Sharif Digital Repository

Development of novel engineering techniques that can promote new clinical treatments requires implementing multidisciplinary in-vitro and in-vivo approaches. In this study, we have implemented microfluidic devices and in-vivorat model to study the mechanism of neural stem cell migration and differentiation.These studies can result in the treatment of damages to the neuronal system. In this research, we have shown that by applying appropriate ranges of biochemical and biomechanical factors as well as by exposing the cells to electromagnetic fields, it is possible to improve viability, proliferation, directional migration and differentiation of neural stem cells. The results of this study can... 

Despite the popularity of the permeable pavements in urban areas in recent years, a few empirical equations have been developed to estimate the time of concentration (Tc) on pervious surfaces, and almost none of them is evaluated over the permeable pavements. In this paper, we aim to investigate the effect of low impact development (LID) on Tc and develop a new equation for estimating overland flow Tc compatible with both permeable and impermeable pavements in small urban watersheds with a semi-arid climate. An experimental model was devised to determine the new equation. Synthetic rainfall (22–40 mm.h−1) was applied to a rectangular shaped (6 m × 1 m) test watershed with an adjustable... 

Independent Component Analysis (ICA) can be used to decompose functional Magnetic Resonance Imaging (fMRI) data into a set of statistically independent images which are likely to be the sources of fMRI data. After applying ICA, a set of independent components are produced, and then, a "meaningful" subset from these components must be identified, because a large majority of components are non-interesting. So, interpreting the components is an important and also difficult task. In this paper, we propose a criterion based on the entropy of time courses to automatically select the components of interest. This method does not require to know the stimulus pattern of the experiment  

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... 

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... 

Data are presented on the solidification of aluminum alloys and their macro segregation behavior. Three alloys with different solidification ranges were prepared in two temperatures. Two types of molds were also prepared by sand and metallic materials. The solidification of Al alloys were studied and the effects of four parameters were determined, including cooling rate, casting temperature, degassing and nucleation effects on solidification and a comparison was conducted to Scheil model performance. Three types of aluminum alloys (Al-12.1%Si, Al-6.9%Si and Al-4.4% Cu) with short, medium and wide solidification ranges were studied and the results showed that degassing, nucleation, increasing... 

Motivated by the bus escape routing problem in printed circuit boards, we study the following rectangle escape problem: given a set S of n axis-aligned rectangles inside an axis-aligned rectangular region R, extend each rectangle in S toward one of the four borders of R so that the maximum density over the region R is minimized. The density of each point p∈R is defined as the number of extended rectangles containing p. We show that the problem is hard to approximate to within a factor better than 3/2 in general. When the optimal density is sufficiently large, we provide a randomized algorithm that achieves an approximation factor of 1+ε with high probability improving over the current best... 

We revisit the problem of finding (Formula presented.) paths with a minimum number of shared edges between two vertices of a graph. An edge is called shared if it is used in more than one of the (Formula presented.) paths. We provide a (Formula presented.)-approximation algorithm for this problem, improving the best previous approximation factor of (Formula presented.). We also provide the first approximation algorithm for the problem with a sublinear approximation factor of (Formula presented.), where (Formula presented.) is the number of vertices in the input graph. For sparse graphs, such as bounded-degree and planar graphs, we show that the approximation factor of our algorithm can be... 

We revisit the problem of finding k paths with a minimum number of shared edges between two vertices of a graph. An edge is called shared if it is used in more than one of the k paths. We provide a ⌊k/2⌋-approximation algorithm for this problem, improving the best previous approximation factor of k - 1. We also provide the first approximation algorithm for the problem with a sublinear approximation factor of O(n3/4), where n is the number of vertices in the input graph. For sparse graphs, such as bounded-degree and planar graphs, we show that the approximation factor of our algorithm can be improved to O(√n). While the problem is NP-hard, and even hard to approximate to within an O(log n)... 

