Iranian Journal of Chemistry and Chemical Engineering
Volume:25 Issue: 4, Jul-Aug 2006

The biologists now face with the masses of high dimensional datasets generated from various high-throughput technologies, which are outputs of complex inter-connected biological networks at different levels driven by a number of hidden regulatory signals. So far, many computational and statistical methods such as PCA and ICA have been employed for computing low-dimensional or hidden representations of these datasets, but in most cases the results are inconsistent with underlying real network. In this paper we have employed and compared three linear (PCA and ICA) and non-linear (MLP neural network) dimensionality reduction techniques to uncover these regulatory signals, from outputs of such networks. The three approaches were verified experimentally using the absorbance spectra of a network of seven hemoglobin solutions, and the results revealed the superiority of the MLP NN to PCA and ICA. This study shows the capability of the MLP NN approach to efficiently determine the regulatory components in biological networked systems

The effects and influences of various parameters upon the efficiency and the overall volumetric mass transfer coefficients are important subjects to be studied in most liquid-liquid extraction processes. One of these important parameters is surface active agent (surfactant). In this paper, in order to study the effect of sodium dodecyl sulfate (SDS) concentration on the efficiency and the average overall volumetric mass transfer coefficients, several experiments were carried out in a ten stage mixer-settler. In these experiments the effect of surfactant concentration on above mentioned parameters at constant operational conditions are studied. In general the efficiency and mass transfer coefficients dropped significantly at low surfactant concentration and remained almost constant at the higher concentrations (Almost a minimum point was observed). Although the surfactant caused a decrease in mass transfer, but the amount of mass transfer coefficients in both phases are considerable and therefore the resistance against mass transfer in both phases cannot be neglected.

The kinetics of the potassium thiocyanate transport mediated by dicyclohexyl-18-crown-6 (L) through a bulk liquid membrane is studied experimentally and theoretically. The proposed model is based on the assumption of a pure diffusion of the complex salt [K•L]+SCN¯ through the liquid membrane stagnant films at the interfaces. It illustrates the connection between liquid-liquid extraction equilibrium data and transport rates. The evaluation of the transfer coefficient allows to evaluate the organic stagnant films thickness, the stationary state transport rate and the time lag.

Enzyme efficiency was investigated in the lipase-catalyzed hydrolysis of canola oil in supercritical carbon dioxide (SCCO2). Immobilized lipase from Mucor miehie (Lipozyme IM) was used as the catalyst and the results showed that enzyme efficiency dropped at high pressures indicating a possible change in enzyme microstructure. Therefore, scanning electron microscopy (SEM) was used as a supplementary tool to investigate microstructural stability of the enzyme under supercritical conditions. SEM images of the treated enzymes did not demonstrate any apparent structural changes with a change in pressure (24.0 and 38.0 MPa), enzyme load of the reactor (1.0 and 5.0 g), CO2 flow rate (0.5 and 3.9 L/min) and the oil content (extracted from 3.0 and 15.0 g canola flakes) of SCCO2. However, a change at the molecular level is a possibility, which requires further investigation.

An artificial neural network has been used to determine the volume flux and rejections of Ca2+, Na+ and Cl¯, as a function of transmembrane pressure and concentrations of Ca2+, polyethyleneimine, and polyacrylic acid in water softening by nanofiltration process in presence of polyelectrolytes. The feed-forward multi-layer perceptron artificial neural network including an eight-neuron hidden layer has the least error in modeling this non-linear process. The overall agreement between the artificial neural network results and experimental data is very good for both the volume flux and rejections, because the maximum values of normalized bias and error are -0.01122 and 1.0737 respectively.

