Showing 6 results for Bahreini
Volume 10, Issue 3 (12-2010)
Abstract
Abstract
In this paper, using Artificial Neural Networks (ANNs) and Finite Element Method (FEM),
health monitoring of damaged cantilever beams having longitudinal cracks is discussed. The
main focus is devoted to the nonlinear behavior (breathing) of crack, which, to our knowledge,
is taken into account in the crack detection of structures using ANNs, for the first time. Thus
nonlinear behavior of crack is modeled using FEM.The changes in the natural frequencies
(due to crack) of various vibration modes were implemented as input for training and testing
of ANNs. By producing various scenarios for sound and damaged beams (with different
damage location and severity), two specific classes of ANNs were trained to predict the
location and length of longitudinal cracks. The Results showed a promising prediction for the
length of cracks by the proposed methodology. Also a considerable approximation observed in
the prediction of cracks location.
S. Mehrban , M. Bahreini , A. Asoodeh , B. Korozhdehi,
Volume 10, Issue 4 (Fall 2019)
Abstract
Aims: Significant amounts of waste, including feathers, bones, blood, etc. are yearly produced by the poultry industry. Feathers are composed of 90% keratin protein, and the rest is composed of lipids and water. Keratinases are one of the most diverse and usable enzymes, which can be produced by bacterial and fungal microorganisms. These enzymes show a wide range of application in various fields.
Materials and Methods: In this study, the keratinolytic activity of the isolated strain from a poultry farm in Mashhad was evaluated and then the medium conditions for keratinase production were optimized. The strains were identified based on the morphological and biochemical methods. 16SrRNA gene of the strain was amplified by PCR and then sequenced. The strain proteolytic activity was examined and compared with its keratinolytic activity. Finally, strain growth ability tested in variety substrate.
Findings: Using 16SrRNA gene sequencing, morphological and biochemical identification, the strain shared 99.9% similarity with Bacillus mojavensis. Optimization of various factors, including temperature, pH, incubation time, carbon and nitrogen sources, aeration and inoculum size showed that the isolated strain has the highest keratinolytic activity at 37°C, 48 hour incubation period, pH=9.5, sucrose 1%, 3% substrate, aeration 75% and 6% (v/v) inoculum amount. None of the nitrogen sources had a positive effect.
Conclusion: The FUM-1 keratinolytic activity was increased approximately 3.38 fold by condition optimization of the medium, indicating the importance of environmental conditions. In the study, the strain with high keratinolytic activity was suggesting its potential use in biotechnological.
Leila Shokrzadeh, Parisa Mohammadi, Masoumeh Bahreini, Samira Behdani, Ali Asgar Sabet Jazari,
Volume 11, Issue 1 (Winter 2020)
Abstract
Fungi are the most important agents of biodeterioration in museums, libraries, and repositories. The objectives of the paper were to evaluate the microbial diversity in biodeteriorated manuscripts located in a repository of the central library of Astan Quds Razavi (AQR) and to estimate the fungal occurrence of the repository air. The sterile cotton swabs and nitrocellulose membranes were used for sampling the manuscripts, while the sedimentation method was used for the microbial sampling of air. To evaluate the biodeteriorative impacts of fungi, fungal spore’s suspension inoculated on paper strips. Fourteen and six fungal isolates were collected from the three different deteriorated substrates and the repository air samples, respectively. Among the fungi isolates, Aspergillus sp. was isolated in high frequency (36%), followed by Penicillium sp. (21/5%) and Altelnania sp. (14%). Fungi species including P. chrysogenum, Cladosporium cladosporioides, Talaromyces diversus, and Aspergillus sp. were isolated from B1 sample as a parchment. The most fungal isolates (53%) in the air repository including Purpureocillium lilacinum, Talaromyces diversus, Cladosporium sp., and Aspergillus sp were achieved from MEA medium. The low number of isolated fungi from repository air can be attributed to the efficiently controlled environment factors of AQR repository. The combination of finding provides some support for the conceptual premise that it could be a direct relationship between the isolated microorganisms from air and those isolated from the manuscripts. The presence of color spots on paper strips can approve the biodeterioration of paper via fungal activities.
