Shiraz University , formerly known as Pahlavi University, is a public university located in Shiraz, Iran. It is one of the major universities of Iran. Shiraz University has always ranked as Top 5 among Iranian universities and is well respected in Iran.The University of Pennsylvania assisted the Iranian government in transforming Shiraz University into the only institution in the Middle East based on American-style higher education. The University of Pennsylvania thus became highly influential in shaping many of Pahlavi University's departments and institutions. Shiraz University has the second biggest campus in Iran. It was initially designed by American architect, Minoru Yamasaki, who is also famous for designing the World Trade Center.Shiraz University has pioneered the establishment of doctoral programs in Iran. Presently the university has over 20,000 students, with 200 Bachelor's degree programs , 300 Master's degree programs , one professional degree program , and 150 Ph.D. programs. Wikipedia.
Rezaei Z.,Shiraz University
Astrophysical Journal | Year: 2017
In this work, we employ the dark matter equations of state (DMEOSs) obtained from the rotational curves of galaxies as well as the fermionic DMEOS with m = 1.0 GeV to study the structure of dark-matter admixed neutron stars (DMANSs). Applying the equation of state in the Skyrme framework for the neutron matter (NM), we calculate the mass-radius relation for different DMANSs with various DMEOSs and central pressure of dark matter (DM) to NM ratios. Our results show that for some DMEOSs, the mass-radius relations are in agreement with new observations, e.g., EXO 1745-248, 4U 1608-52, and 4U 1820-30, which are inconsistent with normal neutron stars. We conclude that both DMEOSs and central pressure ratios of DM to NM affect the slope of the mass-radius relation of DMANSs. This is because of the interaction between DM and NM, which leads to gravitationally or self-bound DMANSs. We study the radius of the NM sphere as well as the radius of the DM halo for different DMANSs. The results confirm that, in some cases, a NM sphere with a small radius is surrounded by a halo of DM with a larger radius. Our calculations verify that, due to the different degrees of DM domination in DMANSs, with a value of the visible radius of a star two possible DMANSs with different masses can exist. The gravitational redshift is also calculated for DMANSs with different DMEOSs and central pressure ratios. The results explain that the existence of DM in a DMANS leads to higher values of gravitational redshift of the star. © 2017. The American Astronomical Society. All rights reserved.
Hendi S.H.,Shiraz University |
Hendi S.H.,Research Institute for Astrophysics and Astronomy of Maragha RIAAM
Annals of Physics | Year: 2013
We consider two types of Born-Infeld like nonlinear electromagnetic fields and obtain their interesting black hole solutions. The asymptotic behavior of these solutions is the same as that of a Reissner-Nordström black hole. We investigate the geometric properties of the solutions and find that depending on the value of the nonlinearity parameter, the singularity covered with various horizons. © 2013 Elsevier Inc.
Mohabatkar H.,Shiraz University
Protein and Peptide Letters | Year: 2010
There are different types of cyclins, which are active during the cell cycle and enable cyclin-dependent kinases to phosphorylate different substrates. Since there is not much similarity between amino acid sequences of cyclins, predicting these proteins is an important job. This paper presents a bioinformatics classifier to predict cyclins based on Chou's pseudo amino acid composition. Analysis of the results by StAR, which is a program for the analysis of ROC curves, showed that accuracy of the approach was 83.53% (AUC=89.44%). The present work demonstrates that the method can provide useful information for predicting cyclins. © 2010 Bentham Science Publishers Ltd.
Mansoori E.G.,Shiraz University
IEEE Transactions on Fuzzy Systems | Year: 2011
Fuzzy clustering is superior to crisp clustering when the boundaries among the clusters are vague and ambiguous. However, the main limitation of both fuzzy and crisp clustering algorithms is their sensitivity to the number of potential clusters and/or their initial positions. Moreover, the comprehensibility of obtained clusters is not expertized, whereupon in data-mining applications, the discovered knowledge is not understandable for human users. To overcome these restrictions, a novel fuzzy rule-based clustering algorithm (FRBC) is proposed in this paper. Like fuzzy rule-based classifiers, the FRBC employs a supervised classification approach to do the unsupervised cluster analysis. It tries to automatically explore the potential clusters in the data patterns and identify them with some interpretable fuzzy rules. Simultaneous classification of data patterns with these fuzzy rules can reveal the actual boundaries of the clusters. To illustrate the capability of FRBC to explore the clusters in data, the experimental results on some benchmark datasets are obtained and compared with other fuzzy clustering algorithms. The clusters specified by fuzzy rules are human understandable with acceptable accuracy. © 2011 IEEE.
Raoofat M.,Shiraz University
International Journal of Electrical Power and Energy Systems | Year: 2011
Reliability improvement and loss reduction are two important goals in optimal sizing and siting of distributed generations (DGs). Also, remote controllable switches can be utilized in distribution networks to increase the role of DGs in reliability improvement. Therefore, this paper presents a GA-based method to allocate simultaneously DGs and remote controllable switches in electric distribution networks. The goal of proposed approach is reliability improvement and energy loss reduction. The optimal sizes of distributed generators are also determined during the optimization procedure. A multilevel yearly load model is utilized to achieve the optimal solution. Numerical studies on a 33-bus distribution network show satisfactory results. © 2011 Elsevier Ltd. All rights reserved.
Ardakani A.G.,Shiraz University
Journal of the Optical Society of America B: Optical Physics | Year: 2014
In this paper, we propose a one-dimensional ternary photonic crystal based on magnetized plasma to obtain nonreciprocal propagation. By employing the transfer matrix method, the transmission spectra of the counterpropagating plane waves incident from air upon either end of the periodic structure are calculated. Our results reveal that there is a significant contrast between the transmittance of the waves propagated in opposite directions. This means that the structure shows nonreciprocal effects. It is shown that the bandwidth at which nonreciprocity is observed depends on the external magnetic field. The effects of the incident angle and the number of elementary cells on the nonreciprocal behaviors are studied. We demonstrate that nonreciprocity disappears in very small angles of incidence. The designed structure shows nonreciprocal response even in the case of a small number of layers. It is also demonstrated that nonreciprocal effects become stronger when increasing the plasma density and the wavelength of the incident wave. © 2014 Optical Society of America.
