Full Research Paper
Fatemeh Ghafouri; Mohammad Hadi Honarvar; Mohammad Mahdi Jalili
Volume 14, Issue 1 , May 2020, Pages 1-11
Abstract
Minimizing the energy expenditure as well as structure's size and weight is very important in biped walking robots. To achieve this target, a passive controller, which is a combination of spring and linear damper, is added to a biped walker. The important specification of the studied walker is that it ...
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Minimizing the energy expenditure as well as structure's size and weight is very important in biped walking robots. To achieve this target, a passive controller, which is a combination of spring and linear damper, is added to a biped walker. The important specification of the studied walker is that it has two convex soles at the end of the legs as feet, which is jointed to body with a passive revolute joint. Contact point moves on a sole curve. To reduce system's dynamic complexity, pointed mass approach is used. The main purpose of this research is studying the dynamical behavior of this underactuated walker before and after adding controller. In the first step, a model based on developed pointed mass model is offered and analyzed by adding two rigid convex soles as feet and passive revolute joint as ankle. To make leg length changes during walking, an active dynamic element is used. Next, a passive controller or dynamic element is used with the active one to reduce active element role during movement. Particle swarm optimization method is used to minimize this role by calculating optimized passive element parameters. The results show using the combination of optimized passive and active dynamic elements, the amount of energy consumption is decreased significantly. As a result, we can use a much smaller active element with less power to walk. Also using a passive dynamic element practically improves mechanical specifications of the structure such as dimensions and weight as well as providing simple use for users.
Full Research Paper
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Farzaneh Dasar; Majid Ghoshuni; Ghasem Sadeghi Bajestani
Volume 14, Issue 1 , May 2020, Pages 13-22
Abstract
Autism spectrum disorder is a developmental disorder that involves disorders in social interaction and communication and repetitive or stereotypical behavior. In some children with autism, the sensitivity to acoustic stimuli is much higher than normal (hypersensitive) versus in some other children, this ...
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Autism spectrum disorder is a developmental disorder that involves disorders in social interaction and communication and repetitive or stereotypical behavior. In some children with autism, the sensitivity to acoustic stimuli is much higher than normal (hypersensitive) versus in some other children, this sensitivity is less than normal (hyposensitive). In this study a method for evaluation of auditory system of hypersensitive and hyposensitive autism children using event related potentials (ERPs) was presented. The EEG signal was recorded from 10 autism children (2 girls) with average age of 7.7±2.31 years. In order to record ERPs, 2000 audio stimulation based on the MissMatch Negetivity (MMN) Pattern was presented to participants. These stimulus include 1600 standard sounds with a frequency of 1000 Hz, deviant at 1300 Hz, and noise at frequencies of 1500-1000, 500 and 2000 Hz. In order to analyze ERP data, 18 time domain features have been extracted from the ERP components in all three types of stimulation (standard, deviation, noise). Based on the results, in the deviant stimuli, total positive area of the Pz channel in the hypersensitive group was significantly increased (p=0.028) compared to the hyposensetive group. Also, in the noise stimuli, total positive area in C4 and Pz channels has significantly increased (p=0.028, p=0.009) in the hyposensitive group compared to hypersensetive group. In conclusion, when hypersensitive children were exposed to deviant stimulue, neural activity was increased in parietal lobe, wheras in hyposensitive children neural activity increased in central and parietal lobe during noise stimulue. Therefore, this method can be useful in assessing children's autism spectrum in terms of hearing loss sensitivity.
Full Research Paper
Biomechanics / Biomechanical Engineering
Hadi Taghizadeh
Volume 14, Issue 1 , May 2020, Pages 23-30
Abstract
Determining mechanical properties of very soft tissues have been considered as a popular and challenging topic in biomechanics only in the last decades. In addition, these tissues do not have any weight-bearing functions, however, their mechanical characterization is important for designing new safety ...
