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The roles played by four major functional groups (amine, carboxyl, azo, hydroxyl groups) in the biomass of castor seeds in adsorption of seven dyes were investigated. These functional groups in castor seeds were chemically modified individually to determine their contribution to the adsorption of ionic dyes. The dyes used were remazol red B, procino yellow, fast green FCF, brilliant cresyl blue, methylene blue, neutral red, red-141. It was found that hydroxyl group inhibited the adsorption of anionic dyes but it was major functional group in the adsorption of cationic dyes, hydroxyl group was important functional group in the adsorption of all seven dyes and the effect of methylation of amino group was not significant on the adsorption of seven dyes.

The synthesis and characterization of four new solid dye complexes, CuL2(L= 2-[2-methoxy-5-(propane-1-sulfonyl)-phenyl azo]-naphthalen-1-ol, 5-{[3-(4,6-dihydroxy-[1,3,5]tri azine-2-ylamino)-phenyl]-hydrazones}-1-ethyl-4-methyl-2,6-dioxo-1,2,5,6-tetrahydro-pyridine-3-carboxylic acid diethylamide, 4-{bis-[4-(benzyl-ethyl-amino)-phenyl]-methyl}-phenol and 7-imino-4-methyl-7H-phenoxazine-1,3-diamine) is reported. The mode for ligand coordination has been determined by IR and EPR spectra. The carboxyl and amino group of dyes coordinates to the Cu(II) atom as a unidentate or as a chelating ligand.

The increasing complexity of modern control systems has emphasized the idea of applying new approaches in order to solve design problems for different control engineering applications. Proportional-Integral-Derivative (PID) control schemes have been widely used in most of process control systems represented by chemical processes for a long time. However, a very important problem is how to determine or tune the PID parameters, because these parameters have a great influence on the stability and the performance of the control system. Computational intelligence (CI), which has caught the eyes of researchers due to its simplicity, low computational cost, and good performance, makes it a possible choice for tuning of PID controllers, to increase their performance. This paper discusses, in detail, the Particle Swarm Optimization (PSO) algorithm, a CI technique, and its implementation in PID tuning for a controller of a real time process. Compared to other conventional PID tuning methods, the result shows that better performance can be achieved with the proposed method. The ability of the designed controller, in terms of tracking set point, is also compared and simulation results are shown.

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