The removal performance of total poly phenols and orthodiphenols (o-diphenols) content in olive mill waste (OMW) was investigated with a three stages cross flow laboratory scale rotating biological contactor (RBC) in the present study. Due to high COD and other pollutant in the original OMW, physico-chemical treatment was effected for COD and other pollutant reduction prior to biological treatment of OMW by the RBC system. Inoculation of RBC was effected by sludge from olive oil factory. In biological treatment, effect of operating parameters such as hydraulic loading (HL) and influent COD were examined. The study of the physico-chemical treatment before biological treatment of OMW showed, that about 9.1% of total poly phenols, 3.2% of o-diphenols and 12% of COD were removed by physical treatment. The effect of chemical treatment by different coagulants, alum, bentonite and zeolite at different pH and concentrations showed that bentonite at pH 6.5 and 15g/l resulted in the best removal efficiency of 20% for poly phenols and o-diphenols. The experimental results in RBC system show that at low HL, significant removal efficiency was observed for poly phenols and o-diphenols, at the first stage, but with increasing HL, other stages took part in removal efficiency. Also, decreasing COD from 5000 to 2500 at different HL caused an increase in poly phenols and o-diphenols removal efficiency.

In recent years, lots of research has been done on effective usage of natural gas; the first step in these processes is conversion of natural gas to Syngas. Natural gas reforming process by refomer furnace is commonly used for syngas and hydrogen production. In this paper, a windows based software, RIPI-RefSim, is introduced. By using proper heat, mass, kinetic and thermodynamic models as well as effect of catalyst shape, the software has been developed for the reformer furnace simulation for syngas and hydrogen production. RIPI-RefSim could be used in three different modes (Rating, Simulation and Design) and provides user a detailed understanding of furnace performance, product characteristics, temperature, reaction rates and pressure drop profiles, heat loss, effect of catalyst shape, and etc.

A method for determination of juglone in leaves and hulls of Pterocarya fraxinifolia was developed, based on RP-HPLC. This compound was extracted from leaves and hulls by chloroform refluxing about 2 hours. The chloroform was evaporated under low pressure at 50 ºC to produce a dry residue. The remained materials were dissolved in acetonitrile to be used for determination of this compound. Appropriate conditions for RP-HPLC were determined using standard of juglone. These conditions include, acetonitrile percentage in mobile phase, pH of mobile phase (phosphate buffer) and temperature of column, which were 50%, 4 and 30ºC, respectively. Juglone concentration was determined using standard addition method. The concentrations of juglone were 2.15, 2.74,1.77,1.12and 0.34 g in 100 g of dry leaves in May, June, July, August and September 2001, respectively. The content of juglone in hulls was 0.44 g in 100 g of dry hulls in May

In this paper, a simplified formulation for compositional reservoir simulator is presented. These types of simulators are used when inter-phase mass transfer depends on phase composition as well as pressure. The procedure for solving compositional model equations is completely described. For equilibrium calculation, property estimation Peng Robinson equation of state is used. This equation was tuned using some data from swelling test and saturation pressure data. It is another purpose of this work, to show how the gas oil interfacial tension impresses the predictions of developed compositional model. Application of the simulator to simulate the results of oil recovery from displacement tests is presented. A good agreement was achieved between the experimental data and model predictions.

First row transition metal complexes of phthalocyanine are employed as catalysts for the oxidation of cyclohexene and cyclooctene using iodosylbenzene and pentafluoroiodosyl benzene. The catalysis was performed in dichloromethane:methanol:water (80:18:2) solvent mixture. The products of the catalysis for cyclohexene are epoxycyclohexane, 2-cyclohexene-1-ol and 2-cyclohexene-1-one whereas for cyclooctene it is specifically cyclooctene oxide. For cyclohexene oxidation epoxide yield and selectivity is in the order of MnII > FeIII > FeII > CoII > CrIII > NiII > CuII, while for 2-cyclohexene-1-one production the ability of the catalysts are in the order of NiII > CoII > CuII > CrIII > FeIII > FeII > MnII.

This study deals with the uptake of Cd 2+ and Mn2+ ions from contaminated water using two Iranian natural clinoptilolite-rich tuffs from Meyaneh (Z-m), and Semnan (Z-s) regions, and a synthetic zeolite-P from Z-m sample (Z-P) under static (batch operation) and dynamic (column operation) conditions. To investigate the selectivity of the zeolites toward Cd 2+ and Mn2+ cations, the ion exchange isotherms were constructed at 298K. According to the data obtained for both cations, the following general trend in distribution coefficient (Kd) and consequently in selectivity was achieved for the investigated exchangers: Z-P>>Z-m> Z-s.