leached in one fraction during sequential extraction. Nanoscale Au 0 and gold bound to the organic matter are leached together in easily oxidizable (organic) fraction; gold bound to Fe(III) compounds and Au complexes chemisorbed on the surface of other minerals (sulfides, aluminosilicates) are leached in reducible (hydroxides) fraction; "invisible" gold in sulfides, nanoscale Au 0 and, partially, >1 μm-seized bulk Au 0 are leached in hardly oxidizable (sulfidic) fraction. Bulk native gold is leached predominantly in residual fraction. Mobile species are Au bound to water-soluble organic compounds and complexes of ionic Au desorbed from the surface of minerals.

Permafrost thaw sensitivity prediction using surficial geology, topography, and remote-sensing imagery: a data-driven neural network approach

Seasonal or degradational thaw subsidence of permafrost terrain affects the landscape, hydrology, and sustainability of permafrost as an engineering substrate. We perform permafrost thaw sensitivity prediction via supervised classification of a feature set consisting of geological, topographic, and multispectral variables over continuous permafrost near Rankin Inlet, Nunavut, Canada. We build a reference classification of thaw sensitivity using process-based categorization of seasonal subsidence as measured from differential interferometric synthetic aperture radar whereby categories of thaw sensitivity are reflective of ground ice conditions. Classification is performed using a neural network trained on both dispersed and parcel-based reference data. For Low, Medium, High, and Very High thaw sensitivity categories, generalized classification accuracy is 70.8% for 20.6 km2 of dispersed training data. In all cases, the majority classes of Low and Medium thaw sensitivity are predicted with higher accuracy and more certainty, while the minority classes of High and Very High thaw sensitivity are underpredicted. Minority classes can be combined to improve accuracy at the expense of a reduced level of discrimination. The two-class problem can be classified with an accuracy of 81.8%, thereby effectively distinguishing between stable and unstable ground. The method is applicable to similar Low-Arctic permafrost terrain with geological and topographical controls on thaw sensitivity. However, generalized accuracy is reduced for parcel-based training, indicating that reference samples are not totally representative for inference beyond the parcel, and any deployment of the network to other geographical regions would benefit from full or partial retraining with local data.

Detecting Buried Porphyry Cu Mineralization in a Glaciated Landscape: A Case Study from the Gibraltar Cu-Mo Deposit, British Columbia, Canada

Abstract At the Gibraltar porphyry Cu-Mo deposit in south-central British Columbia, Canada, geochemical and mineralogical anomalies in till around a cluster of mineral occurrences form amoeboid-shaped dispersal patterns controlled by three phases of ice movement. The glacial dispersal patterns defined by elevated concentrations of ore (Cu, Mo) and pathfinder (Ag, Zn) elements and alteration oxides (Al2O3, K2O) in the till matrix (clay and silt plus clay fractions) extend over areas of 6–36 km2 and are centered on the main economic mineralization. Mineralogical dispersal trains were identified by the high abundances of chalcopyrite, pyrite, jarosite, titanite, and epidote, which were derived from the mineralization and its associated oxidation and alteration zones. These mineralogical anomalies in till extend approximately 30 km2 for chalcopyrite, 62 km2 for jarosite, and up to 136 km2 for epidote. Epidote grains in till with a trace element composition of >10 ppm As, >4 ppm Sb, <200 ppm total rare earth elements (ΣREEs), <45 ppm Y, <100 ppm Sc + Cr + Y, and/or <2 ppm Th + Hf are interpreted as being either principally derived from the intrusive rocks or from hydrothermal alteration of the porphyry mineralization. Rare epidote grains with >30 ppm Cu, interpreted to be related to the porphyry Cu mineralization, were detected in till up to 7 km down-ice from the economic mineralization. This study demonstrates that till geochemistry and mineralogy, combined with geochemical analyses of specific minerals such as epidote, are efficient methods for identifying porphyry Cu mineralization in terrains covered by glacial sediments.

Pedagogical practice of philological students: cooperation with the basic school

The author considers pedagogical practice from the positions of professional risks presented in the scientific literature, taking into account which he builds a practice-oriented system of complex dispersed training of students for practice in the Russian language. At the same time, the emphasis is on interaction with basic schools, where future teachers receive their first professional experience. The university teachers ‘ knowledge of the school’s requirements, the general concept of practice, long-term cooperation of educational organizations of higher and secondary education, the built system of propaedeutic methodological training of students allow them to develop general pedagogical and special competencies of novice teachers, prevent possible risks, and contribute to their successful adaptation at school. Research methods: analysis of scientific literature, associative experiment, method of unfinished sentences, questionnaire, observation, reflexive essay, experimental training, conversation with the employer.