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Determining mechanical properties of very soft tissues have been considered as a popular and challenging topic in biomechanics only in the last decades. In addition, these tissues do not have any weight-bearing functions, however, their mechanical characterization is important for designing new safety equipment, diagnosis and treatment of the diseases and tumors. Liver is one of the vital body organs that is highly porous and tearable and is highly susceptible to mechanical damage during accidents and minimally invasive surgeries. In this study, a set of uniaxial tension tests was performed on a bovine liver tissue. Linear elastic model in combination with the Bridgman correction method was utilized to determine the mechanical properties, i.e., Young’s modulus. An image processing software was also developed utilizing MS Visual Fortran language in order to obtain and track required geometric dimensions, i.e., radii of curvature, minimal sample radius in the necking zone, and probable detaching during the test session. Our experiments showed a tensile elastic modulus of 15.51±1.62 kPa for the samples (p < 0.05). Different amounts for elastic modulus of the liver have been reported in the literature. Hence, we conducted tension tests on samples with progressively increasing diameters. The changes in the sample diameter was in the range of 2.5 to 20 mm. In this way, the effect of sample diameter on elastic modulus was inquired. Our results indicate an inverse relation between elastic modulus and diameter in the tested zone. Such phenomena can be attributed to small sample size which is similar to the size of liver lobules (a few millimeters). Hence, samples with diameters in the range of lobule size cannot constitute a suitable representative element for the liver tissue. To obtain valid results the sample diameters should be more than three times that of the lobule.
Full Research Paper
Biomedical Image Processing / Medical Image Processing
Amirhossein Chalechale; Ali Khadem
Volume 14, Issue 1 , May 2020, Pages 31-42
Abstract
The well-timed and correct diagnosis of Bipolar Disorder (BD) followed by proper treatment is vital for avoiding the progress of the illness. Although using resting-state functional magnetic resonance imaging (rs-fMRI) data and the features extracted from them may have an important role in diagnosing ...
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The well-timed and correct diagnosis of Bipolar Disorder (BD) followed by proper treatment is vital for avoiding the progress of the illness. Although using resting-state functional magnetic resonance imaging (rs-fMRI) data and the features extracted from them may have an important role in diagnosing this kind of brain disorder, few researches have been conducted on this illness and the obtained results are not accurate. In this research we used a new approach to diagnose BD I. By using seed-based correlation we used the following 4 regions of interest in order to extract the connectivity maps for each subject: the posterior cingulate cortex (PCC) to probe the default mode network (DMN), the amygdala and the subgenual cingulate cortex (sgACC) to probe the salience network (SN) and the dorsolateral prefrontal cortex (dlPFC) to probe the frontoparietal network (FPN). After computing the connectivity maps for each subject we extracted the most important connectivities using different threshold on the t-value from the t-test that we applied on them and then we used a support vector machine (SVM) using only four combined features and a leave one out cross-validation (LOOCV) method to classify the two groups. The proposed method was done on rs-fMRI data from 49 healthy control subjects and 34 BD I patients and an accuracy of higher than 90% was obtained in differentiating the two groups from each other. Also there were no hyper-connectivity between the 4 ROIs and the rest of the brain regions for the BD I groups in relation with the healthy controls. The regions that had most of the hypo-connectivity with the 4 ROI’s that we used were: the angular gyrus (Ag) and the orbitofrontal cortex (OFC) with the PCC, the anterior cingulate cortex with the amygdala and the dlPFC and the inferior temporal gyrus (ITG) with the sgACC.
Full Research Paper
Scaffolding / Bio-Scaffolds
Seyedeh Sara Kamali; Haniye Abdi Kordlar; Maryam Saadatmand; Shohreh Mashayekhan
Volume 14, Issue 1 , May 2020, Pages 43-53
Abstract
Successful cell culture in large scale 3D scaffolds in tissue engineering is still challenging and requires full control over physical, chemical and mechanical properties of the applied scaffolds. Recently, using printers for the fabrication of 3D scaffold with a structural arrangement of fibers has ...
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Successful cell culture in large scale 3D scaffolds in tissue engineering is still challenging and requires full control over physical, chemical and mechanical properties of the applied scaffolds. Recently, using printers for the fabrication of 3D scaffold with a structural arrangement of fibers has been extensively developed, because it is possible to define the structure of scaffold geometry before manufacturing. The aim of this study was the investigation of the effective geometrical parameters on the 3D symmetric porous scaffold from the mass and momentum transport phenomena point of view. In this way, the mass and momentum transfer equations were solved using COMSOL Multiphysics software. In 3D scaffolds, the optimum model is the one that can provide a more appropriate environment for the cultured cells leading an increase in the attached cell number. The oxygen concentration reaching the bone cells should be greater than 0.02 mol/m3 in order to prevent cell death. Moreover, the fluid shear stress regime must be such that (between 10-5 to 10-3 Pa) it could not cause cell detachment. After studying the results of the simulation and changing the different parameters such as fiber diameter, fiber distance and the width of the channels, the appropriate structure was obtained regarding maximum shear stress and minimum oxygen concentration, and then the effect of fluid flow rate on maximum shear stress was examined for the appropriate structure. The optimized model with a fiber diameter of 0.25 mm, a fiber distance of 0.25 mm, and a channel width of 0.25 mm was proposed that fluid flow inlet velocity was 5×10-5 m/s.
