搜索结果：Ecotoxicology

We present a novel approach to ecological risk assessment by recasting the Species Sensitivity Distribution (SSD) method within a Bayesian nonparametric (BNP) framework. Widely mandated by environmental regulatory bodies globally, SSD has faced criticism due to its historical reliance on parametric assumptions when modeling species variability. By adopting nonparametric mixture models, we address this limitation, establishing a statistically robust foundation for SSD. Our BNP approach offers several advantages, including its efficacy in handling small datasets or censored data, which are common in ecological risk assessment, and its ability to provide principled uncertainty quantification alongside simultaneous density estimation and clustering. We utilize a specific nonparametric prior as the mixing measure, chosen for its robust clustering properties, a crucial consideration given the lack of strong prior beliefs about the number of components. Through simulation studies and analysis of real datasets, we demonstrate the superiority of our BNP-SSD over classical SSD methods. We also provide a BNP-SSD Shiny application, making our methodology available to the Ecotoxicology communit

The widespread presence of synthetic progestins, such as levonorgestrel (LNG) and gestodene (GES), in aquatic environments poses significant ecotoxicological risks due to their endocrine-disrupting properties. In this study, nano-octahedral magnetite (Fe3O4-NO) was synthesized via a hydrothermal route and incorporated into gas diffusion electrodes (GDEs) supported on Vulcan XC72 to enhance the in-situ electrogeneration of hydrogen peroxide (H2O2). High-resolution transmission electron microscopy, X-ray diffraction, SEM, X-ray photoelectron spectroscopy, and contact angle measurements thoroughly characterized the physicochemical and morphological properties of the materials. The 3% Fe3O4-NO/C catalyst provided a two-fold increase in H2O2 selectivity compared with Vulcan XC72. Electrochemical performance was optimized using a 2^3 factorial design and principal component analysis (PCA), with current density, pH, and Na2SO4 concentration as variables. The optimized GDE (3% Fe3O4-NO/C) achieved a maximum H2O2 production of 0.44 +/- 0.02 g L-1 with a current efficiency of 43.1 +/- 0.23% and a specific energy consumption of 0.012 +/- 0.009 kWh g-1. The electrode was further applied to the

The need for effective biomonitoring in wastewater has become clear due to the impracticality of continuously tracking all chemicals and emerging contaminants in the aquatic exposome. Effect-based biomonitoring provides a cost-effective solution. The ToxMate device, which uses videotracking of locomotor behavior in aquatic invertebrates, has proven efficient for real-time detection of micropollutant surges in effluents. To extend the approach, this proof-of-concept study evaluates the potential to formalize behavioral fingerprints from real-time videotracking data to characterize qualitative variations in effluent contamination. We present the first application of a functional data analysis (FDA) framework in ecotoxicology. Data were obtained by simultaneously tracking three sentinel organisms from distinct taxa (a crustacean, an annelid, and a gastropod) during pulse exposures to four chemicals in the laboratory (two metals, one pharmaceutical, and one insecticide). Individual and multispecies responses were analy-zed to determine whether combining species enhances the resolution of contamination fingerprints through multidimensional FDA. Applying the same data-driven approach to

Although hydrogen generation by water electrolysis is the cheapest of all other available sources, water splitting still occurs with sluggish kinetics. It is a challenging barrier for H2 production on a large scale. Moreover, research is still underway to understand the oxygen evolution reaction (OER) and design the catalysts with improved OER performance. Herein, we report the synthesis, characterization, and OER performance of iron-doped copper oxide (CuO) as low-cost catalysts for water oxidation. The OER occurs at about 1.49 V versus the RHE with a Tafel slope of 69 mV/dec in a 1 M KOH solution. The overpotential of 338 mV at 10 mA/cm2 is among the lowest compared with other copper-based materials. The catalyst can deliver a stable current density of >10 mA/cm2 for more than 10 hours. Additionally, wastewater treatment, particularly synthetic dye wastewater, is vital for preventing water scarcity and adverse effects on human health and ecotoxicology. The as-synthesized catalysts are also utilized for Fenton-like photo-degradation under low-power visible household LED lights toward the most commonly industrially used simulated Methylene blue dye wastewater. Almost complete de

