Sharif Digital Repository

Background: Asymmetric lifting activities are associated with low back pain. Methods: A finite element biomechanical model is used to estimate spinal loads during one- and two-handed asymmetric static lifting activities. Model input variables are thorax flexion angle, load magnitude as well as load sagittal and lateral positions while response variables are L4-L5 and L5-S1 disc compression and shear forces. A number of levels are considered for each input variable and all their possible combinations are introduced into the model. Robust yet user-friendly predictive equations that relate model responses to its inputs are established. Findings: Predictive equations with adequate... 

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... 

We propose a new image recovery method to improve the resolution in microwave imaging applications. Scattered field data obtained from a simplified breast model with closely located targets is used to formulate an electromagnetic inverse scattering problem, which is then solved using the Distorted Born Iterative Method (DBIM). At each iteration of the DBIM method, an underdetermined set of linear equations is solved using our proposed sparse recovery algorithm, IMATCS. Our results demonstrate the ability of the proposed method to recover small targets in cases where traditional DBIM approaches fail. Furthermore, in order to regularize the sparse recovery algorithm, we propose a novel... 

In the present research, ultrasonic-assisted emulsification-microextraction (USAEME) coupled with gas chromatography-mass spectrometry (GC-MS) has been proposed for analysis of thirteen environmental protection agency (EPA) polycyclic aromatic hydrocarbons (PAHs) in aqueous samples. Tetrachloroethylene was selected as extraction solvent. The main parameters of USAEME affecting the efficiency of the method were modeled and optimized using a central composite design (CCD). Under the optimum conditions (9 μL for extraction solvent, 1.15% (w/v) NaCl (salt concentration) and 10min for ultrasonication time), preconcentration factor (PF) of the PAHs was in the range of 500-950. In order to have a... 

Human Brain is one of the most wonderful and complex systems which is designed for ever; A huge complex network composed of neurons as tiny biological and chemical processors which are distributed and work together as a super parallel system to do control and vital activities of human body. Brain learning simulation and hardware implementation is one of the most interesting research areas in order to make artificial brain. One of the researches in this area is Active Learning Method in brief ALM. ALM is an adaptive recursive fuzzy learning algorithm based on brain functionality and specification which models a complex Multi Input Multi Output System as a fuzzy combination of Single Input... 

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... 

The first notable megawatt class wind turbine, which was the pioneer of improvement in the blade performance in large wind turbines, appeared in Vermont. Nowadays, modern wind turbines are using blades with multi-airfoils at different sections. In this study, in order to indicate the best airfoil profile for the optimum performance in different sections of a blade, five popular airfoils, including S8xx, FFA and AH series, were studied. On the large-scale profile, shear stress transport K–ω model was applied for the simulation of horizontal axis wind turbines for different wind speeds. The aerodynamic simulation was accomplished using computational fluid dynamic method, which in turn is based... 

Through the activation process of T cells, actin filaments move from the cell periphery toward the cell center. The moving filaments engage with T cell receptors and thus contribute to transportation of the signaling molecules. To study the connection between the moving actin filaments and T cell receptors, an experiment available in the literature has measured filaments flow velocity passing over a region of confined clusters of receptors. It shows that flow velocity decreases in the proximity of the receptors, and then regains its normal value after traversing the region, suggesting a dissipative friction-like connection. In this work, we develop a minimal theoretical model to re-examine... 

In this paper, we propose a novel method for extracting fiducial points (FPs) of the beats in electrocardiogram (ECG) signals using switching Kalman filter (SKF). In this method, according to McSharry's model, ECG waveforms (P-wave, QRS complex and T-wave) are modeled with Gaussian functions and ECG baselines are modeled with first order auto regressive models. In the proposed method, a discrete state variable called “switch” is considered that affects only the observation equations. We denote a mode as a specific observation equation and switch changes between 7 modes and corresponds to different segments of an ECG beat. At each time instant, the probability of each mode is calculated and... 

Electromyogram signal (EMG) is an electrical manifestation of contractions of muscles. Surface EMG (sEMG) signal collected from the surface of skin has been used in diverse applications. One of its usages is in pattern recognition of hand prosthesis movements. The ability of current prosthesis devices has been generally limited to simple opening and closing tasks, minimizing their efficacy compared to natural hand capabilities. In order to extend the abilities and accuracy of prosthesis arm movements and performance, a novel sEMG pattern recognizing system is proposed. To extract more pertinent information we extracted sEMGs for selected hand movements. These features constitute our main... 

Herein, Kiwi peel activated carbon (AC), Materials Institute Lavoisier (MIL-88B (Fe), and AC/MIL-88B (Fe) composite were synthesized and used as catalysts to degrade Reactive Red 198. The material properties were analyzed by the FTIR, BET-BJH, XRD, FESEM, EDX, TGA, and UV–Vis/DRS. The BET surface area of AC, MIL-88B (Fe) and AC/MIL-88B (Fe) was 1113.3, 150.7, and 199.4 m2/g, respectively. The band gap values (Eg) estimated by Tauc plot method, were obtained 5.06, 4.19 and 3.79 eV for AC, MIL-88B (Fe) and AC/MIL-88B (Fe), respectively. The results indicated that the AC/MIL-88B (Fe) composite had higher photocatalytic activity (99%) than that of pure AC (79%) and MIL-88B (Fe) catalysts (87%).... 

