Browsing by Author "Messaoudi, Mohammed"

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    Impact of gamma irradiation on phytochemical composition, and biological activities of Lepidium sativum seeds extract
    (Walter de Gruyter GmbH, 2024) Hadj Rabia, Samia; Debib, Aicha; Eddaikra, Atika; Aberkane-Mchebbek, Lila; Nouri, Ramy; Benmoussa, Fatima; Mokhtari, Amine; Medjber, Sarah; Mansouri, Belkacem; Messaoudi, Mohammed
    The main objective of this research is to assess how gamma radiation influences the chemical composition and activities such as antioxidant, antimicrobial and anticancer activities of Lepidium sativum (L. sativum) seeds. Methanolic extracts were obtained through a 24 h maceration process from L. sativum seeds exposed to various doses of gamma irradiation. Phytochemical screening involved precipitation and staining reactions, with the antioxidant potential assessed using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. Antimicrobial activity was evaluated through a diffusion test on agar medium, while the cytotoxic potential on the lung cancer line “A-549 cells” was examined using the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay. Qualitative analysis of the extracts identified preserved bioactive constituents after irradiation. Additionally, quantitative analysis indicated a significant rise in the total content of polyphenols and flavonoids under radiation, accompanied by an enhanced reducing power compared to the control. The antimicrobial and cytotoxic capabilities also improved, evident in increased growth inhibition zones for certain microbial strains and reduced viability rates of A549 cells. These results show promise and warrant further investigation into the potential of gamma radiation to enhance additional biological effects of plants.
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    Just suspended speed simulation in torus reactor using multiple Non-Linear regression model
    (MDPI, 2023) Sayah, Houssem Eddine; Alouache, Ali; Annad, Mohamed; Lefkir, Abdelouahab; Nouri, L’hadi; Selatnia, Ammar; Messaoudi, Mohammed
    In the chemical and water treatment industries, it is necessary to achieve maximum contact between the solid and liquid phase, thus promoting the mass and heat transfer, to obtain a homogeneous solution. Increasing stirring speed is the most recommended solution in different types of reactors: stirred tank, column, and tubular. However, this inadvertently increases the energy consumption of the industry. Determination of the minimum speed, labeled the just suspended speed (Njs) and crucial to attaining homogeneity, has been widely investigated. Numerous studies have been carried out to assess formulas for determining the solid particle speed in various reactor types. Given the limitations of the existing formulations based on a generalization of a unique equation for computing Njs for all soil classifications, it appears that most formulas can only approximate complex phenomena that depend on several parameters. A novel formula was developed, and the results given in this paper demonstrate the effectiveness of generating significant uncertainties for the estimation of Njs. The purpose of this study was the elaboration of experiment-based data-driven formulas to calculate Njs for different particle size classes. Nonlinear multiple regression (MNLR) models were used to generate the new formulas. The gradient descent optimization algorithm was employed to solve the hyperparameters of each novel equation, utilizing supervised learning. A comparison of the data indicated that the unique formulas presented in this study outperformed empirical formulas and provide a useful means for lowering energy consumption, while increasing the heat and mass transfer in torus type reactors