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Objective: Enterotoxigenic Escherichia coli is considered as the most important agent of children diarrhea and mortality in developing countries. This bacterium causes 300-600 thousands of deaths in the children under 5 years of age per year. With difficulties in treatment as well as its wide prevalence, designing an effective vaccine against this microorganism is the objective of world Health Organization (WHO). The CfaB protein as immunogen and major subunit of fimberia has a critical role in the bacterial attachment to small intestine epithelium and the produced antibody against this protein can prevent attachment of bacterium to epithelial surface. Hence, this molecule alone or with other virulent factors has been considered by many researchers in vaccine designing. In this study, expression of colonization factor B with the aim of studying the immunogenesity of this protein as a component of vaccine candidate was performed. Materials and Methods: cfaB gene was amplified by PCR and cloned into pET28a and its expression was evaluated. Since there was no expression, which was due to presence of rare codon, the cfaB gene was again cloned into pET28a using codon bias in E.coli and subsequently expressed. Results: Presence of a 20KD band on SDS-PAGE gel indicated the expression of CfaB protein, which was later confirmed by immunoblotting with anti-His tag and anti CfaB antibodies and purified on Ni-NTA column. Conclusion: Codon optimization and expression in heterologous hosts is a useful approach for obtaining large quantities of recombinant protein.

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Centrifugal pumps performance is highly affected by working fluid viscosity. So, optimization of such pumps for pumping of viscose fluids is very important. In the present paper, multi-objective optimization of the centrifugal pumps is performed to obtain optimum impellers for pumping fluids with various viscosities at different volumetric flow rates. In this way, theoretical head and impeller hydraulic losses are considered as objective functions. Design variables defined in this optimization problem are passage width of impeller and outlet angle of blade. Diagrams of Pareto fronts and Pareto sets are extracted for different viscosities and different volumetric flow rates. Some trade-off optimum design points are selected from all non-dominated points using three different methods namely break point, TOPSIS and near to ideal point. Such methods are defined completely and employed to achieve compromising point successfully. Obtained optimum points contain interesting results which cannot be achieve without using proposed multi-objective optimization approach.

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Inducing compressive residual stress is one of the methods of improving fatigue life in metallic components. There are numerous and various methods for inducing compressive residual stress, such as shot peening and deep rolling. One of the most recent and most advanced methods for inducing compressive residual stress in industrial components is Laser Shock Peening (LSP). LSP is a relatively new and complex process, therefore, vast experimental investigations are needed for better understanding the process. For this purpose in the present work, an Nd: YAG Laser with 1200mJ of energy per pulse was used to investigate the LSP process experimentally on Al 6061- T6 alloy. The effect of process on the hardness beneath the surface, the microstructure, and the surface roughness was studied. In addition, in order to investigate the effect of the LSP process on a notch, a notched sample was treated using the LSP process. The results showed that the process could increase the hardness of the material up to 1000μm below the surface. Furthermore, the results showed that the surface roughness would slightly get increased, while this increase could be limited by properly selecting the process parameters. The LSP process of the notched sample showed that this process could lead to the growth of cracks in such samples.

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In Carbon monoxide (CO) is one of the main air pollutant parameters in the atmosphere of Tehran, Iran. Generally, it is difficult to predict and control CO concentration because it is essentially nonlinear time-varying system. Recently, in particular, environmental control such as CO concentration level control is regarded as one of the most important factors in environmental protections. This paper describes forecasting and more specifically uncertainty determination of CO concentration during the modeling process using a support vector machine (SVM) technique. Uncertainty of the air pollution modeling studies highly affected the simulation results. In this regards, it is very important to determine the uncertainty of air pollution models due to consequences on health of people exposed to the pollution. Therefore, this research aims to calibrate, verify, and also determine the uncertainty of support vector machine (SVM) in the process of air pollution modeling in the atmosphere of Tehran. To achive this goal, the SVM model was selected to predict arithmetic average of daily measured CO concentration in the atmosphere of Tehran. In this regards, the SVM model was calibrated and verified using six daily air pollutants include particulate matter with diameter equal or less than 10 micrometer (PM10), total hydrocarbons (THC), nitrogen oxides (NOx), methane (CH4), sulfur dioxide (SO2) and ozone (O3) and also six daily meteorological variables include pressure (Press), temperature (Temp), wind direction (WD), wind speed (WS) and relative humidity (Hum). The data was collected from Gholhak station located in the north of Tehran, Iran, during 2004-2005. Thereafter, the best developed SVM model for predicting the CO concentration was chosen based on determination of coefficient (R2). Finally, to determine the SVM uncertainty, the model was run many times with different calibration data. It led to many different results because of the model sensitivity to the selected calibration data. Then, the model uncertainty in the CO prediction process was evaluated using the width of uncertainty band (d-factor) and the percentage of measured data bracketed by the 95 percent prediction uncertainties (95PPU). Generally, the results confirmed the strong performance of the SVM model in predicting CO concentration in the atmosphere of Tehran. The predicted average daily CO concentrations by SVM model had a good agreement with the measured ones in the Gholahak air quality monitoring station. It was found that the determination of coefficient for calibration and validation of SVM model were equal to 0.89 and 0.88, respectively. Furthermore, the results indicated that the SVM model has an acceptable level of uncertainty in prediction of CO concentration in which the level of d-factor and the percentage of measured data bracketed by the 95PPU in the validation step were 0.74 and 76, respectively. Therefore, The obtained results indicated that the SVM model had an acceptable level of uncertainty in prediction of CO concentration. Therefore, it can be concluded that the SVM model is able to predict the CO concentration in the atmosphere of Tehran while it resulted an acceptable level of uncertainty. Finally, due to the proposed methodology is general, the authors suggest to apply it for analyzing the uncertainty of SVM model in other fields of science and engineering.

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Objective: Cholera is an endemic disease in Iran. Early detection, especially in times of disease outbreaks, is of vital importance. The antibody against the lipopolysaccharide (LPS) is an important method for bacterial detection. This study intends to extract and purify the LPS of Vibrio cholerae and evaluate the cholera antibody for detection purposes. Methods: Vibrio cholerae was cultured in tryptone extract medium. LPS was extracted by the hot phenol water method, purified, and dialyzed. We measured the LPS protein and sugar content, purity, and biological activity. Antibodies were produced by injection of the killed bacteria with Freund's complete adjuvant into rabbits and then the LPS was injected three times with Freund's incomplete adjuvant. After the last booster, blood samples were taken. We used ELISA to determine the antibody titers against the Inaba and Ogawa serotypes, the LPS of these serotypes, and several other similar bacteria. Results: The amount of protein in the purified LPS was approximately zero and sugar was 0.5 mg/ml. The LPS had a titer activity of 1024, and consisted of three bands (5.2, 4, and 5.14 KD). Antibodies produced by the rabbits identified the bacterial Inaba and Ogawa serotypes, and the purified LPS. Ogawa and Inaba serotypes cross-react with each other but not with other species of Vibrio and other bacteria. The LPS antibody titer against the Ogawa serotype was 1:32000, whereas for Inaba it was 1:16000. Conclusion: Due to the low cost of production, high sensitivity, and importance of cholera diagnosis in Iran, the antiserum produced in this study can be used as a tool for early screening of cholera and discrimination of O1 strains from non-O1 strains in immunologic tests.