Simultaneous biodegradation of polycyclic aromatic hydrocarbons and phthalates by bacterial consortium and its bioremediation for complex polluted soil and sewage sludge

Bioresource Technology, Journal Year: 2024, Volume and Issue: 408, P. 131161 - 131161

Published: July 26, 2024

Language: Английский

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Real-time and specific monitoring of nitric oxide and evaluating of the oxidative stress in living cells and zebrafish under the pollutant exposure using a carbon dot-based composite fluorescent probe

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 472, P. 134558 - 134558

Published: May 8, 2024

Language: Английский

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Identification of the associations between co-exposure to organophosphate flame retardants and thyroid dysfunction and exposure risk factors in residents of Shanghai, China

Environmental Pollution, Journal Year: 2025, Volume and Issue: unknown, P. 125911 - 125911

Published: Feb. 1, 2025

Language: Английский

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Machine Learning in Reducing E-Waste

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 105 - 126

Published: Feb. 27, 2025

E-waste is a waste which gathered from various sources, Household sector considered as biggest source of generation e-waste. consists components characterized hazardous and non-hazardous also contain approximately 1000 substances categorized in this category. comprising ferrous non-ferrous metals ceramics other items. When e-waste gets dismantled continuously processed it jeopardizes the health environment, surroundings. composition bio accumulative toxic containing like chromium, mercury, (Arora et al., 2024). Machine learning plays very important role regulating In context to urban segments, week by calculated through building prescient model, creating gradient boosting regression tree (GBRT) neutral network machine calculations. By incorporating learning, calculations will provide exact accurateness algorithm. A convolutional neural was created bifurcate into different countries. These categories are follows: cell phone, remote controller, battery, light bulb.

Language: Английский

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Explainable no-code OECD-compliant machine learning models to predict the mutagenic activity of polycyclic aromatic hydrocarbons and their radical cation metabolites

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 972, P. 179133 - 179133

Published: March 18, 2025

Language: Английский

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Integrated machine learning and density functional theory to reveal the relationship between water contaminants and singlet oxygen via persulfate activation

Applied Catalysis B Environment and Energy, Journal Year: 2025, Volume and Issue: unknown, P. 125322 - 125322

Published: March 1, 2025

Language: Английский

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Dialogue between algorithms and soil: Machine learning unravels the mystery of phthalates pollution in soil

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 482, P. 136604 - 136604

Published: Nov. 20, 2024

Language: Английский

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Exposure to per- and polyfluoroalkyl substances, neonicotinoid insecticides, benzotriazoles and benzothiazoles: Associations with human non-alcoholic fatty liver disease

Environmental Chemistry and Ecotoxicology, Journal Year: 2024, Volume and Issue: 6, P. 283 - 292

Published: Jan. 1, 2024

Evidence of the joint association between exposure to multiple environmental chemicals and non-alcoholic fatty liver disease (NAFLD) is scarce. In this study, 281 participants from Zhuhai, China (138 patients with NAFLD vs. 143 healthy participants) were recruited explore associations 40 per- polyfluoroalkyl substances (PFAS), 11 neonicotinoid insecticides (NEOs), 8 benzotriazoles (BTRs) benzothiazoles (BTHs) risk NAFLD. Perfluorooctane sulfonate (PFOS) its emerging alternatives (6:2 chlorinated polyfluorinated ether [6:2 Cl-PFESA] 8:2 fluorotelomer sulfonic acid [8:2 FTSA]), NEO metabolites (m-NEOs), BTR, BTH predominant PFAS, NEOs, BTRs BTHs, respectively. The total median concentrations PFAS (20.4 ng/mL 7.16 ng/mL) NEOs (7.24 6.23 in group significantly higher than those group. Sex differences have been observed among FTSA short-chain more female NAFLD, whereas other (i.e., 6:2 Cl-PFESA) legacy PFOS long-chain perfluoroalkyl carboxylic acids) easily accumulated male results linear regression analysis indicated a significant positive alanine transaminase (ALT) serum samples (β = 23.2, 95% confidence intervals (CI): 7.82, 38.5). Conversely, negative correlations 5-hydroxy-imidacloprid (5-OH-IMI) γ-glutamyl transpeptidase (GGT) −2.73, CI: −5.29, −0.18), as well tolyltriazole (TTR) bilirubin (TBIL) −0.70, −1.33, −0.08) direct (DBIL) −0.59, −0.98, −0.20). Bayesian kernel machine model revealed effect on elevated outcomes, suggesting that might exacerbate severity This study fills knowledge gap multi-pollutant risk.

Language: Английский

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Developing Industry 4.0-based e-waste management: a decision-aided tool equipped with continuous function-valued intuitionistic fuzzy sets

International Journal of Environmental Science and Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 26, 2024

Language: Английский

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Evidence that cadmium aggravate the toxicity of triphenyl phosphate in aquatic sediments to Corbicula fluminea

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 480, P. 136407 - 136407

Published: Nov. 4, 2024

Language: Английский

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