Stream sediment geochemical exploration for gold in Central Eastern Desert, Egypt: Application of the concentration-number fractal model, factor analysis, and geochemical mineralization probability index

Geochemical exploration by stream sediment sampling using bulk leach extractable gold (BLEG) technique and applying concentration-number (C-N) fractal model, factor analysis (FA), and geochemical mineralization probability index (GMPI) resulted in the recognition of new Au occurrences around the Sukari gold mine in the central Eastern Desert of Egypt. The geochemical data of 128 stream sediment samples collected from the study area was used for delineating the geochemical anomalies and characterizing the dispersion trains of ore and associated elements (Au, Ag, As, Sb, Cu, Pb, Zn, Mo). Statistical analysis of the geochemical data applying the C-N fractal modeling enabled us to identify significant anomaly and background populations of the investigated elements and to construct reliable geochemical anomaly maps. Factor analysis using centered log-ratios (CLR), to address the problem of closed compositional data, revealed significant element associations for mineralization (Au, As, Mo, Zn, Ba), country rock compositions (Rb, Li, Be, Sn, Bi for granite, and Co, Cr, Ni for mafic rocks), and element mobility (e.g. Sb, Zr, and Ag). Weak and moderate Au anomalies that cannot be detected by factor score maps can be delineated clearly by using the C-N fractal method and GMPI distribution map. Our study revealed that Ag, As, and Sb are the main pathfinder elements for gold mineralization in arid to semiarid regions exemplified by the Sukari gold district. Silver can be used as a “direct” pathfinder, whereas As and Sb are “indirect” pathfinders for Au in such regions. The spatial distribution of Au and Ag anomalies indicate that gold mineralization in the Sukari district is structurally controlled. However, the spatial distribution of Cu, Pb, Zn, and Mo is controlled by mineralogical and lithological factors and is not related to any significant base metal deposits.

Application of the C-N fractal model, factor analysis and geochemical mineralization probability index (GMPI) for delineating geochemical anomalies related to a Mn-Fe deposit and associated Cu mineralization in west-central Sinai, Egypt

The west-central Sinai area includes one of the most productive manganese deposits in Egypt (Um Bogma Mn-Fe ore). The explored area is covered by a Carboniferous and Cambro-Ordovician sedimentary succession overlying Precambrian basement rocks. The purpose of this study is to delineate geochemical anomalies of ore and related elements and track their dispersion trains, which may lead to the discovery of unknown ore deposits. For this purpose, 143 stream sediment samples were analysed and the data were interpreted using the concentration–number (C-N) fractal model, factor analysis and the geochemical mineralization probability index (GMPI). Geochemical thresholds obtained from the C-N fractal model, factor scores and GMPI were used for constructing geochemical anomaly maps and delineating probable anomalous sites. The spatial distribution of Mn, Cu, Co, Pb and Zn anomalies was correlated to Mn and Cu mineralization sites whereas those of Fe and Cr were consistent with mafic rock distributions. Factor analysis revealed significant element associations for mineralization (Cu, Co, Mn, Zn, Pb), country rock composition (Fe, Cr) and element mobility (Cd, Zn). The spatial distribution of ore elements (Mn, Cu) delineated by the factor score and GMPI distribution maps was confirmed and more accurately interpreted using geochemical anomaly maps constructed based on the fractal-derived thresholds. Based on the current study, recent Cu and Mn mineralization sites may be suggested. Cobalt, Zn, Pb and Cd are suggested as efficient pathfinder elements for marine Mn deposits. A dispersion sequence of Cd>Mn>Co>Pb>Zn>Cu>Cr>Fe was proposed based on the threshold distribution patterns of these elements. Supplementary material: Tables S1–S3 and Figures S1 and S2 are available at https://doi.org/10.6084/m9.figshare.c.5463511

Mercury Speciation in Natural and Mining-Related Systems

Mercury speciation and the composition of mercury phases in natural and mining-related environments is studied by the thermal release analysis combined with electrothermal atomic absorption spectroscopy (TA-ET-AAS), as well as scanning electron microscopy with energy-dispersive X-ray microanalysis (SEM-EDS). The analyses are applied to laboratory-made samples bearing mercury selenide and to field samples from sites known for relatively high natural or industrially induced Hg background. They are, namely, material from the dispersion train of the Ursk sulfide tailings (Ursk Village, Kemerovo region) and debris precipitated from snow sampled in the Kurai mercury zone (Aktash Village, Gorny Altai). The TA-ET-AAS method works well in discrimination and identification of Hg sulfide and Hg selenide provided that the samples contain sufficient amounts of both compounds, but the sum HgS + HgSe can be determined at any contents of the two compounds. The presence of both mercury sulfide and mercury selenide in the samples has been confirmed by SEM-EDS microanalysis. The temperature ranges for the mercury species (Hg2+; HgS+HgSe mixture; mercury bound with organic matter (Hg-OM), including CH3Hg+) are identical in the laboratory and field samples. Therefore, the suggested approach can ensure fast and reliable detection of Hg phases in rocks exposed to supergene alteration

