Search Results (185)

The waste generated during metal mining activities contains mixtures of heavy metals (HM) that are not biodegradable and can accumulate in the surrounding biota, increasing risk to human and environmental health. Plant species with the capacity to grow and develop on mine tailings can be used as a model system in phytoremediation studies. Dodonaea viscosa (L.) Jacq. is a shrub with wide geographical distribution and the ability to establish itself in mine tailings. The Sierra de Huautla Biosphere Reserve in Mexico contains a metallurgic district where mining activities have generated 780 million kg of waste with large concentrations of toxic heavy metals, mainly cadmium and lead. The present study evaluated the phytoremediation potential of D. viscosa in in situ conditions on soils contaminated with HMs (exposed) and reference sites (non-exposed) for one year. Also, the effects of cadmium (Cd) and lead (Pb) exposure in D. viscosa were analyzed via DNA damage (comet assay) morphological and physiological characters in exposed vs non-exposed individuals. The concentration of Cd and Pb was measured through atomic absorption spectrophotometry in the roots and leaves of plants. In total, 120 D. viscosa individuals were established, 60 growing in exposed and 60 in non-exposed soils. Exposed individuals of D. viscosa hyperaccumulated Cd and Pb in roots and leaves. At the end of the experiment, eight out of twelve characters under evaluation decreased significantly in HM-exposed plants in relation to individuals growing in non-exposed soils, except for stomatal index, stomatal coverage, and fresh leaf biomass. The micro-morphological and physiological traits of D. viscosa were not influenced by Cd and Pb bioaccumulation. In contrast, the bioaccumulation of Cd and Pb significantly influenced the macro-morphological characters and genetic damage; this last biomarker was 3.2 times higher in plants growing in exposed sites. The bioconcentration factor (BCF) of Cd and Pb in root and leaf tissue increased significantly over time. The mean BCF in root and leaf tissue was higher for Pb (877.58 and 798.77) than for Cd (50.86 and 23.02). After 12 months of exposure, D. viscosa individuals growing on mine tailing substrate showed that the total HM phytoextraction capacity was 7.56 kg∙ha⁻¹ for Pb and 0.307 kg∙ha⁻¹ for Cd. D. viscosa shows potential for phytoremediation of soils contaminated with Cd and Pb, given its capacity for establishing and developing naturally in contaminated soils with HM. Along with its bioaccumulation, biomass production, abundance, and high levels of bioconcentration factors, but without affecting plant development and not registering associated herbivores, it may incorporate HM into the trophic chain. Full article

We introduce a new identification strategy for uncertainty shocks to explain macroeconomic volatility in financial markets. The Chicago Board Options Exchange Volatility Index (VIX) measures the market expectations of future volatility, but traditional methods based on second-moment shocks and the time-varying volatility of the VIX often do not effectively to capture the non-Gaussian, heavy-tailed nature of asset returns. To address this, we constructed a revised VIX by fitting a double-subordinated Normal Inverse Gaussian Lévy process to S&P 500 log returns, to provide a more comprehensive measure of volatility that captures the extreme movements and heavy tails observed in financial data. Using an axiomatic framework, we developed a family of risk–reward ratios that, when computed with our revised VIX and fitted to a long-memory time series model, provide a more precise identification of uncertainty shocks in financial markets. Full article

This study is based on the stock returns of 11 subindustry markets in the international clean energy market from 2010 to 2024 and constructs a skewed t distribution dynamic factor copula model. The time-varying load factor is used to characterize the correlation between a single subindustry market and the entire system, and the joint probability of distress is calculated as a measure of the overall level of systemic risk. Two indicators, Systemic Vulnerability Degree and Systemic Importance Degree, are introduced to evaluate the vulnerability of a single subindustry market in systemic risk and its contribution to systemic risk. A conditional risk-spillover index is constructed to measure the risk-spillover level between subindustry markets. This method fully considers the individual differences and inherent correlations of the international clean energy market subsectors, as well as the fat tail and asymmetry of returns, thus capturing more information and more timely information. This study found that the correlation between subindustry markets changes over time, and during the crisis, the market correlation shows a significant upward trend. In the measurement of the overall level of systemic risk, the joint probability of distress can identify the changes in systemic risk in the international clean energy market. The systemic risk of the international clean energy market presents the characteristics of rapid and multiple outbreaks, and the joint default risk probability of the whole system can exceed 0.6. The outbreak of systemic risk is closely related to a series of major international events, showing a strong correlation. In addition, the systemic vulnerability analysis found that the biofuel market has the lowest systemic vulnerability, and the advanced materials market has the highest vulnerability. The energy efficiency market is considered to be the most important market in the system. The advanced materials market and renewable energy market play a dominant role in the risk contribution to other markets, while the geothermal market, solar market, and wind energy market are net risk overflow parties in the tail risk impact, and the developer market and fuel cell market are net risk receivers. This study provides a theoretical basis for systemic risk management and ensuring the stability of the international clean energy market. Full article

