Application of principal component-artificial neural network models for simultaneous determination of phenolic compounds by a kinetic spectrophotometric method

A multicomponent analysis method based on principal component analysis-artificial neural network models (PC-ANN) is proposed for the determination of phenolic compounds. The method relies on the oxidative coupling of phenols (phenol, 2 chlorophenol, 3-chlorophenol and 4-chlorophenol) to N,N-diethyl-p-phenylenediamine in the presence of hexacyanoferrate(III). The reaction monitored at analytical wavelength 680 nm of the dye formed. Phenols can be determined individually over the concentration range 0.1-7.0 microg ml(-1). Differences in the kinetic behavior of the four species were exploited by using PC-ANN, to resolve mixtures of phenol. After reducing the number of kinetic data using principal component analysis, an artificial neural network consisting of three layers of nodes was trained by applying a back-propagation learning rule. The optimized ANN allows the simultaneous quantitation of four analytes in mixtures with relative standard errors of prediction in the region of 5% for four species. The results show that PC-ANN is an efficient method for prediction of the four analytes.     

Bulk and rheological properties of polyacrylamide hydrogels for water shutoff treatment

Presenting an optimal hydrogel for water shutoff, based on the bulk and rheological properties, was the main purpose of this research. To determine gelation time, a bottle test was conducted using central composite design method with two factors, AN125VLM and Cr(OAc)₃, as copolymer and crosslinker, respectively. To select hydrogel with high strength network, crosslinking density and consistency modulus were also measured. Hence, a hydrogel with 26,340 ppm concentration of copolymer, 0.12 ratio of crosslinker/copolymer, maximum value of crosslinking density (1,950) and consistency modulus (31,900 Pa) was selected as the optimal one. To study the gelation time among different factors in porous media, rheological experiments were carried out by Plackett-Burman design to screen the eight factors (NaCl, CaCl₂, KCl and MgCl₂ concentrations, temperature, pH, sodium lactate and nanoclay). Accordingly, temperature was the most effective factor controlling the gelation time, while pH and other factors had negligible effect on the gelation time of the optimal hydrogel.     

Effects of polydimethylsiloxane grafting on the calcification,physical properties,and biocompatibility of polyurethane in a heart valve

Segmented polyurethane (PU) has proven to be the best biomaterial for artificial heart valves, but the calcification of polyurethane surfaces causes serious problems in long‐term implants. This work was undertaken to evaluate the effects of polydimethylsiloxane (PDMS) grafting on the calcification, biocompatibility, and blood compatibility of polyurethane. A grafted polyurethane film was compared with virgin polyurethane surfaces. Physical properties of the samples were examined using different techniques. The hydrophobicity of the polyurethane films increased as a result of silicone modification. The effects of surface modification of polyurethane films on their calcification and fibroblast cell (L 929) and platelet behavior were evaluated in vitro. Fourier transform infrared spectroscopy indicated the direct involvement of the polyether soft segments of the polymer in the calcification process. Scanning electron microscopy of films indicated that grafting of silicone rubber to the surface of polyurethane successfully prevented the calcification process. The morphology of fibroblast cells that adhered to the PU films and modified films was similar to that of controls and showed the same proliferation. On the other hand, grafting PDMS onto PU did not affect the amount of platelets that adhered to the polyurethane surfaces. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 758–766, 2005     

Diversity achieving full-duplex DF relaying with joint relay-antenna selection under Nakagami-m fading environment

One of the main imperfections degrading the performance of full-duplex (FD) relaying systems is the outage floor. In this work, a power scaling method is proposed, which overcomes this effect even when there does not exist a direct channel between source and destination nodes. The system is composed of $K$ decode-and-forward (DF) FD relays over the Nakagami-m fading environment. To promote system performance, joint antenna and relay selection methods are employed in the FD relaying systems. Each FD relay is equipped with multiple antennas for receiving and the other for transmitting the information. The transmitting and receiving antennas are chosen based on the instantaneous channel variations, and one relay is selected to improve the signal-to-interference and noise ratio (SINR) of the FD relaying system. The performance of the proposed design is investigated. Moreover, the closed-form equations of the ergodic capacity and outage probability are attained. The analytical results are confirmed by different simulations. Results indicate that the proposed design achieves an additional spatial diversity gain because of using the antenna selection at the relay nodes. Moreover, by power scaling (PS) method, the system performance is effectively improved compared to the conventional FD relaying structures.