Assessment of the Amaruq gold deposit signature in glacial sediments using multivariate geochemical data analysis and indicator minerals

The varying nature and thickness of glacial sediments affect the characteristics of mineralized dispersal trains in the Amaruq gold deposit area in Nunavut, northern Canada. To help evaluate the deposit signature, glacial sediments were collected from frost boils along transects parallel to the main ice-flow direction. A complementary detailed geochemical drift exploration dataset and a new Quaternary map were also used to define and interpret the geometry of the mineralized debris dispersal trains. Principal Component Analysis identifies a gold mineralization signature associating As, Ag, Au, Cu, Pb, Sb, W, S, Fe, and Zn and its mafic-BIF (Banded Iron Formation) host rock. This signature, similar to other lode gold geochemical signatures, follows a general NNW dispersal trend, in agreement with the predominant regional and local ice-flow indicators. In a zone characterized by streamlined landforms composed of thick distally -derived till, the dispersal train shows a higher distance for the first indicator to appear at surface down-ice of the known mineralization (~1 km lag) when compared to other mineralized dispersal trains (~300 m lag). Results from this area also show a lower intensity of deposit signature compared to mineralized dispersal trains located in thin locally-derived till characterized by small transverse moraine ridges. Elevated counts of scheelite and pristine-shaped gold grains are found down-ice of mineralization and their distribution is in general agreement with the dispersal train patterns defined by the till-matrix geochemistry. Our results strengthen the use of PCA and indicator minerals combined with an understanding of ice flow dynamics to map deposit signatures at surface and efficiently guide mineral exploration during glacial sediment surveys at local scales.

Natural organic matter from the dispersion train of gold sulfide tailings: group composition and fractionation of elements: case study of Ursk Tailings, Kemerovo Region, Siberia

We study the contents of elements and group composition in natural organic matter (NOM) that interacts with acid mine drainage (АMD) and high-sulfide tailings at the Ursk site (southwestern Siberia, Russia). AMD causes biomass changes in NOM, related changes in the composition of fractions, and hydrolysis of hydrolyzable compounds; it increases the water-soluble fraction and maintains depolymerization of humic acids to fulvic acids, but exerts no effect on substances soluble in organics (bitumen) or on poorly hydrolyzable compounds. Accumulation of inorganic elements and precipitation of minerals obscure the true fraction composition of NOM: the superposed mineral component contributes significantly to the water-soluble, humic acid, hydrolyzable and non-hydrolyzable fractions, and may reach 26.4% per total of all fractions. Rock-forming and potentially toxic elements partition among NOM fractions and predominate in the water-soluble fraction. The contents of Au and Ag are the highest in the fractions of humic acids and hydrolyzable compounds but are lower in the non-hydrolyzable residue. The obtained data have implications for possible migration of potentially toxic elements and noble metals and thus for remediation of polluted areas. The observed fractionation of Ag and Au in NOM helps us to understand the mechanisms of their distribution in organic-bearing environments, such as peatlands or coal basins.

Automated Indicator Mineral Analysis of Fine-Grained Till Associated with the Sisson W-Mo Deposit, New Brunswick, Canada

Exploration under thick glacial sediment cover is an important facet of modern mineral exploration in Canada and northern Europe. Till heavy mineral concentrate (HMC) indicator mineral methods are well established in exploration for diamonds, gold, and base metals in glaciated terrain. Traditional methods rely on visual examination of >250 µm HMC material. This study applies mineral liberation analysis (MLA) to investigate the finer (<250 µm) fraction of till HMC. Automated mineralogy (e.g., MLA) of finer material allows for the rapid collection of precise compositional and morphological data from a large number (10,000–100,000) of heavy mineral grains in a single sample. The Sisson W-Mo deposit has a previously documented dispersal train containing the ore minerals scheelite, wolframite, and molybdenite, along with sulfide and other accessory minerals, and was used as a test site for this study. Wolframite is identified in till samples up to 10 km down ice, whereas in previous work on the coarse fraction of till it was only identified directly overlying mineralization. Chalcopyrite and pyrite are found up to 10 km down ice, an increase over 2.5 and 5 km, respectively, achieved in previous work on the coarse fraction of the same HMC. Galena, sphalerite, arsenopyrite, and pyrrhotite are also found up to 10 km down ice after only being identified immediately overlying mineralization using the >250 µm fraction of HMC. Many of these sulfide grains are present only as inclusions in more chemically and robust minerals and would not be identified using optical methods. The extension of the wolframite dispersal train highlights the ability of MLA to identify minerals that lack distinguishing physical characteristics to aid visual identification.