Plain or crude Monte Carlo simulation (CMC) is commonly applied for estimating multi-period tail risk measures such as value-at-risk (VaR) and expected shortfall (ES). After fitting a volatility model to the past history of returns and estimating the conditional distribution of innovations, one can simulate the return process following the fitted volatility model with the estimated conditional distribution of innovations. Repeated generation of the return processes with the desired length gives a sufficient number of simulated multi-period returns. Then, the multi-period VaR and ES are directly estimated from the empirical distribution of them. CMC is easily applicable. However, it needs to generate a huge number of multi-period returns for the accurate estimation of a tail risk measure, especially when the confidence level of the measure is close to 1. To overcome this shortcoming, we propose a sequential importance sampling, which is a modification of CMC. In the proposed method. The sampling distribution of innovations is chosen differently from the estimated conditional distribution of innovations so that the simulated multi-period losses are more severe than in the case of CMC. In other words, the simulated losses over the VaR that is wanted to estimate are common in the proposed method, which reduces very much the estimation error of ES, and requires the less simulated samples. We propose how to find the near optimal sampling distribution. The multi-period VaR and ES are estimated from the weighted empirical distribution of the simulated multi-period returns. We propose how to compute the weight of a simulated multi-period return. An empirical study is given to backtest the estimated VaRs and ESs by the proposed method, and to compare the performance of the proposed sequential importance sampling with CMC. Full article

Microplastic pollution is a global concern arising from the extensive production and use of plastics. The prevalence of microplastics (MPs) in the environment is escalating due in large part to the excessive use of plastics in various human-related activities. Consequently, animals are being exposed to MPs through dietary intake, which poses significant health risks to the wild populations. The objective of the study was to assess the concentration of MPs in the feces of wild long-tailed macaques (Macaca fascicularis) in the Kosumpee Forest Park (KFP) located in Northeast Thailand. KFP is situated in close proximity to the town of Kosum Phisai and experiences considerable human–primate interaction. Fresh fecal drops from 50 adult macaques were collected and sampled. MP presence in the feces was measured using density separation through visual identification under a stereomicroscope. We found a total of 396 MP particles in the feces with an average of 7.9 particles/macaque. Two forms of MPs were found in the macaques’ feces including fibers (391 pieces; 98.73%) and asymmetric fragments (5 pieces; 1.27%), with sizes mostly ranging under 1000 µm. The most observed color of MPs was blue (152 pieces; 38.48%). This study highlights the impact of anthropogenic waste and the potential health problems that can be caused to wild animals via microplastic pollution. The results contribute to the ongoing discussions on environmental health within the One Health framework. Full article

A detailed analysis of the accident that occurred at the flotation tailings storage facility (TSF) at the inactive mine “Stolice” in 2014 is provided in this paper. All factors that caused the accident have been analyzed, with a review of the consequences of the accident, their accident class according to the Global Industry Standard on Tailings (GISTM), and the implemented measures to rehabilitate the TSF and the surrounding area after the accident. It has been concluded that the TSF had not been properly maintained even before the accident occurred and that the unfavorable weather conditions in Serbia in the May of that year contributed to the filtration disturbance and multiple tailings spillages from the TSF. It has been stated that the consequences according to the GISTM span from “low” to “significant”, with the group of environmental consequences having the highest rank (3). Although the accident occurred without recorded human casualties, with the damage being of a local nature, it is considered one of the most significant accidents at a TSF in Serbia in the last 20 years. The reconstructed TSF is considered stable now, with a low-to-medium risk of failure. Full article

