Islamic Azad University at Ashkezar
Yazd, Iran
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Aghaei F.,Islamic Azad University at Ashkezar | Seifati S.M.,Islamic Azad University at Ashkezar | Nasirizadeh N.,Islamic Azad University at Yazd
Analytical Methods | Year: 2017

Phenylketonuria (PKU), which is a deficiency of an important metabolic enzyme, is caused by several identified point mutations in populations around the world. Several methods have been developed for the detection of DNA mutations so far, including biosensors, especially electrochemical biosensors. In this research, we developed a novel biosensor using a special electrochemical label, hematoxylin. A screen-printed gold electrode (SPGE) modified with thiolated detection probes was used to detect the point mutation IVS10nt-11g→a of phenylalanine hydroxylase (PAH) enzyme. The methodology and its efficiency have been proved using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) studies in [Fe(CN)6]3−/4− solution. Under optimized conditions, the biosensor was able to detect the target DNA ranging from 20 pM to 150 nM with a detection limit of 8.5 pM. In addition, the selectivity of the biosensor was tested by the application of single-base mismatched and three-base mismatched oligonucleotides in comparison to the target DNA. Finally, the interference studies were performed in order to confirm the functionality of the biosensor in real sample applications, which proved good functionality for the biosensor in simulated extracted DNA solutions. © The Royal Society of Chemistry.

Kakahaji H.,Islamic Azad University at Tehran | Banadaki H.D.,Islamic Azad University at Ashkezar | Kakahaji A.,Islamic Azad University at South Tehran | Kakahaji A.,Water Resources Management Company of Iran
Water Resources Management | Year: 2013

Undoubtedly, the most significant factor with wise decision making and designing hydrological structures along the lake coasts is an accurate model of lake level changes. This issue becomes more and more important as recent global climate changes have completely reformed the behavior of traditional lake level fluctuations. Subsequently, estimating lake levels becomes more important and at the same time more difficult. This paper deals with modeling lake level changes of Lake Urmia located in north-west of Iran, in terms of both simulator and predictor models. According to this, two traditional simulator models based on water budget are developed which benefit from most effective components on water budget namely precipitation, evaporation, inflow and the lake level antecedents, as model inputs. Most famous linear modeling tools, Autoregressive with exogenous input (ARX) and Box-Jenkins (BJ) models are employed with the same mentioned inputs for prediction purpose. In addition, two other methods that are, Multi-Layer Perceptron (MLP) neural network and also Local Linear Neuro-Fuzzy (LLNF) are applied to investigate capability of intelligent nonlinear methods for lake level changes prediction. All models performances are indicated using both graph and numerical illustrations and results are discussed. Comparative results reveal that the intelligent methods are superior to traditional models for modeling lake level behavior as complex hydrological phenomena. © 2013 Springer Science+Business Media Dordrecht.

Jozi S.A.,Islamic Azad University at Tehran | Pouriyeh A.A.,Islamic Azad University at Ashkezar
Chemical Industry and Chemical Engineering Quarterly | Year: 2011

Growing importance of environmental issues at global and regional levels including po lution of water, air etc. as we l as the outcomes such as global warming and climate change have led to environmental aspects being considered as effective factors for power generation. The aim of this study is the examination of risks resulting from activities of the Yazd Combined Cycle Power Plant located in Iran. The method applied in the research is analytical hierarchy process. After identification of factors causing risk, the analytical hierarchy structure of the power plant risks was designed and the weights of the criteria and sub-criteria were calculated by intensity probability product using Eigenvector method and Expert Choice software. Results indicate that in technological, health-safety, biophysical and socioeconomic sections of the power plant, factors influenced by the power plant activities like fire and explosion, hearing loss, quantity of groundwater, power generation are among the most important factors causing risk in the power plant. The drop in underground water levels is the most important natural consequence influenced on Yazd combined cycle power plant.

Zare-Karizi S.,Iran National Institute of Genetic Engineering and Biotechnology | Hosseini-Mazinani S.M.,Iran National Institute of Genetic Engineering and Biotechnology | Khazaei-Koohpar Z.,Islamic Azad University at Tonekabon | Seifati S.M.,Iran National Institute of Genetic Engineering and Biotechnology | And 4 more authors.
Molecular Genetics and Metabolism | Year: 2011

Identification of molecular basis of phenylketonuria (PKU) in Iran has been accomplished through the analysis of 248 unrelated chromosomes from 124 Iranian classic PKU subjects. Phenylalanine hydroxylase (PAH) gene mutations were analyzed through a combined approach in which p.S67P, p.R252W, p.R261Q, p.R261X, p.L333F, IVS10-11G>A, IVS11+1G>C, p.L364del, p.R408Q and p.R408W mutations were first screened by PCR of PAH gene exons 3, 7, 10, 11 and 12, followed by digestion with the appropriate digestion enzymes. Subsequently SSCP analysis for exons 2, 6, 7 and 11 of the PAH gene and finally, sequencing of 13 PAH gene exons have been used to study uncharacterized PKU chromosomes. 26 different mutations were found. The predominant mutation in this population sample was IVS10-11G>A, with a frequency of 24.6%. Nine mutations (IVS10-11G>A, p.R261Q, p.P281L, IVS11+1G>C, p.K363>NFS, p.R243X, IVS2+5G>C, p.R261X and p.R252W) represent almost 84% of all PKU chromosomes studied. IVS10-11G>A mutation is the major PKU-causing mutation throughout the Mediterranean region. The finding of the high prevalence of this mutation in Iranian population is consistent with the historical and geographical links between Iranian and Mediterranean populations. © 2010 Elsevier Inc.