Exploration Potential of Fine-Fraction Heavy Mineral Concentrates from Till Using Automated Mineralogy: A Case Study from the Izok Lake Cu–Zn–Pb–Ag VMS Deposit, Nunavut, Canada

Exploration under thick glacial sediment cover is an important facet of modern mineral exploration in Canada and northern Europe. Till heavy mineral concentrate (HMC) indicator mineral methods are well established in exploration for diamonds, gold, and base metals in glaciated terrain. Traditional methods rely on visual examination of >250 µm HMC material, however this study applies modern automated mineralogical methods (mineral liberation analysis (MLA)) to investigate the finer (<250 µm) fraction of till HMC. Automated mineralogy of finer material allows for rapid collection of precise compositional and morphological data from a large number (10,000–100,000) of heavy mineral grains in a single sample. The Izok Lake volcanogenic massive sulfide (VMS) deposit, one of the largest undeveloped Zn–Cu resources in North America, has a well-documented fan-shaped indicator mineral dispersal train and was used as a test site for this study. Axinite, a VMS indicator mineral difficult to identify optically in HMC, is identified in till samples up to 8 km down ice. Epidote and Fe-oxide minerals are identified, with concentrations peaking proximal to mineralization. Corundum and gahnite are intergrown in till samples immediately down ice of mineralization. Till samples also contain chalcopyrite and galena up to 8 km down ice of mineralization, an increase from 1.3 km for sulfide minerals in till previously reported for coarse HMC fractions. Some of these sulfide grains occur as inclusions within chemically and physically robust mineral grains and would not be identified visually in the coarse HMC visual counts. Best practices for epoxy mineral grain mounting and abundance reporting are presented along with the automated mineralogy of till samples down ice of the deposit.

Modeling the Process of Au Sorption by Natural Sorbents in the Conditions of the Dispersion Train of a Sulfide Tailings

The experimental study is aimed at elucidation the laws of Au sorption/deposition by various natural sorbents in an acidic environment (pH=2). The experiments simulated the conditions of the dispersion train of the Ursk tailings (Kemerovo region, Russia), where active concentration of Au by natural organic matter in an acidic environment is observed. It was found that the degree of extraction of gold from a sulfate solution is generally higher than from chloride solution. This may indicate higher thermodynamic stability of Au chloride complexes in an acidic environment than sulfate ones. Higher deposition rates of gold are observed in solutions with a predominant content of sulfate ions. According to the degree of deposition of Au, a series was established (from larger to smaller): a mixture of clay minerals (smectite + palygorskite + muscovite) > humic acids > kaolinite

Redistribution and speciation of elements in gold-bearing sulfide mine tailings interbedded with natural organic matter: case study of Novo-Ursk deposit, Kemerovo Region, Siberia

The paper presents data on two cores from the dispersion train of gold-bearing sulfide tailings in the Novo-Ursk deposit (Kemerovo region, Russia), where organic-bearing mud and natural organic matter are interbedded with cyanide tailings and acid mine drainage (AMD). The study focuses on speciation of Au, Ag and potentially toxic elements (PTE), including Fe, Cu, Zn, As, Se and Pb according to selective sequential extractions. Since large contents of elements are found in water solution and bound to Fe(III) compounds, sulfides and/or organic matter in both cores, the organic material behaves as a natural biogeochemical barrier for potentially toxic elements and precious metals released from AMD. The interaction with organic matter results in biogeochemical sorption and immobilization of elements and is favourable for secondary enrichment in gold and silver. It leads to immobilization of elements that further form new mineral phases or become partitioned between existing phases. On the other hand, very high concentrations of water-soluble and oxidizable species of PTE and Au, which are unstable in surface conditions and may become remobilized when the environment changes, make the organic material less workable and even potentially hazardous. Thus, both positive (secondary enrichment) and negative (pollution) effects should be taken into account in the planning and design of systems for purification, disposal of cyanide tailings and recovery of useful components from tailings using natural organic matter as a geochemical barrier.

Internal waves in a shear background current: Transition from solitary-wave regime to dispersive-wave regime

For a given stratification, the presence of a shear background current may significantly alter the wave form of internal waves. Depending on the direction and strength of background shear, it could prevent the formation of solitary waves but enable the formation of a dispersive wave train.