Sharif Digital Repository

Background: Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. Methods: In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for... 

Nonlinear propagation has been demonstrated to have a significant impact on ultrasound imaging. An efficient computational algorithm is presented to simulate nonlinear ultrasound propagation through layered liquid and tissue-equivalent media. Results are compared with hydrophone measurements. This study was undertaken to investigate the role of nonlinear propagation in high frequency ultrasound micro-imaging. The acoustic field of a focused transducer (20 MHz centre frequency, f-number 2.5) was simulated for layered media consisting of water and tissue-mimicking phantom, for several wide-bandwidth source pulses. The simulation model accounted for the effects of diffraction, attenuation and... 

In this paper, we follow two control tasks in a leader following frame with undirected network and local communications. As the first goal, distributed behavioral imitation, which is necessary to fit agents with complicated motion equations in kinematic frames, is discussed. Providing real agents with behavioral controller makes them capable to act as a kinematic particle. The second goal is to design an active leading strategy for the LA to move the group on a predefined path. Both problems can be mathematically modeled in an affine form, which is the reason behind using a unique adaptive controller to solve them. The controller is based on a neuro-fuzzy structure with critic-based leaning... 

In presence of obstacles, inter-agent pulling actions must be bounded. In this case, to remain connected to the group, the leader-agent (LA) must perform an active leading strategy. In this paper, an active leading algorithm is proposed which monitors the neighborhood of the LA and adjusts its velocity. The algorithm is based on the ant colony optimization (ACO) technique. As a real time optimization package, the ACO algorithm maximizes influence of the LA on the group, leading to fast flocking. Comparison with another optimization method is provided as well. Simulations show that the algorithm is successful and cost effective  

The urine formation and excretion system have long been of interest for mathematicians and physiologists to elucidate the obscurities within the process happens in renal tissue. In this study, a novel three-dimensional approach is utilized for modeling the urine concentrating mechanism in rat renal outer medulla which is essentially focused on demonstrating the significance of tubule's architecture revealed in anatomic studies and physiological literature. Since nephrons and vasculatures work interdependently through a highly structured arrangement in outer medulla which is dominated by vascular bundles, a detailed functional unit is proposed based on this specific configuration.... 

In this study, a dielectrophoresis field-flow fractionation device was analyzed using a numerical simulation method and the behaviors of a set of different cells were investigated. By reducing the alternating current frequency of the electrodes from the value used in the original setup configuration and increasing the number of exit channels, total discrimination in cell trajectories and subsequent separation of four cell types were achieved. Cells were differentiated based on their size and dielectric response that are represented in their real part of Clausius–Mossotti factor at different frequencies. A number of novel designs were also proposed based on the original setup configuration.... 

Steady blood flow through a circular artery with rigid walls is studied by COSSERAT Continuum Mechanical Approach. To obtain the additional viscosities coefficients, feed forward multi-layer perceptron (MLP) type of artificial neural networks (ANN) and the results obtained in previous empirical works is used. The governing filed equations are derived and solution to the Hagen-Poiseuilli flow of a COSSERAT fluid in the artery is obtained analytically by Homotopy Perturbation Method (HPM) and numerically using finite difference method. Comparison of analytical results with numerical ones showed excellent agreement. In addition microrotation and the velocity profile along the radius are... 

The study of electrocardiogram (ECG) waveform amplitudes, timings and patterns has been the subject of intense research, for it provides a deep insight into the diagnostic features of the heart's functionality. In some recent works, a Bayesian filtering paradigm has been proposed for denoising and compression of ECG signals. In this paper, it is shown that this framework may be effectively used for ECG beat segmentation and extraction of fiducial points. Analytic expressions for the determination of points and intervals are derived and evaluated on various real ECG signals. Simulation results show that the method can contribute to and enhance the clinical ECG beat segmentation performance. ©... 

Equivariant adaptive separation via independence (EASI) is one of the most successful algorithms for blind source separation (BSS). However, the user has to choose non-linearities, and usually simple (but non-optimal) cubic polynomials are applied. In this paper, the optimal choice of these non-linearities is addressed. We show that this optimal non-linearity is the output score function difference (SFD). Contrary to simple non-linearities usually used in EASI (such as cubic polynomials), the optimal choice is neither component-wise nor fixed: it is a multivariate function which depends on the output distributions. Finally, we derive three adaptive algorithms for estimating the SFD and... 

In this paper, an efficient approach for ultrasonic object segmentation with special application for left ventricle segmentation in echocardiography images is proposed. At first, an efficient hybrid trend for ultrasonic image edge detection is suggested. Then, a modified level set approach is introduced based on the extracted edges and the computed probabilistic map as the stopping criteria for the contour evolution. Both synthetic and clinical images are utilized as validation measures with respect to the prior techniques which indicate outperform results quantitatively and qualitatively. Left ventricle segmentation using proposed method illustrates expert-approved performance, providing a... 

