Search Results (555)

The increasing demand for mineral resources has generated mine tailings with heavy metals (HM) that negatively impact human and ecosystem health. Therefore, it is necessary to implement strategies that promote the immobilization or elimination of HM, like phytoremediation. However, the toxic effect of metals may affect plant establishment, growth, and fitness, reducing phytoremediation efficiency. Therefore, adding organic amendments to mine tailings, such as biochar, can favor the establishment of plants, reducing the bioavailability of HM and its subsequent incorporation into the food chain. Here, we evaluated HM bioaccumulation, biomass, morphological characters, chlorophyll content, and genotoxic damage in the herbaceous Crotalaria pumila to assess its potential for phytostabilization of HM in mine tailings. The study was carried out for 100 days on plants developed under greenhouse conditions under two treatments (tailing substrate and 75% tailing/25% coconut fiber biochar substrate); every 25 days, 12 plants were selected per treatment. C. pumila registered the following bioaccumulation patterns: Pb > Zn > Cu > Cd in root and in leaf tissues. Furthermore, the results showed that individuals that grew on mine tailing substrate bioaccumulated many times more metals (Zn: 2.1, Cu: 1.8, Cd: 5.0, Pb: 3.0) and showed higher genetic damage levels (1.5 times higher) compared to individuals grown on mine tailing substrate with biochar. In contrast, individuals grown on mine tailing substrate with biochar documented higher chlorophyll a and b content (1.1 times more, for both), as well as higher biomass (1.5 times more). Therefore, adding coconut fiber biochar to mine tailing has a positive effect on the establishment and development of C. pumila individuals with the potential to phytoextract and phytostabilize HM from polluted soils. Our results suggest that the binomial hyperaccumulator plant in combination with this particular biochar is an excellent system to phytostabilize soils contaminated with HM. Full article

Mine-tailing dumps are one of the leading sources of environmental degradation, often with public health and ecological consequences. Due to the complex ecosystems generated, they are ideal sites for exploring the bacterial diversity of specially adapted microorganisms. We investigated the concentrations of trace metals in solid copper (Cu) mine tailings from the Ovejería Tailings Dam of the National Copper Corporation of Chile and used high-throughput sequencing techniques to determine the microbial community diversity of the tailings using 16S rRNA gene-based amplicon sequence analysis. The concentrations of the detected metals were highest in the following order: iron (Fe) > Cu > manganese (Mn) > molybdenum (Mo) > lead (Pb) > chromium (Cr) > cadmium (Cd). Furthermore, 16S rRNA gene-based sequence analysis identified 12 phyla, 18 classes, 43 orders, 82 families, and 154 genera at the three sampling points. The phylum Proteobacteria was the most dominant, followed by Chlamydiota, Bacteroidetes, Actinobacteria, and Firmicutes. Genera, such as Bradyrhizobium, Aquabacterium, Paracoccus, Caulobacter, Azospira, and Neochlamydia, showed high relative abundance. These genera are known to possess adaptation mechanisms in high concentrations of metals, such as Cd, Cu, and Pb, along with nitrogen-fixation capacity. In addition to their tolerance to various metals, some of these genera may represent pathogens of amoeba or humans, which contributes to the complexity and resilience of bacterial communities in the studied Cu mining tailings. This study highlights the unique microbial diversity in the Ovejería Tailings Dam, including the discovery of the genus Neochlamydia, reported for the first time for heavy metal resistance. This underscores the importance of characterizing mining sites, particularly in Chile, to uncover novel bacterial mechanisms for potential biotechnological applications. Full article

Despite the tremendous advances in aircraft design that led to successful powered flights of aircraft as heavy as the Antonov An-225 Mriya, which weighs 640 tons, or as fast as the NASA-X-43A, which reached a record of Mach 9.6, many characteristics of bird flight have yet to be utilized in aircraft designs. These characteristics enable various species of birds to fly efficiently in gusty environments and rapidly change their momentum in flight without having modern thrust vector control (TVC) systems. Vultures and seagulls, as examples of expert gliding birds, can fly for hours, covering more than 100 miles, without a single flap of their wings. Inspired by the Great Black-Backed Gull (GBBG), this paper presents “CGull”, a non-flapping unmanned aerial vehicle (UAV) with wing and tail morphing capabilities. A coupled two degree-of-freedom (DOF) morphing mechanism is used in CGull’s wings to sweep the middle wing forward and the outer feathered wing backward, replicating the GBBG’s wing deformation. A modular two DOF mechanism enables CGull to pitch and tilt its tail. A computational model was first developed in MachUpX to study the effects of wing and tail morphing on the generated forces and moments. Following the biological construction of birds’ feathers and bones, CGull’s structure is mainly constructed from carbon-fiber composite shells. The successful flight test of the proof-of-concept physical model proved the effectiveness of the proposed morphing mechanisms in controlling the UAV’s path. Full article

