Search results for: A. Yadollah

Authors: Majid Rezayi, Sh. Shahaboddin, HNM E. Mahmud, A. Yadollah, A. Saeid, A. Yatimah

Abstract:

In this study, the adaptive neuro-fuzzy inference system (ANFIS) was applied to obtain the membrane composition model affecting the potential response of our reported polymeric PVC sensor for determining the titanium (III) ions. The performance statistics of the artificial neural network (ANN) and linear regression models for potential slope prediction of membrane composition of titanium (III) ion selective electrode were compared with ANFIS technique. The results show that the ANFIS model can be used as a practical tool for obtaining the Nerntian slope of the proposed sensor in this study.

Keywords: adaptive neuro fuzzy inference, PVC sensor, titanium (III) ions, Nerntian slope

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Authors: Mehdi Dasineh, Yadollah Tariverdi, Marzieh H. Takhti

Abstract:

This paper investigated the relationship between top management turnover with risk volatility, sale volatility and fluctuations in the company's cash depending on the unqualified audit report in Tehran Stock Exchange (TSE). In this study, we examined 104 firms over the period 2009-2014 which were selected from (TSE). There was 624 observed year-company data in this research. Hypotheses of this research have been evaluated by using regression tests for example F-statistical and Durbin-Watson. Based on our sample we found significant relationship between top management replacement and risk volatility, sale Volatility and cash volatility with tendency unqualified audit opinion.

Keywords: top management replacement, risk volatility, sale volatility, cash volatility, unqualified audit opinion

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Authors: Haniye Dehestani, Yadollah Ordokhani

Abstract:

In this work, we present an efficient approach for solving variable-order time-fractional partial differential equations, which are based on Legendre and Laguerre polynomials. First, we introduced the pseudo-operational matrices of integer and variable fractional order of integration by use of some properties of Riemann-Liouville fractional integral. Then, applied together with collocation method and Legendre-Laguerre functions for solving variable-order time-fractional partial differential equations. Also, an estimation of the error is presented. At last, we investigate numerical examples which arise in physics to demonstrate the accuracy of the present method. In comparison results obtained by the present method with the exact solution and the other methods reveals that the method is very effective.

Keywords: collocation method, fractional partial differential equations, legendre-laguerre functions, pseudo-operational matrix of integration

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Authors: Yadollah Hezarjaribi, Mahdie Yari Esboi

Abstract:

In this paper, a novel MEMS capacitive pressure sensor with small size and high sensitivity is presented. This sensor has the separated clamped square diaphragm and the movable plate. The diaphragm material is polysilicon. The movable and fixed plates and mechanical coupling are gold. The substrate and diaphragm are pyrex glass and polysilicon, respectively. In capacitive sensor the sensitivity is proportional to deflection and capacitance changes with pressure for this reason with this design is improved the capacitance and sensitivity with small size. This sensor is designed for low pressure between 0-60 mmHg that is used for medical application such as treatment of an incurable disease called glaucoma. The size of this sensor is 350×350 µm2 and the thickness of the diaphragm is 2µm with 1μ air gap. This structure is designed by intellisuite software. In this MEMS capacitive pressure sensor the sensor sensitivity, diaphragm mechanical sensitivity for polysilicon diaphragm are 0.0469Pf/mmHg, 0.011 μm/mmHg, respectively. According to the simulating results for low pressure, the structure with polysilicon diaphragm has more change of the displacement and capacitance, this leads to high sensitivity than other diaphragms.

Keywords: glaucoma, MEMS capacitive pressure sensor, square clamped diaphragm, polysilicon

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Authors: Reza Ferdousi, Reza Safdari, Yadollah Omidi

Abstract:

Drug-drug interactions (DDIs) are main cause of the adverse drug reactions and nature of the functional and molecular complexity of drugs behavior in human body make them hard to prevent and treat. With the aid of new technologies derived from mathematical and computational science the DDIs problems can be addressed with minimum cost and efforts. Market basket analysis is known as powerful method to identify co-occurrence of thing to discover patterns and frequency of the elements. In this research, we used market basket analysis to identify important bio-elements in DDIs occurrence. For this, we collected all known DDIs from DrugBank. The obtained data were analyzed by market basket analysis method. We investigated all drug-enzyme, drug-carrier, drug-transporter and drug-target associations. To determine the importance of the extracted bio-elements, extracted rules were evaluated in terms of confidence and support. Market basket analysis of the over 45,000 known DDIs reveals more than 300 important rules that can be used to identify DDIs, CYP 450 family were the most frequent shared bio-elements. We applied extracted rules over 2,000,000 unknown drug pairs that lead to discovery of more than 200,000 potential DDIs. Analysis of the underlying reason behind the DDI phenomena can help to predict and prevent DDI occurrence. Ranking of the extracted rules based on strangeness of them can be a supportive tool to predict the outcome of an unknown DDI.

