Sharif Digital Repository

Background: Small scale robotics have attracted growing attention for the prospect of targeting and accessing cell-sized sites, necessary for high precision biomedical applications and drug/gene delivery. The loss of controlled gene therapy, inducing systemic side effects and reduced therapeutic efficiency, can be settled utilizing these intelligent carriers. Methods: Newly proposed solutions for the main challenges of control, power supplying, gene release and final carrier extraction/degradation have shifted these smart miniature robots to the point of being employed for practical applications of transferring oligonucleotides (pDNA, siRNA, mRNA, etc.) in near future. Conclusion: In this... 

We consider magnetic actuation and control of a spherical neutrally buoyant magnetic microrobot via magnetic coil setups and seek to design an optimal controller to reduce the required energy and coils’ currents. We showed that in currently employed setups, where the actuation frequency is few tens of Hertz, the nonlinear dynamics of the system can be well approximated by a set of linear constrained ones. The approximated model is obtained by consciously overlooking the rotational dynamics and the inertia terms in translational dynamics. We acquired the linear quadratic regulation (LQR) controller for the approximated model which is a constrained time-varying system. Finally, 3D manipulation... 

A number of HZSM-5 catalysts modified with 5 wt% Mg, Na, Zr, and Al as well as others modified with 5-60 wt% Zn prepared by wet impregnation. These materials were characterized by the NH3-TPD, XRF, and XRD analyses and tested in a slurry reactor to determine their activities in dehydration of methanol solution in kerosene. Reactions were carried out at 230°C and 19 bar for 4 h of residence time in the reactor. Results showed that in the first series, the catalyst modified with Zr and in the second series, the one modified with 10 wt% Zn led to the highest methanol conversion. It was deduced that elimination of strong acid sites and partial replacement of active cations in the HZSM-5 zeolite... 

In this paper we analyses the energy consumption of well known family of asynchronous circuits and present a new methodology for energy estimation of these circuits at intermediate-level of abstraction. Energy estimation is performed by simulating the intermediate format of the design. The number of Read and Write accesses on the ports of the concurrent processes are counted by analyzing the conditional and computational portion during the simulation which is the base of our estimation methodology. Our proposed power estimation scheme is faster than usual post-synthesis power estimation by an order of 9, while the estimated power resides in a boundary of 11% total imprecision. © 2007 IEEE  

NoC is an efficient on-chip communication architecture for SoC architectures. It enables integration of a large number of computational and storage blocks on a single chip. NoCs have tackled the SoCs disadvantages and are scalable. In this paper, we compare two popular NoC topologies, i.e., mesh and torus, in terms of different figures of merit e.g., latency, power consumption, and power/throughput ratio under different routing algorithms and two common traffic models, uniform and hotspot. To the best of our knowledge, this is the first effort in comparing mesh and torus topologies under different routing algorithms and traffic models with respect to their performance and power consumption.... 

Biosensors could be used as digital devices to measure the sample infield. Consequently, computational programming along with experimental achievements are required. In this study, a novel biosensor/artificial neural network (ANN) integrated system was developed. Poly (3,4-ethylenedioxy-thiophene)(PEDOT), graphene oxide nano-sheets (GONs) and laccase (Lac) were used to construct a biosensor. The simple and one-pot process was accomplished by electropolymerizing 3,4-ethylenedioxy-thiophene (EDOT) along with GONs and Lac as dopants on glassy carbon electrode. Scanning electron microscopy (SEM) and electrochemical characterization were conducted to confirm successful enzyme entrapment. The... 

Resection of the epilepsy foci is the best treatment for more than 15% of epileptic patients or 50% of patients who are refractory to all forms of medical treatment. Accurate mapping of the locations of epileptic neuronal networks can result in the complete resection of epileptic foci. Even though currently electroencephalography is the best technique for mapping the epileptic focus, it cannot define the boundary of epilepsy that accurately. Herein we put forward a new accurate brain mapping technique using superparamagnetic nanoparticles (SPMNs). The main hypothesis in this new approach is the creation of super-paramagnetic aggregates in the epileptic foci due to high electrical and... 

This paper scrutinizes the magnetic field effect to deliver the superparamagnetic nanoparticles (SPMNs) through the Blood Brain Barrier (BBB). Herein we study the interaction between the nanoparticle (NP) and BBB membrane using Molecular Dynamic (MD) techniques. The MD model is used to enhance our understanding of the dynamic behavior of SPMNs crossing the endothelial cells in the presence of a gradient magnetic field. Actuation of NPs under weak magnetic field offers the great advantage of a non-invasive drug delivery without the risk of causing injury to the brain. Furthermore, a weak magnetic portable stimulator can be developed using low complexity prototyping techniques. Based on MD... 

Nowadays, nanoparticles (NPs) are used in a variety of biomedical applications including brain disease diagnostics and subsequent treatments. Among the various types of NPs, magnetic nanoparticles (MNPs) have been implemented by many research groups for an array of life science applications. In this paper, we studied MNPs controlled delivery into the endothelial cells using a magnetic field. Dynamics equations of MNPs were defined in the continuous domain using control theory methods and were applied to crossing the cell membrane. This study, dedicated to clinical and biomedical research applications, offers a guideline for the generation of a magnetic field required for the delivery of... 

Multigeneration systems (MGSs) driven by renewable sources are proved as cutting-edge technologies for multiple productions purposes to curb greenhouse gas emissions. With this regard, a novel geothermal-based MGS is proposed to produce multiple commodities of cooling, heating, power, and hydrogen, simultaneously, using liquefied natural gas (LNG) as cold energy recovery. The system is composed of an organic Rankine cycle (ORC), an ejector refrigeration cycle (ERC), an LNG power generation system, and a proton exchange membrane (PEM) electrolyzer system. To demonstrate the feasibility of the proposed MGS, energy, exergy, and exergoeconomic analysis are employed as the most effective tools... 

Asynchronous circuits have many advantages vs synchronous design styles like high performance and lower power consumption; however, there is a drawback of big overhead in handshake circuitry of these circuits. In this paper, we have reduced the amount of these extra circuits by take advantage of some compiler techniques. The compiler methods can be used innovatively to improve the synthesis results in terms of both power consumption and area, since these code motions lead to removing of completion detection and validity check parts of asynchronous designs. To the best of our knowledge this is the first effort in using the compiler pre-synthesis optimizations in asynchronous circuits to... 

Severe plastic deformation methods such as severe shot peening are used in order to improve mechanical properties of the components by surface microstructure nanocrystallization. Severe shot peening is one of the popular mechanical surface treatments generally aimed at generating nanograined layer and compressive residual stress close to the surface. Moreover, artificial neural network has been used as an efficient approach to predict and optimize the engineering problems. In present study effects of conventional and severe shot peening on cast iron were modelled by means of artificial neural networks and they were compared. The obtained results indicate that severe shot peening has superior... 

In the recent years a great attention of research deals with different physical and biological aspects of the BBB structure, a robust shield that separates the blood and brain, a recent research held by the authors of this paper has focused on figuring out computing the diffusion coefficient of endothelial cell membrane. In this study, the major efforts have been concentrated on calculating a standardized measure for the amount of permeability and diffusion of this barrier. As a result, this work is dedicated to molecular dynamics (MD) simulation of calculating the interaction force between nano-particle and BBB membrane. data is recorded by using steered molecular dynamics simulation and... 

Epilepsy is the most common neurological disorder that is known with uncontrolled seizure. Around 30% of patients with epilepsy resist to all forms of medical treatments and therefore, the removal of epileptic brain tissue is the only solution to get these patients free from chronical seizures. The precise detection of an epileptic zone is key to its treatment. In this paper, we propose a method of epilepsy detection using brain magnetic field. The possibility of superparamagnetic nanoparticle (SPMN) as sensors for the detection of the epileptic area inside the brain is investigated. The aggregation of nanoparticles in the weak magnetic field of epileptic brain is modeled using potential... 

Nowadays, nanoparticles (NPs) are used in a variety of biomedical applications including brain disease diagnostics and subsequent treatments. Among the various types of NPs, magnetic nanoparticles (MNPs) have been implemented by many research groups for an array of life science applications. In this paper, we studied MNPs controlled delivery into the endothelial cells using a magnetic field. Dynamics equations of MNPs were defined in the continuous domain using control theory methods and were applied to crossing the cell membrane. This study, dedicated to clinical and biomedical research applications, offers a guideline for the generation of a magnetic field required for the delivery of... 

Traffic models exert different message flows in a network and have a considerable effect on power consumption through different applications. So a good power analysis should consider traffic models. In this paper we present power and throughput models in terms of traffic rate parameters for the most popular traffic models, i.e. Uniform, Local, HotSpot and First Matrix Transpose (FMT) as a permutational traffic model. We also select Mesh topology as the most prominent NoC topology and validate the presented models by comparing our results against simulation results from Synopsys Power Compiler and Modelsim From the comparison, we show that our modeling approach leads to average error of 2%...