Each year, the production of synthetic dye wastewater reaches a trillion tons, posing a significant challenge to addressing water scarcity on a global level. Hence, the treatment of wastewater to prevent water scarcity is of prime importance, and failing to do so will increase ecotoxicological risks and human health. Textile wastewater contains harmful dye. Photocatalytic degradation of such dye-contaminated wastewater is crucial to purifying the dye-contaminated water. However, this process takes time, uses high-power lamps, and is expensive. Here, we report the effect of the concentration of precursor on the size and surface morphology of TiO2 nanostructures prepared by facile hydrothermal synthesis and its ability to perform as a photocatalyst to degrade the most common industrial textile dye, methylene blue (MB), under natural sunlight. The impact of particle size on the photocatalytic activity and photocarrier migration rate was thoroughly examined. Also, the effect of pH on adsorption and photocatalytic degradation has been evaluated in detail. With several optimized conditions, almost complete dye degradation was achieved within 40 minutes under the direct illumination of na

The zymase activity of the yeast Saccharomyces Cerevisiae is sensitive to environmental parameters and is therefore used as a microbiological sensor for water quality assessment, ecotoxicological characterization or environmental monitoring. Comparing to bacterial bioluminescence approach, this method has no toxicity, excludes usage of genetically modified microorganisms, and enables low-cost express analysis. This work focuses on measuring the yeast fermentation dynamics based on multichannel pressure sensing and electrochemical impedance spectroscopy (EIS). Measurement results are compared with each other in terms of accuracy, reproducibility and ease of use in the field conditions. It has been shown that EIS provides more information about ionic dynamics of metabolic processes and requires less complex measurements. The conducted experiments demonstrated the sensitivity of this approach for assessing biophotonic phenomena, non-chemical water treatments and impact of environmental stressors.

1. Behavioral analysis based on video recording is becoming increasingly popular within research fields such as; ecology, medicine, ecotoxicology, and toxicology. However, the programs available to analyze the data, which are; free of cost, user-friendly, versatile, robust, fast and provide reliable statistics for different organisms (invertebrates, vertebrates and mammals) are significantly limited. 2. We present an automated open-source executable software (ToxTrac) for image-based tracking that can simultaneously handle several organisms monitored in a laboratory environment. We compare the performance of ToxTrac with current accessible programs on the web. 3. The main advantages of ToxTrac are: i) no specific knowledge of the geometry of the tracked bodies is needed; ii) processing speed, ToxTrac can operate at a rate >25 frames per second in HD videos using modern desktop computers; iii) simultaneous tracking of multiple organisms in multiple arenas; iv) integrated distortion correction and camera calibration; v) robust against false positives; vi) preservation of individual identification if crossing occurs; vii) useful statistics and heat maps in real scale are exported i

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We introduce a dependent Bayesian nonparametric model for the probabilistic modeling of membership of subgroups in a community based on partially replicated data. The focus here is on species-by-site data, i.e. community data where observations at different sites are classified in distinct species. Our aim is to study the impact of additional covariates, for instance environmental variables, on the data structure, and in particular on the community diversity. To that purpose, we introduce dependence a priori across the covariates, and show that it improves posterior inference. We use a dependent version of the Griffiths-Engen-McCloskey distribution defined via the stick-breaking construction. This distribution is obtained by transforming a Gaussian process whose covariance function controls the desired dependence. The resulting posterior distribution is sampled by Markov chain Monte Carlo. We illustrate the application of our model to a soil microbial dataset acquired across a hydrocarbon contamination gradient at the site of a fuel spill in Antarctica. This method allows for inference on a number of quantities of interest in ecotoxicology, such as diversity or effective concentrat

A mathematician working at Anthropic says he used the AI model Claude Fable 5 to uncover a remarkably simple counterexample to the Jacobian conjecture, a famous problem that has resisted mathematicians for more than a century。 The result shows that the conjecture is false in three dimensions and above, although the original two-dimensional version

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