Keywords: drug-drug interaction, market basket analysis, rule discovery, important bio-elements

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Authors: Saba Didarataee, Abbas Ali Khodadadi, Yadollah Mortazavi, Fatemeh Mousavi

Abstract:

Photocatalytic water splitting is one of the most attractive alternative methods for hydrogen evolution. A variety of nanoparticle engineering techniques were introduced to improve the activity of semiconductor photocatalysts. Among these methods, heterojunction formation is an appealing method due to its ability to effectively preventing electron-hole recombination and improving photocatalytic activity. Reaching an optimal ratio of the two target semiconductors for the formation of heterojunctions is still an open question. Considering environmental issues as well as the cost and availability, ZnS and ZnO are frequently studied as potential choices. In this study, first, the ZnS nanoparticle was synthesized in a hydrothermal process; the formation of ZnS nanorods with a diameter of 14-30 nm was confirmed by field emission scanning electron microscope (FESEM). Then two different methods, partial oxidation and chemical precipitation were employed to construct ZnS/ZnO core-shell heterojunction. X-ray diffraction (XRD), BET, and diffuse reflectance spectroscopy (DRS) analysis were carried out to determine crystallite phase, surface area, and bandgap of photocatalysts. Furthermore, the temperature of oxidation was specified by a temperature programmed oxidation (TPO) and was fixed at 510℃, at which mild oxidation occurred. The bandgap was calculated by the Kubelka-Munk method and decreased by increasing oxide content from 3.53 (pure ZnS) to 3.18 (pure ZnO). The optimal samples were determined by testing the photocatalytic activity of hydrogen evolution in a quartz photoreactor with side irradiation of UVC lamps with a wavelength of 254 nm. In both procedures, it was observed that the photocatalytic activity of the ZnS/ZnO composite was sensibly higher than the pure ZnS and ZnO, which is attributed to forming a type-II heterostructure. The best ratio of oxide to sulfide was 0.24 and 0.37 in partial oxidation and chemical precipitation, respectively. The highest hydrogen evolution was 1081 µmol/gr.h, gained from partial oxidizing of ZnS nanoparticles at 510℃ for 30 minutes.

Keywords: heterostructure, hydrogen, partial oxidation, photocatalyst, water splitting, ZnS

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Authors: Parvin Samadi Pakchin, Reza Saber, Hossein Ghanbari, Yadollah Omidi

Abstract:

Ovarian cancer is one of the leading cause of mortality among the gynecological malignancies, and it remains the one of the most prevalent cancer in females worldwide. Tumor markers are biochemical molecules in blood or tissues which can indicates cancers occurrence in the human body. So, the sensitive and specific detection of cancer markers typically recruited for diagnosing and evaluating cancers. Recently extensive research efforts are underway to achieve a simple, inexpensive and accurate device for detection of cancer biomarkers. Compared with conventional immunoassay techniques, electrochemical immunosensors are of great interest, because they are specific, simple, inexpensive, easy to handling and miniaturization. Moreover, in the past decade nanotechnology has played a crucial role in the development of biosensors. In this study, a signal-off electrochemical immunosensor for the detection of CA125 antigen has been developed using chitosan-gold nanoparticles (CS-AuNP) and multi-wall carbon nanotubes (MWCNT) composites. Toluidine blue (TB) is used as redox probe which is immobilized on the electrode surface. CS-AuNP is synthesized by a simple one step method that HAuCl4 is reduced by NH2 groups of chitosan. The CS-AuNP-MWCNT modified electrode has shown excellent electrochemical performance compared with bare Au electrode. MWCNTs and AuNPs increased electrochemical conductivity and accelerate electrons transfer between solution and electrode surface while excessive amine groups on chitosan lead to the effective loading of the biological material (CA125 antibody) and TB on the electrode surface. The electrochemical, immobilization and sensing properties CS-AuNP-MWCNT-TB modified electrodes are characterized by cyclic voltammetry, electrochemical impedance spectroscopy, differential pulse voltammetry and square wave voltammetry with Fe(CN)63−/4−as an electrochemical redox indicator.

Keywords: signal-off electrochemical biosensor, CA125, ovarian cancer, chitosan-gold nanoparticles

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