Saadat M.,Shiraz University
Cancer Epidemiology | Year: 2012
Aim: The paraoxonase 1 gene (PON1, MIN: 168820) is a member of the multifactorial antioxidant enzyme paraoxonase family (EC 18.104.22.168). Two common functional single-nucleotide polymorphisms L55M (dbSNP: rs854560) and Q192R (dbSNP: rs662) have been identified in the coding region of PON1. Several studies have investigated the associations between polymorphisms of PON1 and susceptibility to breast cancer, but have yielded apparently conflicting results. We therefore carried out a meta-analysis of published studies to clarify this inconsistency and to establish a comprehensive picture of the relationship between PON1 gene variants and breast cancer risk. Method: Overall six eligible studies were identified. Summary odds ratios (ORs) and 95% confidence intervals (CIs) were obtained using fixed and random-effect models. Results: In our meta-analysis, the presence of the R allele was associated with decreased risk of breast cancer (QR+RR compared to QQ genotype, summary OR=0.57, 95% CI: 0.49-0.67, P<0.001). Both heterozygosity (OR=1.32, 95% CI: 1.10-1.58, P=0.002) and homozygosity (OR=2.16, 95% CI: 1.75-2.68, P<0.001) for the 55M allele were associated with increased risk of breast cancer. Also there was a significant linear trend in risk associated with zero, one, and two 55M alleles (χ 2=54.2, P<0.001). Conclusion: The present study showed that PON1 M and Q alleles are associated with a higher risk of breast cancer. Individuals having MM and QQ genotypes have a lower level and lower detoxification activity of the PON1 enzyme, which may increase the vulnerability of the breast to genetic damage by reducing the ability to detoxify inflammatory oxidants, as well as dietary carcinogens. © 2011 Elsevier Ltd.
Eghtedarpour N.,Shiraz University |
Farjah E.,Shiraz University
IEEE Transactions on Smart Grid | Year: 2014
Hybrid ac/dc microgrids have been planned for the better interconnection of different distributed generation systems (DG) to the power grid, and exploiting the prominent features of both ac and dc microgrids. Connecting these microgrids requires an interlinking ac/dc converter (IC) with a proper power management and control strategy. During the islanding operation of the hybrid ac/dc microgrid, the IC is intended to take the role of supplier to one microgrid and at the same time acts as a load to the other microgrid and the power management system should be able to share the power demand between the existing ac and dc sources in both microgrids. This paper considers the power flow control and management issues amongst multiple sources dispersed throughout both ac and dc microgrids. The paper proposes a decentralized power sharing method in order to eliminate the need for any communication between DGs or microgrids. This hybrid microgrid architecture allows different ac or dc loads and sources to be flexibly located in order to decrease the required power conversions stages and hence the system cost and efficiency. The performance of the proposed power control strategy is validated for different operating conditions, using simulation studies in the PSCAD/EMTDC software environment. © 2010-2012 IEEE.
Eslamloueyan R.,Shiraz University
Applied Soft Computing Journal | Year: 2011
This paper proposes a hierarchical artificial neural network (HANN) for isolating the faults of the Tennessee-Eastman process (TEP). The TEP process is the simulation of a chemical plant created by the Eastman Chemical Company to provide a realistic industrial process for evaluating process control and monitoring methods The first step in designing the HANN is to divide the fault patterns space into a few sub-spaces through using fuzzy C-means clustering algorithm. For each sub-space of fault patterns a special neural network has been trained in order to diagnose the faults of that sub-space. A supervisor network has been developed to decide which one of the special neural networks should be triggered. In this regard, each neural network in the proposed HANN has been given a specific duty, so the proposed procedure can be called Duty-Oriented HANN (DOHANN). The neuromorphic structure of the networks is based on multilayer perceptron (MLP) networks. The simulation of Tennessee-Eastman (TE) process has been used to generate the required training and test data. The performance of the developed method has been evaluated and compared to that of a conventional single neural network (SNN) as well as the technique of dynamic principal component analysis (DPCA). The simulation results indicate that the DOHANN diagnoses the TEP faults considerably better than SNN and DPCA methods. Training of each MLP network for the DOHANN model has required less computer time in comparison to SNN model. This is because of structurally simpler MLPs used by the developed DOHANN method. © 2010 Elsevier B.V. All rights reserved.
Aflakseir A.,Shiraz University
Journal of Diabetes | Year: 2012
Background: The aim of this study was to examine the role of illness and medication perceptions on medication adherence in a group of Iranian patients with type2 diabetes. Methods: A total of 102 patients with type 2 diabetes was recruited from an outpatient clinic in Shiraz, Iran, using the convenience sampling method. The participants completed the Illness Perception Questionnaire-Revised (IPQ-R), Belief Medication Questionnaire (BMQ), and Medication Adherence Report Scale (MARS). Results: The findings of the study revealed that illness perception, including timeline (chronic -the belief that diabetes would last a long time), predicted a higher level of medication adherence, while medication belief (concern - holding concerns about the potential negative effects of medicines) predicted a lower level of adherence to medicines. This prediction was above and beyond the relevant and demographic variables such as age and the duration of illness. Conclusions: The findings of this study suggest that medication beliefs, such as concern about the negative effects of medicines, have an important role in the low level of adherence to medication for diabetic patients in Iran. © 2012 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd.