Sharif Digital Repository

Levodopa [L-3, 4-dihydroxyphenylalanine, or L-DOPA] is an important neurotransmitter used for the treatment of neural disorders such as Parkinson's disease. Abnormal L-Dopa concentrations in biological fluids can be used for the evaluation of such diseases. In this work, a rapid and sensitive method for L-DOPA detection has been reported which is based on in situ formation of polylevodopa nanoparticles. Under alkaline conditions, L-DOPA is spontaneously oxidized to its quinone derivative and shows fluorescence properties. The fluorescence signal of the oxidation product has been monitored and used for the determination of L-DOPA in the presence of dopamine, uric acid, ascorbic acid and other... 

Current studies show a growing interest on transformation induced plasticity (TRIP) in austenitic steels. Most researches are based on inducing plasticity via tensile stresses, so it seems interesting to accomplish these researches by compressive stresses. Rolling process is a suitable choice to make compressive stresses. In present work, the effects of a wide range of rolling strains (5%-60%) at 0 and 24 °C on the austenite to martensite transformation were investigated on high-alloy austenitic steel. For this purpose, XRD, hardness test and magnetic measurements were used. Results show that by increasing the amount of rolling strain, transformation of austenite to martensite generally... 

A series of novel pseudopeptides contained coumarin skeleton were synthesized through the Ugi-four-component reaction. The 3-substituted coumarin-3-carboxamides were formed through reaction of benzaldehyde derivatives, anilines, coumarin-3- carboxylic acid and isocyanides with high yields and high bond-forming efficiency at room temperature. These novel amidated coumarins exhibit brilliant fluorescence in range of 535-547 nm in chloroform  

A new robust AQM strategy for dynamically varying TCP/AQM networks is proposed and its performance is investigated through computer simulations in MATLAB and ns-2 environments. The developed AQM is designed based on coefficient diagram method (CDM), which is a new indirect pole placement method that considers the speed, stability and robustness of the closed loop system in terms of time domain specifications. Simulation results indicate that the new method (CDM-AQM) performs very well for network variations both in topology and traffic. Besides, a new adaptive controller based on CDM as an AQM method is introduced. In the developed adaptive AQM (ACDM), the output feedback pole placement is... 

Packet-level observations show that the TCP/RED congestion control systems exhibit complex non-periodic oscillations which vary with the network/RED parameter variations. In this paper, it is investigated whether such complex behaviors are due to nonlinear deterministic chaotic dynamics or do they originate from nonlinear stochastic dynamics. To do this, various methods of linear and nonlinear time series analyses have been applied to the packet-level data gathered from a typical network simulated in ns-2. The results of the analysis for a wide range of variations in averaging weight of RED (as the most important bifurcation factor in TCP/RED networks) show that such behaviors are not due to... 

Predictive functional control (PFC) as a new active queue management (AQM) method in dynamic TCP networks supporting explicit congestion notification (ECN) is proposed. The ability of the controller in handling system delay along with its simplicity and low computational load makes PFC a privileged AQM method in the high speed networks. Besides, considering the disturbance term (which represents model/process mismatches, external disturbances, and existing noise) in the control formulation adds some level of robustness into the PFC-AQM controller. This is an important and desired property in the control of dynamically-varying computer networks. In this paper, the controller is designed based... 

In this paper, a new effective and computationally reduced method for congestion control in high speed dynamic computer networks is introduced. The controller is designed using the well-known predictive functional control (PFC) scheme and an ARMarkov model representation that considers the system delay explicitly. Use of the multi-step-ahead predictive ARMarkov model structure within the PFC results in a simple algebraic control law that does not require recursive model output computation in the so-called prediction horizon performed in the other Model Predictive Controllers (MPC). This combination not only reduces the required computational load, but the accumulative error due to the model... 

In this paper, a mathematical model and control theoretical framework for designing AQM controllers in networks supporting TCP Vegas is introduced. We have emphasized on a modified TCP Vegas algorithm that can respond to congestion signals through explicit congestion notification (ECN). The overall nonlinear delayed differential equations of the dynamics model of closed loop system have been derived based on TCP Vegas model. The model is then linearized to derive a transfer function representation between the packet marking probability and the bottleneck router queue length as the input and output of the modified TCP Vegas/AQM system. The model properties have been then examined especially... 

The performance of a new robust AQM strategy for dynamically varying TCP/AQM networks is proposed. Network variations include in both network topology and traffic variations. The developed AQM is designed based on Coefficient Diagram Method (CDM), which is a new indirect pole placement method that considers the speed, stability and robustness of the closed loop system in terms of time domain specifications. Simulation results show different features of the proposed method. ©2005 IEEE  

Ultrasonic motors (USM's) possess heavy nonlinear and load dependent characteristics such as dead-zone and saturation reverse effects, which vary with driving conditions. In this paper, behavior of an ultrasonic motor is modeled using Hammerstein model structure and experimental measurements. Also, model predictive controllers are designed to obtain precise USM position control. Simulation results indicate improved performance of the motor for both set point tracking and disturbance rejection. © 2005 ISA - The Instrumentation, Systems, and Automation Society  

Ultrasonic motors (USM) possess heavy nonlinear, and load dependent characteristics such as dead-zone and saturation reverse effects, which vary with driving conditions. These properties have made the position/velocity control of USM a difficult and challenging task. In this paper, a generalized model predictive (GPC) controller for precise USM position control is suggested. Simulation results indicate improved performance of the motor for both set point tracking and disturbance rejection. Since the motor and the controller both are of type one, the applied saturation would cause in wind up phenomenon. This drawback is removed by implementing the Quadratic GPC controller. © 2004 IEEE  

Ultrasonic motors (USM) possess heavy nonlinear and load dependent characteristics of ultrasonic motors (USM) such as dead-zone and saturation reverse effects, which vary with driving conditions. In this paper, behaviour of an ultrasonic motor is modelled using Hammerstein model structure and experimental measurements. Simulation results show the good matching between the developed model and experimental measurements. © 2004 IEEE  

Biogenic amines (BAs) are known as substantial indicators of the quality and safety of food. Developing rapid and visual detection methods capable of simultaneously monitoring BAs is highly desired due to their harmful effects on human health. In the present study, we have designed a multicolor sensor array consisting of two types of gold nanostructures (i.e., gold nanorods (AuNRs) and gold nanospheres (AuNSs)) for the discrimination and determination of critical BAs (i.e., spermine (SM), tryptamine (TT), ethylenediamine (EA), tyramine (TR), spermidine (SD), and histamine (HT)). The design principle of the probe was based on the metallization of silver ions on the surface of AuNRs and AuNSs... 

Considering the crucial role of biothiols in many biological processes, which turns them into highly valuable biomarkers for the early diagnosis of various diseases, the development of an affordable, sensitive and portable probe for the identification and discrimination of these compounds is of great importance. Herein, we developed a ratiometric fluorescent (RF) sensor array with a wide color emissive variation, on a bacterial cellulose (BC) nanopaper substrate for the visual discrimination of biothiols. To this aim, RF sensing elements including N-acetyl l-cysteine capped green CdTe quantum dots-rhodamine B (GQDs-RhB) and red CdTe QDs-carbon dots (RQDs-CDs) at two different NaOH... 

Discrimination of chiral targets is generally achieved with chiral nanomaterials. However, the limited number of intrinsic chiral nanostructures as well as their complex synthesis procedure has led to the production of chirality-induced nanomaterials as alternatives. Chirality can be induced in nanomaterials by either chirality transfer or the formation of chiral assemblies. Using the latter approach, in this work, we have provided chiral supramolecular assemblies of CdTe quantum dots (QDs) from achiral starting materials. CTAB-QD assemblies showed chiroptical activities, and their orange emission in combination with the blue emission of carbon dots was utilized as a ratiometric chiral... 

A new approach for optimal reserve determination and cost allocation in the pool-based and disaggregated market model using a well-being framework is presented in this paper. In the proposed method, customers have the chance to specify the risk level which they are willing to accept. Firstly, the energy market is cleared, and afterwards the reserve market is cleared such that the required risk levels of different customers are satisfied. Then, according to the required risk levels and the provided reserve, the cost of reserve is allocated between the different customers with different reliability requirements. For fairly managing the shortage between different customers in the real time... 

In this paper, a new method is introduced for identification of transformer winding fault through transfer function analysis. For this analysis, vector fitting and probabilistic neural network are used. The results of transfer functions estimation through vector fitting are employed for training of neural network, and consequently, probabilistic neural network is used for classification of faults. The required data for fault type identification are obtained by measurements on two groups of transformers (one is a classic 20 kV transformer, and the other is a model transformer) under intact condition and under different fault conditions (axial displacement, radial deformation, disc space...