In this paper we show how the higher index theory can be used to prove results concerning the non-existence of a complete Riemannian metric with uniformly positive scalar curvature at infinity. By improving some classical results due to M. Gromov and B. Lawson we show the efficiency of these methods to prove such non-existence theorems  

In this paper we state and prove delocalized Morse type inequalities for Morse functions as well as for closed differential 1-forms. These inequalities involve delocalized Betti numbers. As an immediate consequence, we prove the vanishing of delocalized Betti numbers of manifolds fibering over the circle under a vanishing condition on the delocalizing conjugacy class  

We explore the dictionary learning problem for sparse representation when the signals are dependent. In this paper, a first-order Markovian model is considered for dependency of the signals, that has many applications especially in medical signals. It is shown that the considered dependency among the signals can degrade the performance of the existing dictionary learning algorithms. Hence, we propose a method using the Maximum Log-likelihood Estimator (MLE) and the Expectation Minimization (EM) algorithm to learn the dictionary from the signals generated under the first-order Markovian model. Simulation results show the efficiency of the proposed method in comparison with the... 

Diffusion weighted imaging (DWI) is a non-invasive method for investigating the brain white matter structure. It can be used to evaluate fiber bundles in the brain. However, clinical acquisitions are often low resolution. This paper proposes a method for improving the resolution using sparse representation. In this method a non-diffusion weighted image (bO) is utilized to learn the patches and then diffusion weighted images are reconstructed based on the trained dictionary. Our method is compared with bilinear, nearest neighbor and bicubic interpolation methods. The proposed method shows improvement in terms of Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM)  

Diffusion tensor magnetic resonance imaging (DTMRI) is a non-invasive method for investigating the brain white matter structure. It can be used to evaluate fiber bundles in the brain but in the regions with crossing fibers, it fails. To resolve this problem, high angular resolution diffusion imaging (HARDI) with a large number of diffusion encoding directions is used and for reconstruction, the Q-ball method is applied. In this method, orientation distribution function (ODF) of fibers can be calculated. Mathematical models play a crucial role in the field of ODF. For instance, in registering Q-ball images for applications like group analysis or atlas construction, one needs to interpolate... 

Diffusion Tensor Imaging (DTI) is a common method for the investigation of brain white matter. In this method, it is assumed that diffusion of water molecules is Gaussian and so, it fails in fiber crossings where this assumption does not hold. High Angular Resolution Diffusion Imaging (HARDI) allows more accurate investigation of microstructures of the brain white matter; it can present fiber crossing in each voxel. HARDI contains complex orientation information of the fibers. Therefore, registration of these images is more complicated than the scalar images. In this paper, we propose a HARDI registration algorithm based on the feature vectors that are extracted from the Orientation... 

In this paper, we compare registration results obtained using different diffusion maps extracted from diffusion tensor imaging (DTI). Fractional Anisotropy (FA) and Ellipsoidal Area Ratio (EAR) are two diffusion maps (indices) that may be used for image registration. First, we use FA maps to find deformation matrix and register diffusion weighted images. Then, we use EAR maps and finally we use both of FA and EAR maps to register diffusion weighted images. The difference between FA values before deformation and after registration using the FA alone or EAR alone has a median of 0.57 and using both of them has a median of 0.29. Therefore, the results of registration using both of the FA and... 

Background: Diffusion weighted imaging (DWI) is a non-invasive method for investigating the brain white matter structure and can be used to evaluate fiber bundles. However, due to practical constraints, DWI data acquired in clinics are low resolution. New method: This paper proposes a method for interpolation of orientation distribution functions (ODFs). To this end, fuzzy clustering is applied to segment ODFs based on the principal diffusion directions (PDDs). Next, a cluster is modeled by a tensor so that an ODF is represented by a mixture of tensors. For interpolation, each tensor is rotated separately. Results: The method is applied on the synthetic and real DWI data of control and... 

Background and objective Registration is a critical step in group analysis of diffusion weighted images (DWI). Image registration is also necessary for construction of white matter atlases that can be used to identify white matter changes. A challenge in the registration of DWI is that the orientation of the fiber bundles should be considered in the process, making their registration more challenging than that of the scalar images. Most of the current registration methods use a model of diffusion profile, limiting the method to the used model. Methods We propose a model-independent method for DWI registration. The proposed method uses a multi-level free-form deformation (FFD), a sparse...