The predictability of the adsorption capacity of the multicomponent adsorption system was modelled using Support Vector Machine (SVM). Two SVM models were built and compared. In the first model, the SVM method was used with an already built-in optimisation algorithm. However, in the second model, the SVM method was used by means of a very recent and efficient optimisation algorithm: the Dragonfly Algorithm (DA). The models' accuracy was evaluated by three well-established statistical metrics (root mean squared error RMSE, determination coefficient R 2 , and correlation coefficient R). The used data were collected from previous experimental papers published in literature containing all kinds of pollutants, such as heavy metal ions, dyes, and organic compounds, and different natural/ synthetic adsorbents. The dataset contained five important variables with 1023 points; the variables were divided into four inputs (molecular weight, equilibrium concentrations of adsorbate, specific area of adsorbent, and temperature), and one output (adsorption capacity at equilibrium). The data were divided using the holdout function into two subsets (80 % for training set, and 20 % for test set). The programming stage was carried out using MATLAB software. The results showed that the optimised DA-SVM model with RBF-Gaussian kernel function had good ability for global search combined with high prediction accuracy, with R 2 = 0.997, R = 0.998, and RMSE = 2.539. The obtained model can be used to predict the efficiency of the adsorption system, and provides a tool for process optimisation responding to changes in operating conditions. A new graphical user interface (GUI) was developed with MATLAB GUI to estimate accurately the desired responses by using the best DA-SVM model.
The aim of this study was to prepare microcapsules based on a natural polymer chitosan solution (high degree of deacetylation (DDA), low molecular weight (MW), and low viscosity)/sodium alginate in the presence of a crosslinking agent (glutaraldehyde), in order to encapsulate and vectorise the active principle towards the diseased organ (colon), without being diffused into other levels of the digestive tract, to increase the therapeutic effectiveness of treatment by chemotherapy and to reduce undesirable effects. The method of preparation of the microcapsules obtained from the sodium alginate/chitosan solution/active ingredients system was examined by conventional optical microscopy. In addition, an in vitro study was carried out on the active ingredients’ release profiles, depending on the pH simulating the gastric and intestinal media for the seven systems proposed. It should be mentioned that, in the basic medium (pH(colon) = 8), the release of the active ingredients is of the utmost importance. Nevertheless, control of this release can be improved by a crosslinking agent and the coating method. The dry [sodium alginate / chitosan solution / active ingredients + crosslinking 2 %] formulation coated with non-crosslinked chitosan (Formulation 7) is the standard formula that meets all the criteria from our earlier work, with a core release rate of 67 %. The PSD was unimodal, with sizes ranging from 750 µm to 900 µm.
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