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Biological Computer Modeling / Biological Computer Simulation
Sajad Shafiekhani; Amin Mashayekhi Shams; Seyed Yashar Banihashem; Nematollah Gheibi; Amir Homayoun Jafari
Volume 14, Issue 1 , May 2020, Pages 55-67
Abstract
According to cancer’s global statistics, there will be 27.5 million new cases of cancer each year by 2040, therefore, it is crucial to achieve a deeper understanding of the cancer progression mechanisems and immune system functions in response to it. Nowadays, computational models are widely used ...
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According to cancer’s global statistics, there will be 27.5 million new cases of cancer each year by 2040, therefore, it is crucial to achieve a deeper understanding of the cancer progression mechanisems and immune system functions in response to it. Nowadays, computational models are widely used to capture dynamics of the tumor- immune system (TIS). The proposed model on this manuscript is on the basis of the ordinary differential equations which mechanistically models the interactions of tumor cells, CTLs, NKs and MDSCs. CTLs and NK cells are the most important cells of adaptive and innate immune system, respectively that encounter with tumor cells, while MDSCs as immature immune cells suppress the immune responses in the inflammatory environments. Due to the error of the in-vivo/in-vitro experiments, vagueness, imprecise information, incomplete data and natural variability of the tumor-immune system emerges between different individuals, the kinetic parameters of computational models are uncertain that this uncertainty can be captured by fuzzy sets. Hence, we assign fuzzy numbers with triangular membership functions instead of crisp numbers to some kinetic parameters of the tumor–immune system model. In fact, the uncertainty in the kinetic parameters of the ordinary differential equations affects the dynamic of the system species. In this essay, for the first time, a fuzzy number has been used to model the uncertainty of the parameters of the ODE model. Our data reveals that increasing/decreasing the uncertainty region of the model's fuzzy parameters increases/decreases the uncertainty region of dynamics of species. Furtheremore, the simulations of the model in the crisp setting of parameters show that the repition of 5-FU treatment for inhibition of MDSCs dramatically inhibits tumor cells and eradicate tumor.
Full Research Paper
Computational Neuroscience
Naser Sadeghnejad; Mehdi Ezoji; Reza Ebrahimpour
Volume 14, Issue 1 , May 2020, Pages 69-79
Abstract
Object recognition is one of the main cognitive abilities of human and animals. Human visual system, as a fast and accurate system can be a source of inspiration for the computational models of object recognition. Studies on the human visual system have emphasized its processing over time, whereas it ...
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Object recognition is one of the main cognitive abilities of human and animals. Human visual system, as a fast and accurate system can be a source of inspiration for the computational models of object recognition. Studies on the human visual system have emphasized its processing over time, whereas it is not considered in the conventional computational models of object recognition. In this paper, we attempt to present a time-based multilevel model for object recognition. In the first layer of the model, the input image information is sent to the next layer in a temporal representation. In the middle layer of the model, a deep neural network is used as a feature extractor. Finally, in contrast to the popular computational models for object recognition, a decision-making model such as drift-diffusion model is proposed based on the neuronal decision-making mechanisms in the brain. In other words, adaption to the human visual system has been considered in all of three layers. Several experiments have been conducted to evaluate the performance of the proposed computational model in object recognition. The experimental results show that as the input image becomes more complicated, noise increases, or occlusion occurs, the performance/reaction time of the model decreases/increases, which is consistent with the behavior of human visual system. The performance of the model for object recognition and base-level categorization is also investigated for application of the original images and the inverted images. The results show the difference between the processes of the object recognition and base-level categorization, which is consistent with the behavior of human visual system reported in the referenced papers.