This study introduces a novel approach to estimate tail dependence in financial contagion using mixture copulas. Addressing the challenges of weight parameter estimation in conventional models, we propose a Bayesian model averaging method to determine optimal copula weights. Through both simulations and empirical studies, the proposed method demonstrates improved robustness and accuracy, particularly when handling extreme weight scenarios. These advancements offer more reliable measurements of financial contagion, contributing to enhanced risk management and policy-making in interconnected financial markets. Full article

Recent trends in portfolio management emphasize the importance of reducing carbon footprints and aligning investments with sustainable practices. This paper introduces Sensitivity Value-at-Risk (SensitivityVaR), an advanced distortion risk measure that combines Value-at-Risk (VaR) and Expected Shortfall (ES) with the Cornish–Fisher expansion. SensitivityVaR provides a more robust framework for managing risk, particularly under extreme market conditions. By incorporating first- and second-order distorted stochastic dominance criteria, we enhance portfolio decarbonization strategies, aligning financial objectives with environmental targets such as the Paris Agreement’s goal of a 7% annual reduction in carbon intensity from 2019 to 2050. Our empirical analysis evaluates the impact of integrating carbon intensity data—including Scope 1, Scope 2, and Scope 3 emissions—on portfolio optimization, focusing on key sectors like technology, energy, and consumer goods. The results demonstrate the effectiveness of SensitivityVaR in managing both risk and environmental impact. The methodology led to significant reductions in carbon intensity across different portfolio configurations, while preserving competitive risk-adjusted returns. By optimizing tail risks and limiting exposure to carbon-intensive assets, this approach produced more balanced and efficient portfolios that aligned with both financial and sustainability goals. These findings offer valuable insights for institutional investors and asset managers aiming to integrate climate considerations into their investment strategies without compromising financial performance. Full article

Geckos are renowned for their exceptional climbing abilities, enabled by their specialized feet with hairy toes that attach to surfaces using van der Waals forces. Inspired by these capabilities, various gecko-like robots have been developed for high-risk applications, such as search and rescue. While most research has focused on adhesion mechanisms, the gecko’s tail also plays a critical role in maintaining balance and stability. In this study, we systematically explore the impact of tail dynamics on the climbing performance of gecko-inspired robots through both simulation and experimental analysis. We developed a dynamic climbing simulation system that models the robot’s specialized attachment devices and predicts contact failures. Additionally, an adjustable-angle force measurement platform was constructed to validate the simulation results. Our findings reveal the significant influence of the tail on the robot’s balance, stability, and maneuverability, providing insights for further optimizing climbing robot performance. Full article

The main aim of this paper is to consider a new risk metric that permits taking into account the spatial interactions of data. The considered risk metric explores the spatial tail-expectation of the data. Indeed, it is obtained by combining the ideas of expected shortfall regression with an expectile risk model. A spatio-functional Nadaraya–Watson estimator of the studied metric risk is constructed. The main asymptotic results of this work are the establishment of almost complete convergence under a mixed spatial structure. The claimed asymptotic result is obtained under standard assumptions covering the double functionality of the model as well as the data. The impact of the spatial interaction of the data in the proposed risk metric is evaluated using simulated data. A real experiment was conducted to measure the feasibility of the Spatio-Functional Expectile Shortfall Regression (SFESR) in practice. Full article

