Sharif Digital Repository

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... 

Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES). To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and small-world structure, estimated with clustering coefficient, modularity, global efficiency, and small-worldness metrics, respectively. Yet the number of PNES attacks per month correlated with a... 

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... 

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... 

This paper presents an investigation of the dynamics of two coupled non-identical FitzHugh-Nagumo neurons with delayed synaptic connection. We consider coupling strength and time delay as bifurcation parameters, and try to classify all possible dynamics which is fairly rich. The neural system exhibits a unique rest point or three ones for the different values of coupling strength by employing the pitchfork bifurcation of non-trivial rest point. The asymptotic stability and possible Hopf bifurcations of the trivial rest point are studied by analyzing the corresponding characteristic equation. Homoclinic, fold, and pitchfork bifurcations of limit cycles are found. The delay-dependent stability... 

A hallmark of more advanced models is their higher details of trunk muscles represented by a larger number of muscles. The question is if in reality we control these muscles individually as independent agents or we control groups of them called "synergy". To address this, we employed a 3-D biomechanical model of the spine with 18 trunk muscles that satisfied equilibrium conditions at L4/5, with different cost functions. The solutions of several 2-D and 3-D tasks were arranged in a data matrix and the synergies were computed by using non-negative matrix factorization (NMF) algorithms. Variance accounted for (VAF) was used to evaluate the number of synergies that emerged by the analysis, which... 

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.... 

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... 

A novel hybrid algorithm based on a genetic algorithm and particle swarm optimization to design a fuzzy neural network, named self-organizing fuzzy neural network based on GA and PSO (SOFNNGAPSO), to implement Takagi-Sugeno (TS) type fuzzy models is proposed in this paper. The proposed algorithm, as a new hybrid algorithm, consists of two phases. A tuning based on TS's fuzzy model is applied to identify the fuzzy structure, and also a fuzzy cluster validity index is utilized to determine the optimal number of clusters. To obtain a more precision model, GA and PSO are performed to conduct fine tuning for the obtained parameter set of the premise parts and consequent parts in the... 

Laccase production by indigenous fungus, Phanerochaete chrysosporium, requires solving optimal problems to determine the maximum production of the enzyme within a definite time period and conditions specified in the solid-state fermentation process. For this purpose, parallel to response surface methodology, an analytical approach has been proposed based on the advanced concepts of Poisson geometry and Lie groups, which lead to a system of the Hamiltonian equations. Despite the dating of the Hamiltonian approach to solving biological problems, the novelty of this paper is based on the expression of a Hamiltonian system in notions of Poisson geometry, Lie algebras and symmetry groups and... 

Biomechanical modeling approaches require body posture to evaluate the risk of spine injury during manual material handling. The procedure to measure body posture via motion-analysis techniques as well as the subsequent calculations of lumbosacral moments and spine loads by, respectively, inverse-dynamic and musculoskeletal models are complex and time-consuming. We aim to develop easy-to-use yet accurate artificial neural networks (ANNs) that predict 3D whole-body posture (ANNposture), segmental orientations (ANNangle), and lumbosacral moments (ANNmoment) based on our measurements during load-handling activities. Fifteen individuals each performed 135 load-handling activities by reaching (0... 

Research question: Would there be differences in muscle activation between healthy subjects’ (HS) dominant leg and transfemoral amputees’ (TFA) intact-leg/contralateral-limb (IL) during normal transient-state walking speed? Methods: The muscle activation patterns are obtained by calculating the linear envelope of the EMG signals for each group. The activation patterns/temporal changes are compared between-population using statistical parametric mapping (SPM). Results: Individual muscle activity showed significant differences in all muscles except vastus lateralis (VL), semitendinosus (SEM) and tensor fascia latae (TFL) activities. Significance: The information could be used by the therapists... 

Two artificial neural networks (ANNs) are constructed, trained, and tested to map inputs of a complex trunk finite element (FE) model to its outputs for spinal loads and muscle forces. Five input variables (thorax flexion angle, load magnitude, its anterior and lateral positions, load handling technique, i.e., one- or two-handed static lifting) and four model outputs (L4-L5 and L5-S1 disc compression and anterior-posterior shear forces) for spinal loads and 76 model outputs (forces in individual trunk muscles) are considered. Moreover, full quadratic regression equations mapping input-outputs of the model developed here for muscle forces and previously for spine loads are used to compare the... 

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... 

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 paper a variational framework for joint segmentation and motion estimation is employed for inspecting heart in Cine MRI sequences. A functional including Mumford-Shah segmentation and optical flow based dense motion estimation is approximated using the phase-field technique. The minimizer of the functional provides an optimum motion field and edge set by considering both spatial and temporal discontinuities. Exploiting calculus of variation principles, multiple partial differential equations associated with the Euler-Lagrange equations of the functional are extracted, first. Next, the finite element method is used to discretize the resulting PDEs for numerical solution. Several... 

Density functional theory (DFT) calculations were performed at the B3LYP level with a 6-311++G(d,p) basis set to systematically explore the geometrical multiplicity and binding strength for complexes formed by Li+, Na+, and K+ with cytidine and 2′-deoxycytidine. All computational studies indicate that the metal ion affinity (MIA) decreases from Li+ to Na+ and K+ for cytosine nucleosides. For example, for cytidine the affinity for the above metal ions are 79.5, 55.2, and 41.8 and for 2′-deoxycytidine, 82.8, 57.4, and 42.2 kcal/mol, respectively. It is also interesting to mention that linear correlations between calculated MIA values and the atomic numbers (Z) of the above metal ions were... 

A quantitative structure-mobility relationship was developed to accurately predict the electrophoretic mobility of organic acids. The absolute electrophoretic mobilities (μ0) of a diverse dataset consisting of 115 carboxylic and sulfonic acids were investigated. A set of 1195 zero- to three-dimensional descriptors representing various structural characteristics was calculated for each molecule in the dataset. Classification and regression trees were successfully used as a descriptor selection method. Four descriptors were selected and used as inputs for adaptive neuro-fuzzy inference system. The root mean square errors for the calibration and prediction sets are 1.61 and 2.27, respectively,...