A Takagi-Sugeno adaptive neuro-fuzzy inference system (TSFIS) model is developed and applied to a dataset of wellhead flow-test data for the Resalat oil field located offshore southern Iran, the objective is to assist in the prediction and control of multi-phase flow rates of oil and gas through the wellhead chokes. For this purpose, 182 test data points (Appendix 1) related to the Resalat field are evaluated. In order to predict production flow rate (QL) expressed as stock-tank barrels per day (STB/D), this dataset includes four selected input variables: upstream pressure (Pwh); wellhead choke sizes (D64); gas to liquid ratio (GLR); and, base solids and water including some water-soluble... 

Most slab-on-girder steel bridges have been designed and constructed without seismic resistance consideration; as a result, their members, connections, and more commonly their substructure are not sized and detailed to provide the required ductile response needed during major earthquakes. A ductile seismic retrofit solution proposed in this investigation consist of converting of existing end diaphragms into ductile end diaphragms and replacing the end cross-frames and the lower lateral-braced panels adjacent to the supports by special ductile diaphragms. Consequently, this creates ductile fuses to protect the rest of the super- and substructure. This paper illustrates the typical seismic... 

The flow of non-Newtonian fluids through two-dimensional porous media is analyzed at the pore scale using the smoothed particle hydrodynamics (SPH) method. A fully explicit projection method is used to simulate incompressible flow. This study focuses on a shear-thinning power-law model (n < 1), though the method is sufficiently general to include other stress-shear rate relationships. The capabilities of the proposed method are demonstrated by analyzing a Poiseuille problem at low Reynolds numbers. Two test cases are also solved to evaluate validity of Darcy's law for power-law fluids and to investigate the effect of anisotropy at the pore scale. Results show that the proposed algorithm can... 

Distributed Generation (DG) can help in reducing the cost of electricity to the customer, relieve network congestion, provide environmentally friendly energy close to load centers as well as promote system technical characteristics such as loss reduction, voltage profile enhancement, reserve mitigation and many other factors. Furthermore, its capacity is also scalable and it can provide voltage support at distribution level. The planning studies include penetration level and placement evaluation which are influenced directly by DG type. Most of the previous publications in this field chose one or two preferred parameter as basic objective and implement the optimizations in systems. But due... 

Electromyogram (EMG) signal is an electrical manifestation of muscle contractions. EMG signal collected from surface of the skin, a non-invasive bioelectric signal, can be used in different rehabilitation applications and artificial extremities control. This study has proposed to utilize the surface EMG (SEMG) signal to recognize patterns of hand prosthesis movements. It suggests using an adaptive neuro-fuzzy inference system (ANFIS) to identify motion commands for the control of a prosthetic hand. In this work a hybrid method for training fuzzy system, consisting of back-propagation (BP) and least mean square (LMS) is utilized. Also in order to optimize the number of fuzzy rules, a... 

Cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1), two clinically relevant targets for the immunotherapy of cancer, are negative regulators of T-cell activation and migration. Optimizing the therapeutic response to CTLA-4 and PD-1 blockade calls for a more comprehensive insight into the coordinated function of these immune regulators. Mathematical modeling can be used to elucidate nonlinear tumor–immune interactions and highlight the underlying mechanisms to tackle the problem. Here, we investigated and statistically characterized the dynamics of T-cell migration as a measure of the functional response to these pathways. We used a previously... 

Disease prediction is a well-known classification problem in medical applications. Graph Convolutional Networks (GCNs) provide a powerful tool for analyzing the patients’ features relative to each other. This can be achieved by modeling the problem as a graph node classification task, where each node is a patient. Due to the nature of such medical datasets, class imbalance is a prevalent issue in the field of disease prediction, where the distribution of classes is skewed. When the class imbalance is present in the data, the existing graph-based classifiers tend to be biased towards the major class(es) and neglect the samples in the minor class(es). On the other hand, the correct diagnosis... 

Multivariate curve resolution (MCR) and multivariate clustering methods along with other chemometric methods are proposed to improve the analysis of gas chromatography-mass spectrometry (GC-MS) fingerprints of secondary metabolites in citrus fruits peels. In this way, chromatographic problems such as baseline/background contribution, low S/N peaks, asymmetric peaks, retention time shifts, and co-elution (overlapped and embedded peaks) occurred during GC-MS analysis of chromatographic fingerprints are solved using the proposed strategy. In this study, first, informative GC-MS fingerprints of citrus secondary metabolites are generated and then, whole data sets are segmented to some... 

In this paper, a novel nonlinear joint dynamical model is presented, which is based on a set of coupled ordinary differential equations of motion and a Gaussian mixture model representation of pulsatile cardiovascular (CV) signals. In the proposed framework, the joint interdependences of CV signals are incorporated by assuming a unique angular frequency that controls the limit cycle of the heart rate. Moreover, the time consequence of CV signals is controlled by the same phase parameter that results in the space dimensionality reduction. These joint equations together with linear assignments to observation are further used in the Kalman filter structure for estimation and tracking. Moreover,...