Volume 13, Issue 53 (5-2015)
Abstract
The objective of this experiment was to investigate the antimould effect of 19 Lactobacillus plantarum strains isolated from different production stages of Lighvan cheese (3, 8 and 8 strains from raw milk, curd and fresh cheese stages, respectively) a traditional raw milk cheese, on Penicillium expansum (PTCC 89046) as an indicator in fruit juice spoilage. This antimould spectrum was determined by agar spot and well diffusion method, followed by determination the influence of different technological or physico-chemical factors including temperature (80°C for 1 h, 100°C for 10 min, 100°C for 30 min and 121° C for 15 min) and pH( 2 to 7) and different dilution (Titre test) . Serial twofold dilutions were conducted to the CFE in order to assess of CFE Titre against mould indicator. Findings revealed that Lactobacillus plantarum strain C28 has the highest antimould properties in both antimicrobial methods (Agar Spot and Well Diffussion Assay) and antimould effect showed decreasing trend with pH increasing. In 121 ° C for 15 min, no antimould effect was observed. The Lactobacillus plantarum strain C28 showed the highest titre factor of 160 (AU / ml) . Finally, we can assume that these strains which isolated from different production stages of Lighvan cheese or their Cell Free Extract (CFE) can be used as biopreservative in food systems.
Volume 16, Issue 1 (1-2014)
Abstract
The objectives of this study were to identify a suitable mathematical model for describing the growth curve of Baluchi sheep based on monthly records of live weight from birth to yearling; and to evaluate the efficacies of nonlinear mixed effect model (NLMM) and the nonlinear fixed effect model (NLM) methodologies. Growth models were fitted to a total of 16,650 weight–age data belonging to 2071 lambs. Five nonlinear growth functions of von Bertalanffy, Gompertz, Brody, Logistic, and Richards and two linear polynomial functions were applied. The growth models were compared by using the Akaike’s information criterion (AIC) and residual mean square (MSE). Among all nonlinear fixed effect models, the Brody function had the smallest AIC and MSE values, indicating the best fit for both sexes. The Brody fixed effect model compared with NLMM including one random effect of asymptotic mature weight. The model evaluation criteria indicated that the Brody mixed effect model fitted the data better than the corresponding fixed effect model. It can be concluded that, among the linear models, the polynomial of the third order and, among nonlinear models, Brody mixed model were found to best fit the Baluchi sheep growth data.
Volume 16, Issue 12 (2-2017)
Abstract
In this paper, by introducing of development of two approaches based on the relative map filter (RMF); it has been tried to improve simultaneous localization and mapping (SLAM). The implementation of Extended Kalman Filter SLAM (EKF-SLAM) in large environments is not practical due to large volume of calculations. On the other hand, the observation and motion models of many robots are nonlinear and these cause the divergence of EKF-SLAM. The basis of RMF is relative distances between landmarks; therefore its equations are independent from the robot motion model. Also, the robot observation model can be linearly defined and its convergence is guaranteed. Despite these features, the relative filter proposed methods are faced with the problem of ambiguity in absolute positioning of robot and landmarks. In this article, ILPE (Improved Lowest Position Estimation) and IMVPE (Improved Minimum Variance Position Estimation) methods are introduced. In these methods, the ambiguity problem in localization and mapping of robot and landmarks are solved by sequential switching between absolute and relative spaces. The calculation volume of these methods does not depend on the number of landmarks and depends on the average number of landmarks observed in each scan of the robot. In this paper, the equations and the required algorithm to find the position of landmarks and robot are presented. Moreover by simulation, the performance and efficiency of the proposed methods are discussed in comparison with the previous methods including EKF-SLAM.
