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  • Open Access

    REVIEW

    Climate Change and Aquatic Phytoremediation of Contaminants: Exploring the Future of Contaminant Removal

    Marcelo Pedrosa Gomes*

    Phyton-International Journal of Experimental Botany, Vol.93, No.9, pp. 2127-2147, 2024, DOI:10.32604/phyton.2024.056360 - 30 September 2024

    Abstract Climate change, driven by anthropogenic activities, profoundly impacts ecosystems worldwide, particularly aquatic environments. This review explores the multifaceted effects of climate change on the phytoremediation capabilities of aquatic plants, focusing on the physiological responses to key environmental factors such as temperature, carbone dioxide (CO2) and ozone (O3) levels, pH, salinity, and light intensity. As global temperatures rise, moderate increases can enhance photosynthesis and biomass production, boosting the plants’ ability to absorb and detoxify contaminants, such as metals, pharmaceuticals, and nutrients. However, extreme temperatures and salinity levels impose stress, disrupting metabolic processes and reducing phytoremediation efficiency. Elevated CO2More >

  • Open Access

    ARTICLE

    Ozone Depletion Identification in Stratosphere Through Faster Region-Based Convolutional Neural Network

    Bakhtawar Aslam1, Ziyad Awadh Alrowaili2, Bushra Khaliq1, Jaweria Manzoor1, Saira Raqeeb1, Fahad Ahmad3,*

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2159-2178, 2021, DOI:10.32604/cmc.2021.015922 - 13 April 2021

    Abstract The concept of classification through deep learning is to build a model that skillfully separates closely-related images dataset into different classes because of diminutive but continuous variations that took place in physical systems over time and effect substantially. This study has made ozone depletion identification through classification using Faster Region-Based Convolutional Neural Network (F-RCNN). The main advantage of F-RCNN is to accumulate the bounding boxes on images to differentiate the depleted and non-depleted regions. Furthermore, image classification’s primary goal is to accurately predict each minutely varied case’s targeted classes in the dataset based on ozone… More >

  • Open Access

    ARTICLE

    Synthesis of Resins with Ozonized Sunfl ower Oil and Radiata Pine Tannins

    M.Thébault*, A.Pizzi, E.Fredon

    Journal of Renewable Materials, Vol.1, No.4, pp. 242-252, 2013, DOI:10.7569/JRM.2013.634121

    Abstract Sunfl ower oil was subjected to a fl ow of compressed air containing ozone for different time periods. The addition of α-D-Glucose was used to increase the aldehyde content by reduction of the intermediate ozonides of the ozonation reaction. These new oils were analyzed by FTIR and GC-MS spectrometry, and their relative aldehyde groups content measured by the Henick method. They were then mixed with an aqueous solution of Radiata Pine tannin to form resins, subsequently analyzed by 13C NMR and MALDITOF mass spectrometry. Wood particleboards were then made using some of these resins as the More >

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