To investigate the mechanism of polypropylene fiber (PPF) on the rheological and thixotropic properties of cemented paste backfill containing mineral admixtures, the concept of water film thickness (WFT) was introduced. The packing density of the tailings-binder-PPF (TBP) system was measured in dry and wet conditions and the WFT was calculated accordingly. Additionally, the rheological parameters (yield stress, thixotropy, etc.) of the fiber-reinforced cemented paste backfill (FRCPB) were quantified. The results demonstrate that the wet packing test is a more appropriate method for measuring the packing density of the TBP system. The PPF length has a slight adverse effect on the packing density, and the packing density initially increases and then decreases with the PPF content. The reasons can be attributed to the filling effect and wedge effect of the fibers, respectively. In addition to the packing density, the thixotropy of FRCPB is also affected by the interaction of fibers. WFT is a crucial factor affecting the yield stress of FRCPB, with which it exhibits a strong linear relationship. The study identified that the optimum PPF content for enhancing the rheological and thixotropic properties of CPB is 0.2%, with a fiber length of 9 mm, balancing flowability and stability for practical application in mining backfill operations. These insights can guide the optimization of CPB mixtures, enhancing their flowability and stability during placement in mined-out spaces. By improving the fill quality and reducing the risk of blockage during backfill operations, the results offer practical benefits in increasing the safety and efficiency of underground mining activities. Full article

Based on the typical positions of S&P 500 option market makers, we derive a funding illiquidity measure from quoted prices of S&P 500 derivatives. Our measure significantly affects the returns of leveraged managed portfolios; hedge funds with negative exposure to changes in funding illiquidity earn high returns in normal times and low returns in crisis periods when funding liquidity deteriorates. The results are not driven by existing measures of funding illiquidity, market illiquidity, and proxies for tail risk. Our funding illiquidity measure also affects leveraged closed-end mutual funds and, to an extent, asset classes where leveraged investors are marginal investors. Full article

Using daily returns of Bitcoin, Litecoin, Ripple and Stellar, we introduce a novel risk measure for quantitative-risk management in the cryptomarket that accounts for the significant co-movements between cryptocurrencies. We find that our model has a lower error margin when forecasting the extent of future losses than traditional risk measures, such as Value-at-Risk and Expected Shortfall. Most notably, we observe this in Litecoin’s results, where Expected Shortfall, on average, overestimates the potential fall in the price of Litecoin by 8.61% and underestimates it by 3.92% more than our model. This research shows that traditional risk measures, while not necessarily inappropriate, are imperfect and incomplete representations of risk when it comes to the cryptomarket. Our model provides a suitable alternative for risk managers, who prioritize lower error margins over failure rates, and highlights the value in exploring how risk measures that incorporate the unique characteristics of cryptocurrencies can be used to supplement and complement traditional risk measures. Full article

During dental scaling in dogs under general anaesthesia, contamination of the peripheral intravenous catheter (PIVC) is unavoidable due to splatter and the generated aerosol. Bacterial contamination was compared between two commonly used PIVC placement sites. Thirty-nine client-owned dogs with a minimum length from their nose to their tail base of 50 cm were randomly assigned to receive a PIVC in either their cephalic or saphenous vein. Irrespective of the PIVC placement site, brain heart infusion agar dishes were placed in the cephalic and saphenous vein areas. Their lids were closed 0, 5, and 10 min into the procedure. Contamination was measured by counting the colony-forming units after incubation on different substrates. The data were analysed with descriptive statistics, ANOVA, and ANCOVA (p < 0.05). The cephalic vein area showed a significantly higher bacterial load than the saphenous vein area (p ≈ 0.0) regardless of the length of the dog. Furthermore, the dorsal PIVC injection ports were sampled before and after scaling, and the colonies isolated were counted and subjected to MALDI-TOF-MS for identification. The bacteria mainly belonged to the genera Staphylococcus, Neisseria, and Bacillus. Our results suggest that for dental scaling in dogs, the PIVC should be placed in the pelvic limb whenever possible to reduce the potential risk of contamination. Full article

The large lateral displacement of tail ropes increases the risk of their wear and fracture, posing hidden dangers to the safety of the hoisting system. However, no suitable method is available to recognize the lateral swing of tail ropes online. A target-free visual measurement method, which includes the dual-branch SiamSeg, was proposed in this study. Considering the slender characteristics of tail ropes, the receptive field of the feature extraction network was enhanced via the Receptive Field Module (RFM), thereby strengthening the discriminability and integrity of tail rope features. The consistency loss constraints were added to the segmentation loss function to maximize the time sequence information of the video and further improve the accuracy of pixel-level displacement. Compared with other methods, the proposed approach achieved better segmentation effects. Comparison results synchronously measured by sensors revealed the effectiveness of this method and its potential for practical underground applications. Full article