In this paper, an adaptive multi-model sliding mode controller for robotic manipulators is presented. By using the multiple models technique, the nominal part of the control signal is constructed according to the most appropriate model at different environments. Adaptive single-input-single-output (SISO) fuzzy systems or radial basis function (RBF) neural networks, regarding their functional equivalence property, are used to approximate the discontinuous part of control signal; control gain, in a classical sliding mode controller. The key feature of this scheme is that prior knowledge of the system uncertainties is not required to guarantee the stability. Also the chattering phenomenon in... 

In this work, the 3D proton dose profile is calculated in a homogenous water phantom using a Monte Carlo application developed with the Geant4 toolkit. The effect of the ridge filter material (for SOBP widths of 6, 9 and 12 cm) on the homogeneity of the dose distribution, secondary neutron production and beam efficiency are investigated in a single ring wobbling irradiation system. The energy spectrum of secondary neutrons per primary proton at various locations around the phantom surface is calculated. The simulation revealed that most of the produced neutrons are released at slight angles which enable them to reach the patient and consequently to be hazardous. Also, the homogeneity of the... 

Response surface methodology was used to investigate the effects of operating parameters such as impeller speed, binder mass and granulation time on the average size of granules produced in a lab scale conical high shear granulator. Two quadratic models were proposed to express granule mean size as a function of impeller speed and binder mass as well as impeller speed and granulation time. It was found out that in the studied domain, the influence of each parameter on granule size differs from one another. While increasing binder mass at constant quantity of powder increased the average size linearly, increasing impeller speed changed the mean size in accordance with quadratic trend. The... 

The finite element method and molecular dynamics simulations are used for modeling the AFM microcantilever dynamics and the tip-sample interaction forces, respectively. Molecular dynamics simulations are conducted to calculate the tip-sample force data as a function of tip height at different lateral positions of the tip with respect to the sample. The results demonstrate that in the presence of nonlinear interaction forces, higher eigenmodes of the microcantilever are excited and play a significant role in the tip and sample elastic deformations. Using comparisons between the results of FEM and lumped models, how some aspects of the system behavior can be hidden when the point-mass model is... 

Multivariate curve resolution-particle swarm optimization (MCR-PSO) algorithm is proposed to exploit pure chromatographic and spectroscopic information from multi-component hyphenated chromatographic signals. This new MCR method is based on rotation of mathematically unique PCA solutions into the chemically meaningful MCR solutions. To obtain a proper rotation matrix, an objective function based on non-fulfillment of constraints is defined and is optimized using particle swarm optimization (PSO) algorithm. Initial values of rotation matrix are calculated using local rank analysis and heuristic evolving latent projection (HELP) method. The ability of MCR-PSO in resolving the chromatographic... 

A signaling pathway is a sequence of proteins and passenger molecules that transmits information from the cell surface to target molecules. Understanding signal transduction process requires detailed description of the involved pathways. Several methods and tools resolved this problem by incorporating genomic and proteomic data. However, the difficulty of obtaining prior knowledge of complex signaling networks limited the applicability of these tools. In this study, based on the simulation of signal flow in signaling network, we introduce a method for determining dominant pathways and signal response to stimulations. The model uses topology-weighted transit compartment approach and comprises... 

Simulating signal transduction in cellular signaling networks provides predictions of network dynamics by quantifying the changes in concentration and activity-level of the individual proteins. Since numerical values of kinetic parameters might be difficult to obtain, it is imperative to develop non-parametric approaches that combine the connectivity of a network with the response of individual proteins to signals which travel through the network. The activity levels of signaling proteins computed through existing non-parametric modeling tools do not show significant correlations with the observed values in experimental results. In this work we developed a non-parametric computational... 

In this investigation, a systematic sequential intelligent system is proposed to provide the surgeon with an estimation of the state of the tool-tissue interaction force in laparoscopic surgery. To train the proposed intelligent system, a 3D model of an in vivo porcine liver was built for different probing tasks. To capture the required knowledge, three different geometric features, i.e. Y displacement of the nodes on the upper surface and slopes on the closest node to the deforming area of the upper edge in both X-. Y and Z-. Y planes, were extracted experimentally. The numerical simulations are conducted in three independent successive stages. At the first step, a well-known... 

A multi-item multiperiod inventory control model is developed for known-deterministic variable demands under limited available budget. Assuming the order quantity is more than the shortage quantity in each period, the shortage in combination of backorder and lost sale is considered. The orders are placed in batch sizes and the decision variables are assumed integer. Moreover, all unit discounts for a number of products and incremental quantity discount for some other items are considered. While the objectives are to minimize both the total inventory cost and the required storage space, the model is formulated into a fuzzy multicriteria decision making (FMCDM) framework and is shown to be a... 

Control problem in a biological system is the problem of finding an interventional policy for changing the state of the biological system from an undesirable state, e.g. disease, into a desirable healthy state. Boolean networks are utilized as a mathematical model for gene regulatory networks. This paper provides an algorithm to solve the control problem in Boolean networks. The proposed algorithm is implemented and applied on two biological systems: T-cell receptor network and Drosophila melanogaster network. Results show that the proposed algorithm works faster in solving the control problem over these networks, while having similar accuracy, in comparison to previous exact methods. Source...