One technique that is widely used in various fields, including nonlinear target tracking, is the extended Kalman filter (EKF). The well-known minimum mean square error (MMSE) criterion, which performs magnificently under the assumption of Gaussian noise, is the optimization criterion that is frequently employed in EKF. Further, if the noises are loud (or heavy-tailed), its performance can drastically suffer. To overcome the problem, this paper suggests a new technique for maximum correntropy EKF with nonlinear regression (MCCEKF-NR) by using the maximum correntropy criterion (MCC) instead of the MMSE criterion to calculate the effectiveness and vitality. The preliminary estimates of the state and covariance matrix in MCKF are provided via the state mean vector and covariance matrix propagation equations, just like in the conventional Kalman filter. In addition, a newly designed fixed-point technique is used to update the posterior estimates of each filter in a regression model. To show the practicality of the proposed strategy, we propose an effective implementation for positioning enhancement in GPS navigation and radar measurement systems. Full article

Soil heavy metal pollution is one of the hottest topics in soil environmental research. There are a large number of small abandoned metal mines in China. Due to the lack of timely restoration and treatment, the heavy metal concentration in the soil within these mining areas often exceeds the local background levels, facilitating pollution spread to other natural factors such as precipitation, resulting in a wider extent of continuous contamination. This paper investigates the current status of heavy metal pollution in an abandoned small lead-zinc mine, particularly examining the concentrations of 10 specific heavy metals (V, Cr, Ni, Zn, As, Cd, Hg, Pb, Cu, Co) in soil samples. Additionally, it explores the extent of contamination caused by these heavy metals within the area. Besides, principal component analysis and positive matrix factorization model (PMF) were adopted to determine the sources of these heavy metals. The risk assessment of the pollution status was also carried out. The provision of a scientific basis for mining area management under similar conditions holds significant importance. The results indicate a significant positive correlation among the majority of these 10 heavy metals in soil. The presence of these heavy metals in the soil within the concentrator and tailings reservoir area primarily stems from mining operations, construction activities, and discharges from the power system. Hg, Pb, Zn, and As in the surrounding agricultural land mainly come from the heavy metal spillover from the mining area. Furthermore, the area is plagued by severe contamination from As and Pb. The Nemerow comprehensive index method has confirmed substantial pollution in both the concentrator and tailings reservoir. Additionally, there exists a substantial ecological risk ranging from moderate to high. Full article

For lithium-ion batteries and supercapacitors in hybrid power storage facilities, both steady degradation and random shock contribute to their failure. To this end, in this paper, we propose to introduce the degradation-threshold-shock (DTS) model for their remaining useful life (RUL) prediction. Non-homogeneous compound Poisson process (NHCP) is proposed to simulate the shock effect in the DTS model. Considering the long-range dependence and heavy-tailed characteristics of the degradation process, fractional Weibull process (fWp) is employed in the diffusion term of the stochastic degradation model. Furthermore, the drift and diffusion coefficients are constantly updated to describe the environmental interference. Prior to the model training, steady degradation and shock data must be separated, based on the three-sigma principle. Degradation data for the lithium-ion batteries (LIBs) and ultracapacitors are employed for model verification under different operation protocols in the power system. Recent deep learning models and stochastic process-based methods are utilized for model comparison, and the proposed model shows higher prediction accuracy. Full article

Sustainable potable groundwater supply is crucial for human development and the preservation of natural habitats. The largest endorheic inland lake in Kazakhstan, Balkhash Lake, is the main water resource for the arid southeastern part of the country. Several ore enrichment plants that are located along its shore have heavy metal pollution potential. The study area is located around a plant that has an evident anthropogenic impact on the Balkhash Lake aquatic ecological system, with ten known heavy metal toxic hotspots endangering fragile habitats, including some indigenous human communities. This study assessed the risk of heavy metal contamination from tailing dump operations, storage ponds, and related facilities and suggested management practices for preventing this risk. The coastal zone risk assessment analysis used an innovative integrated groundwater numerical flow and transport model that predicted the spread of groundwater contamination from tailing dump operations under several mitigation strategies. Heavy metal pollution prevention models included a no-action scenario, a filtration barrier construction scenario, and two scenarios involving the drilling of drainage wells between the pollution sources and the lake. The scenario assessment indicates that drilling ten drainage wells down to the bedrock between the existing drainage channel and the lake is the optimal engineering solution for confining pollution. Under these conditions, pollution from tailings will not reach Lake Balkhash during the forecast period. The methods and tools used in this study to enable mining activity without environmental implications for the region can be applied to sites with similar anthropogenic influences worldwide. Full article