Mirabi M.,Islamic Azad University at Ashkezar | Ghomi S.M.T.F.,Amirkabir University of Technology | Jolai F.,University of Tehran
Journal of Intelligent Manufacturing | Year: 2013

This paper considers a two-stage hybrid flowshop scheduling problem in machine breakdown condition. By machine breakdown condition we mean that the machine may not always be available during the scheduling period. Machine failure may occur with a known probability after completing a job. Probability of machine failure depends on the previous processed job. The problem to be studied has one machine at the first stage and M parallel identical machines at the second stage. The objective is to find the optimal job combinations and the optimal job schedule such that the makespan is minimized. The proposed problem is compatible with a large scope of real world situations. To solve the problem, first, we introduce one optimal approach for job precedence when there is one machine in both stages and then provide a heuristic algorithm when there are M machines in stage two. To examine the performance of the heuristic, some experiments used are provided as well. © 2011 Springer Science+Business Media, LLC.

Mirabi M.,Islamic Azad University at Ashkezar | Fatemi Ghomi S.M.T.,Amirkabir University of Technology
IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management | Year: 2010

Single machine capacitated lot-sizing and scheduling problem (SMCLSP) is one of the most famous fields of research in scheduling area. What makes this problem particularly difficult to solve is large and sequence dependent setups and also multiple criteria that must be considered. This paper formulates such a problem and presents a hybrid simulated annealing (HSA) for it. The superiority of HSA is shown compared to one the efficient recent heuristics. The average deviation of the HSA from the corresponding optimal solution for small size problems ranges from 0 to 10%. ©2010 IEEE.

Fathullahzadeh S.,Islamic Azad University at Ashkezar
Cancer Gene Therapy | Year: 2016

Chronic lymphocytic leukemia (CLL) is known as the most common lymphoid malignancy in the Western world. MicroRNAs (miRNAs) are a class of small noncoding RNAs with pivotal roles in cellular and molecular processes related to different malignancies including CLL. Recently, some studies have shown that miR-192 plays a key role in CLL pathogenesis through increasing CDKN1A/p21 levels, suppression of Bcl-2 and enhancement of wild-type P53 and cell cycle arrest. Forty samples, including 20 patients with CLL, diagnosed in Omid hospital (Isfahan, Iran) and 20 healthy controls were sampled during a period of 4 months. Using real-time PCR method, expression of miR-192 was analyzed in peripheral blood mononuclear cells (PBMCs) of CLL patients in comparison with healthy subjects. In silico molecular signaling pathway enrichment analysis was also performed on validated and predicted targets (targetome) of miR-192 in DAVID database to explore possible role of miR-192 in some pathways. The expression of miR-192 was found to be significantly reduced (~2.5-folds) in CLL patients compared with healthy subjects (P=0.002). In silico molecular signaling pathway enrichment analysis detected cell indicated signaling pathway as one of the most statistically relevant pathway with miR-192 targetome. Our findings showed that miR-192 could be a biomarker for early diagnosis of CLL.Cancer Gene Therapy advance online publication, 23 September 2016; doi:10.1038/cgt.2016.34. © 2016 Nature America, Inc., part of Springer Nature.

Mirabi M.,Islamic Azad University at Ashkezar
International Journal of Advanced Manufacturing Technology | Year: 2011

Single-machine capacitated lot-sizing and scheduling problem (SMCLSP) is one of the most famous fields of research in scheduling area. What makes this problem particularly difficult to solve in many real situations is large and sequence-dependent setups and also multiple criterions that must be considered. In this paper, such a problem is formulated and a hybrid simulated annealing for this problem is presented. Also, lower bounds are obtained from solving the problem relaxation, and they are compared with the optimal solutions to estimate the goodness of them. As decision criteria, all of important costs imposed by the solution are considered and also infeasible sequences are mentioned. There is a ceiling value for the manufacturer's cost of each job and according to it, some sequences between jobs are maybe infeasible. It showed the superiority of hybrid simulated annealing (HSA) compared with one of the efficient recent heuristics. The average deviation of the HSA from the corresponding optimal solution for small-size problems ranges from 0% to 10% and from the corresponding lower bound ranges for large-size problems ranges from 11% to 21%. The presented HSA is capable to solve large instances that are mostly compatible with the real-world problems. © Springer-Verlag London Limited 2010.

Mirabi M.,Islamic Azad University at Ashkezar
International Journal of Advanced Manufacturing Technology | Year: 2011

In the real world, production scheduling systems, usually optimal job scheduling, requires an explicit consideration of sequence-dependent setup times. One of the most important scheduling criteria in practical systems is makespan. In this paper, the author presents an ant colony optimization (ACO) algorithm for the sequence-dependent permutation flowshop scheduling problem. The proposed ACO algorithm benefits from a new approach for computing the initial pheromone values and a local search. The proposed algorithm is tested on randomly generated problem instances and results indicate that it is very competitive with the existing best metaheuristics. © 2010 Springer-Verlag London Limited.

Mirabi M.,Islamic Azad University at Ashkezar
World Academy of Science, Engineering and Technology | Year: 2011

Flow-shop scheduling problem (FSP) deals with the scheduling of a set of jobs that visit a set of machines in the same order. The FSP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To meet the requirements on time and to minimize the make-span performance of large permutation flow-shop scheduling problems in which there are sequence dependent setup times on each machine, this paper develops one hybrid genetic algorithms (HGA). Proposed HGA apply a modified approach to generate population of initial chromosomes and also use an improved heuristic called the iterated swap procedure to improve initial solutions. Also the author uses three genetic operators to make good new offspring. The results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of solution.

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