Deletioglu D.,Mustafa Kemal University |
Yalcinkaya S.,Mustafa Kemal University |
Demetgul C.,Mustafa Kemal University |
Timur M.,Mustafa Kemal University |
Serin S.,Ukurova University
Materials Chemistry and Physics | Year: 2011
The complex of copper (II) with N,N′-bis(3-methoxysalicylidene)-2- aminobenzylamine (H2L) was synthesized and characterized by elemental analysis, magnetic susceptibility, UV-vis. and FT-IR spectroscopy. The results showed that the tetradentate ligand coordinated to the Cu(II) ion through the azomethine nitrogen and phenolic oxygen atoms. The prepared complex [CuL] was electropolymerized on platinum electrode surface in a 0.1 mol dm-3 solution of lithium perchlorate in acetonitrile by cyclic voltammetry between 0 and 1.6 V vs. Ag/Ag+. Cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), conductance measurements, FT-IR and SEM were used to characterize polymer film of Cu(II) complex. The reduction of hydrogen peroxide on poly[CuL] has been investigated mainly in phosphate buffer medium (pH 7.2), between 0 and -0.8 V versus Ag/Ag+ at a scan rate 0.1 V s-1. © 2011 Elsevier B.V. All rights reserved.
Eker I.,Ukurova University
ISA Transactions | Year: 2010
In this article, a second-order sliding mode control (2-SMC) is proposed for second-order uncertain plants using equivalent control approach to improve the performance of control systems. A Proportional + Integral + Derivative (PID) sliding surface is used for the sliding mode. The sliding mode control law is derived using direct Lyapunov stability approach and asymptotic stability is proved theoretically. The performance of the closed-loop system is analysed through an experimental application to an electromechanical plant to show the feasibility and effectiveness of the proposed second-order sliding mode control and factors involved in the design. The second-order plant parameters are experimentally determined using inputoutput measured data. The results of the experimental application are presented to make a quantitative comparison with the traditional (first-order) sliding mode control (SMC) and PID control. It is demonstrated that the proposed 2-SMC system improves the performance of the closed-loop system with better tracking specifications in the case of external disturbances, better behavior of the output and faster convergence of the sliding surface while maintaining the stability. © 2010 ISA. Published by Elsevier Ltd. All rights reserved.
Ozer H.T.,Ukurova University |
Ozbalkan Z.,Ankara Numune Research and Education Hospital
International Journal of Clinical Rheumatology | Year: 2010
Over the last decade, TNF-α antagonists became the most powerful tools for controlling patient suffering from a number of rheumatic diseases. Infliximab, etanercept and adalimumab can induce remission and prevent both clinical and radiological disease progression in rheumatoid arthritis with significant improvement in patients symptoms, function and quality of life. They improve joint symptoms and significantly retard radiographic progression in psoriatic arthritis. TNF-α antagonists have been demonstrated to reduce disease activity, retard radiologic progression and increase quality of life in ankylosing spondylitis patients. Long-term follow-up studies demonstrated sustained efficacy and acceptable safety profiles that were comparable in rheumatoid arthritis, ankylosing spondylitis and psoriatic arthritis. Etanercept is the only US FDA-approved TNF antagonist for juvenile rheumatoid arthritis. TNF-α antagonists may improve some clinical manifastations of Behets disases, including uveitis. Tuberculosis and some other granulomatous infections are likely to occur more frequently among patients treated with monoclonal antibodies than among those treated with soluble TNF receptors. During the first 6 years of therapy, no overall elevation of cancer risk was observed with any of the three TNF antagonists. TNF antagonists were not associated with any major further increase in the already increased lymphoma risk in rheumatoid arthritis. Frequent monitoring of serum transaminase levels and viral load was suggested for TNF antagonist use in hepatitis B and C infection. They might reduce some important costs to the patients; however, studies with additional detailed cost calculations are required. © 2010 Future Medicine Ltd.
Efendiolu A.,Ukurova University |
Yanpar Yelken T.,Mersin University
Computers and Education | Year: 2010
The purpose of this study was to investigate the effects of two different methods on primary school teacher candidates' academic achievements and attitudes toward computer-based education, and to define their views on these methods. Both the first experimental group, programmed instruction (PI), and the second experimental group, meaningful learning (ML), included 36 students separately. While a significant difference was found between the groups regarding academic achievements, no significant difference was found between the groups' attitude scores. There was no significant difference between the academic achievements of the students according to their genders in both groups. In addition, while there was no significant difference between the pre-test and post-test attitudes of students in the PI group, a significant difference was determined in the ML group. Generally, in the PI group, students considered the method effective but boring. Besides, students in the ML group had positive views on the method. © 2010 Elsevier Ltd. All rights reserved.
Ersoz Kaya I.,Mersin University |
Ibrikci T.,Ukurova University |
Ersoy O.K.,Purdue University
Expert Systems with Applications | Year: 2011
Recognizing that many intrinsically disordered regions in proteins play key roles in vital functions and also in some diseases, identification of the disordered regions has became a demanding process for structure prediction and functional characterization of proteins. Therefore, many studies have been motivated on accurate prediction of disorder. Mostly, machine learning techniques have been used for dealing with the prediction problem of disorder due to the capability of extracting the complex relationships and correlations hidden in large data sets. In this study, a novel method, named Border Vector Detection and Extended Adaptation (BVDEA) was developed for predicting disorder as an alternative accurate classifier. The classifier performs the predictions by using three types of structural features belonging to proteins. For attesting the performance of the method, three computational learning techniques and eleven specific tools were used for comparison. Training was executed based on the data by 5-fold cross validation. When compared with the two learning methods of LVQ and BVDA, the proposed method gives the best success on classification. The BVDEA also provides faster and more robust learning as compared to the others. The new method provides a significant contribution to predicting disorder and order regions of proteins. © 2011 Elsevier Ltd. All rights reserved.