This study investigated the distribution of heavy metals in agricultural soils in the vicinity of three large mining landfills of the Kizhnica mine in the Republic of Kosovo. The mining sector is one of the most important sectors of Kosovo’s economic development, and the Kizhnica mine is one of the most important ore producers in Kosovo. Besides the positive aspects, the development of production also has some negative side effects, such as the generation of industrial waste and the possible contamination of surrounding areas, including agricultural land. Therefore, ten sampling sites were selected in the vicinity of the Kizhnica mine. These sites were characterized and assessed as the most important due to the anthropogenic impact of mineral processing and open-tailing waste deposits in Kizhnica. The concentration of Pb, Zn, Cu, As, Cd, Ni, Mn and Sb in the selected samples was determined using inductively coupled plasma–optical emission spectrometry. The data obtained were used to create geochemical maps and calculate the contamination factor, pollution load index and geoaccumulation index. Cluster analysis, Pearson correlation coefficient and air spatial distribution patterns using the air dispersion model were used to evaluate within the area. The results showed that heavy metal levels are influenced by the anthropogenic nature of pollution, confirming a current ecological threat from mining activities in the region. In order to improve waste management, reduce the hazardous impacts of mining and contribute to the sustainable development of the region, the potential reuse of the deposited waste material in the construction industry is proposed. Full article

Exploratory factor analysis (EFA) is a very common tool used in the social sciences to identify the underlying latent structure for a set of observed measurements. A primary component of EFA practice is determining the number of factors to retain, given the sample data. A variety of methods are available for this purpose, including parallel analysis, minimum average partial, and the Chi-square difference test. Research has shown that the presence of outliers among the indicator variables can have a deleterious impact on the performance of these methods for determining the number of factors to retain. The purpose of the current simulation study was to compare the performance of several methods for dealing with outliers combined with multiple techniques for determining the number of factors to retain. Results showed that using correlation matrices produced by either the percentage bend or heavy-tailed Student’s t-distribution, coupled with either parallel analysis or the minimum average partial yield, were most accurate in terms of identifying the number of factors to retain. Implications of these findings for practice are discussed. Full article

Recently, there has been an increased focus on enhancing the accuracy of machine learning techniques. However, there is the possibility to improve it by selecting the optimal tuning parameters, especially when data heterogeneity and multicollinearity exist. Therefore, this study proposed a statistical model to study the importance of changing the crude oil prices in the European Union, in which it should meet state-of-the-art developments on economic, political, environmental, and social challenges. The proposed model is Elastic-net quantile regression, which provides more accurate estimations to tackle multicollinearity, heavy-tailed distributions, heterogeneity, and selecting the most significant variables. The performance has been verified by several statistical criteria. The main findings of numerical simulation and real data application confirm the superiority of the proposed Elastic-net quantile regression at the optimal tuning parameters, as it provided significant information in detecting changes in oil prices. Accordingly, based on the significant selected variables; the exchange rate has the highest influence on oil price changes at high frequencies, followed by retail trade, interest rates, and the consumer price index. The importance of this research is that policymakers take advantage of the vital importance of developing energy policies and decisions in their planning. Full article

An approach to derive the below-bandgap absorption in GaSb/GaAs self-assembled quantum dot devices using room-temperature external quantum efficiency measurement results is presented. Devices with five layers of delta-doped quantum dots placed in the intrinsic, n- and p-regions of a GaAs solar cell are studied. The importance of incorporating an extended Urbach tail absorption in analyzing the absorption strength of quantum dots and the transition states is demonstrated. The theoretically integrated absorbance via quantum dot ground states is calculated as 1.04 × 10¹⁵ cm⁻¹s⁻¹, which is in reasonable agreement with the experimentally derived value 8.1 × 10¹⁵ cm⁻¹s⁻¹. The wetting layer and quantum dot absorption contributions are separated from the tail absorption and their transition energies are calculated. Using these transition energies and the GaAs energy gap of 1.42 eV, the heavy hole confinement energies for the quantum dots (320 meV) and for the wetting layer (120 meV) are estimated. Full article

We define a new family of random geometric graphs which we call random covering graphs and study its statistical properties. To the best of our knowledge, this family of graphs has not been explored in the past. Our experimental results suggest that there are striking deviations in the expected number of edges, degree distribution, spectrum of adjacency/normalized Laplacian matrix associated with the new family of graphs as compared to both the well-known Erdos–Renyi random graphs and the general random geometric graphs as originally defined by Gilbert. Particularly, degree distribution of the graphs shows some interesting features in low dimensions. To the more applied end, we believe that our random graph family might be effective in modelling some practically useful networks (world wide web, social networks, railway or road networks, etc.). It is observed that the degree distribution of some complex networks arising in practice follow power law distribution or log power distribution; they tend to be right skewed, having a heavy tail unlike the degree distribution of Erdos–Renyi graphs or general geometric random graphs (which follow exponential distribution with a sharp tail). The degree distribution of our random graph family significantly deviates from that of Erdos–Renyi graphs or general geometric random graphs and is closer to a right-skewed power law distribution with a heavy tail. Thus, we believe that this new family of graphs might be more effective in modelling the typical real-world networks mentioned above. The key contribution of the paper is introducing this new random graph family and studying some of its properties experimentally, further investigation into which would be interesting from a purely mathematical perspective. Also, it might be of practical interest in terms of modelling real-world networks. Full article

Phytoremediation is a useful, low-cost, and environmentally friendly alternative for the rehabilitation of heavy-metal-contaminated (HM) soils. This technology takes advantage of the ability of certain plant species to accumulate HMs in their tissues. Crotalaria pumila is a herbaceous plant with a wide geographical distribution that grows naturally in environments polluted with HMs. In this work, the bioaccumulation capacity of roots and leaves in relation to five HMs (Cr, Cu, Fe, Pb, and Zn) was evaluated, as well as the morphological changes presented in C. pumila growing in control substrate (without HMs) and mine-tailing substrate (with HMs) under greenhouse conditions for 150 days. Four metals with the following concentration pattern were detected in both tissues and substrates: Fe > Pb > Cu > Zn. Fe, Pb, and Zn concentrations were significantly higher in the roots and leaves of individuals growing on mine-tailing substrate compared to the control substrate. In contrast, Cu concentration increased over time in the exposed individuals. The bioconcentration factor showed a similar pattern in root and leaf: Cu > Fe > Pb > Zn. Around 87.5% of the morphological characters evaluated in this species decreased significantly in individuals exposed to HMs. The bioconcentration factor shows that C. pumila is efficient at absorbing Cu, Fe, and Pb from the mine-tailing substrate, in the root and leaf tissue, and the translocation factor shows its efficiency in translocating Cu from the roots to the leaves. Therefore, C. pumila may be considered as a HM accumulator plant with potential for phytoremediation of polluted soils with Cu, Pb, and Fe, along with the ability to establish itself naturally in contaminated environments, without affecting its germination rates. Also, it exhibits wide geographical distribution, it has a short life cycle, exhibits rapid growth, and can retain the mine-tailing substrate, extracting HMs in a short time. Full article

A single-server queueing system with n classes of customers, stationary superposed input processes, and general class-dependent service times is considered. An exponential splitting is proposed to construct classical regeneration in this (originally non-regenerative) system, provided that the component processes have heavy-tailed interarrival times. In particular, we focus on input processes with Pareto interarrival times. Moreover, an approximating $GI/G/1$-type system is considered, in which the independent identically distributed interarrival times follow the stationary Palm distribution corresponding to the stationary superposed input process. Finally, Monte Carlo and regenerative simulation techniques are applied to estimate and compare the stationary waiting time of a customer in the original and in the approximating systems, as well as to derive additional information on the regeneration cycles’ structure. Full article

The importance of the mining/milling industry in increasing the growth level and welfare of countries is quite high. However, at the end of mining/milling processes, huge amounts of waste (often known as tails) are inevitably produced that have no economic value and can even be considered dangerous due to some heavy metals they contain. These tails are highly problematic due to both their volume (difficult to manage environmentally) and toxicity (potential to cause acid/leach waters) and need to be handled outside of existing disposal methods. This article presents the effective and sustainable handling and application of tails resulting from the enrichment of copper–zinc ores, which are actively engaged in metallic mining activities in the northeast of Türkiye, with the submarine tails disposal (STD) method. In the mining operation under study, some (~55–60 wt.%) of the tails are employed as underground fill, even though the residual part is disposed of by the STD method. The characterization of ore beneficiation tails, their transportation to the subsea via a pipeline system, and discharge monitoring results are detailed in the present investigation. According to the limitations which are indicated by the Turkish Control of Water Contamination regulation, the concentration of Pb-Cu found in the results was under the allowable limit of 0.05 mg/L. The allowed 2 mg/L limit for Zn was not surpassed mainly by the concentration found in the collected samples. pH values were almost above the allowable limit of pH > 5. The results reveal that the STD technique works quite well as an integrated mine tails method in the mine under study. Full article