Biomolecules and Polymers Translocation Through Biological Single Nanopores and Current Characteristics Analysis

, Ph.D. Dissertation Sharif University of Technology Haji Abdolvahab, Rouhollah (Author) ; Ejtehadi, Mohammad Reza (Supervisor) ; Mobasheri, Hamid (Co-Advisor)

Abstract

Translocation processes are ubiquitous in biology and biotechnology. Translocation of small molecules, e. g. sugar from maltoporin, metabolites through bacteria and macromolecules like proteins, from channels of cellular organelles and or RNA translocation though
nuclear pores are of vital importance for cellular metabolism. One of the important applications of translocation processes in biotechnology is to sense translocating macromolecules or small molecules by analyzing the current passing through natural or synthesis channels. Improving our knowledge about this process can also help us to develop new methods for designing the appropriate drugs. In this thesis by studying and...

Vibration Modes of Membrane Proteins by Application of Elastic Network Model

, Ph.D. Dissertation Sharif University of Technology Besya, Azimberdy (Author) ; Ejtehadi, Mohammad Reza (Supervisor) ; Mobasheri, Hamid (Supervisor) ; Naghdabadi, Reza (Co-Advisor)

Abstract

Outer membrane proteins play the role of molecular machines in the outer membrane of bacteria to regulate their basic functions. These macromolecules have nano-scale dimensions and they are involved in the classifications of nano-machines and nano-pores. Protein structure is constructed of chain of amino acids. Coarse grained elastic network model of the protein introduces a network of selected point masses, which is located on α-carbon of each amino acid, linked together with harmonic springs that represent the interactions between residues, both the chemical (protein backbone) and physical bonds. Using the harmonic network potential and theory of mechanical vibration, normal modes of...

Analysis of the growth process of neural cells in culture environment using image processing techniques

, Article 13th International Computer Society of Iran Computer Conference on Advances in Computer Science and Engineering, CSICC 2008, Kish Island, 9 March 2008 through 11 March 2008 ; Volume 6 CCIS , 2008 , Pages 732-736 ; 18650929 (ISSN); 3540899847 (ISBN); 9783540899846 (ISBN) Mirsafian, A ; Isfahani, S. N ; Kasaei, S ; Mobasheri, H ; Sharif University of Technology

2008

Abstract

Here we present an approach for processing neural cells images to analyze their growth process in culture environment. We have applied several image processing techniques for: 1- Environmental noise reduction, 2- Neural cells segmentation, 3- Neural cells classification based on their dendrites' growth conditions, and 4- neurons' features Extraction and measurement (e.g., like cell body area, number of dendrites, axon's length, and so on). Due to the large amount of noise in the images, we have used feed forward artificial neural networks to detect edges more precisely. © 2008 Springer-Verlag

Fabrication localized surface plasmon resonance sensor chip of gold nanoparticles and detection lipase-osmolytes interaction

, Article Applied Surface Science ; Vol. 314, issue , 2014 , Pages 138-144 ; ISSN: 01694332 Ghodselahi, T ; Hoornam, S ; Vesaghi, M. A ; Ranjbar, B ; Azizi, A ; Mobasheri, H ; Sharif University of Technology

2014

Abstract

Co-deposition of RF-sputtering and RF-PECVD from acetylene gas and Au target were used to prepare sensor chip of gold nanoparticles (Au NPs). Deposition conditions were optimized to reach a Localized Surface Plasmon Resonance (LSPR) sensor chip of Au NPs with particle size less than 10 nm. The RF power was set at 180 W and the initial gas pressure was set at 0.035 mbar. Transmission Electron Microscopy (TEM) images and Atomic Force Microscopy (AFM) data were used to investigate particles size and surface morphology of LSPR sensor chip. The Au and C content of the LSPR sensor chip of Au NPs was obtained from X-ray photoelectron spectroscopy (XPS). The hydrogenated amorphous carbon (a-C:H)...

Fabrication and characterization and biosensor application of gold nanoparticles on the carbon nanotubes

, Article Applied Surface Science ; Volume 355 , November , 2015 , Pages 1175-1179 ; 01694332 (ISSN) Ghodselahi, T ; Aghababaie, N ; Mobasheri, H ; Zand Salimi, K ; Akbarzadeh Pasha, M ; Vesaghi, M. A ; Sharif University of Technology

Elsevier 2015

Abstract

Gold nanoparticles (Au NPs) were synthesized by co-deposition of RF-sputtering and RF-PECVD from acetylene gas and Au target on the carbon nanotubes (CNTs). The CNTs were prepared by thermal chemical vapor deposition (TCVD) and Pd nanoparticles catalyst. TEM image shows that high-density and uniform distribution of Au NPs were grown on the CNTs. XRD analysis indicates that Au NPs have fcc crystal structure and CNTs have a good graphite structure. Raman spectroscopy results suggest that our sample includes double-walled CNTs. It is resulted that intensity of D-band reduces and G-band intensity raises and radial breathing mode (RBM) is changed by immobilizing of Au NPs on the CNTs. Raman...

Optimizing Transmisson from Distant Wind Farms

, M.Sc. Thesis Sharif University of Technology Abdollahi Mansourkhani, Hamid Reza (Author) ; Hosseini, Hamid (Supervisor)

Abstract

Wind power is site dependent and is by nature partially dispatchable. Furthermore, good wind sites are far from grid. Due to these problems, and along with the existing limitations in the transmission networks, a comprehensive analysis over an extended time is needed to properly explore all potential wind sites for wind capacity allocation. This problem is computationally expensive and decomposition methods are required to break down this problem. Here Benders decomposition approach is used, which is a popular technique for solving large-scale problems, to decompose the original problem into a master and a subproblem. The master problem is a linear problem, which allocates wind capacity to...

Identification of the Set of Single Nucleotide Variants in Genome Responsible for the Differentiation of Expression of Genes

, M.Sc. Thesis Sharif University of Technology Khatami, Mahshid (Author) ; Rabiee, Hamid Reza (Supervisor) ; Beigi, Hamid (Supervisor)

Abstract

Single nucleotide polymorphs, There are changes caused by a mutation in a nucleotide in the Dena sequence. Mononucleotide polymorphisms are the most common type of genetic variation. Some of these changes have little or no effect on cells, while others cause significant changes in the expression of cell genes that can lead to disease or resistance to certain diseases. Because of the importance of these changes and their effect on cell function, the relationships between these changes are also important. Over the past decade, thousands of single disease-related mononucleotide polymorphisms have been identified in genome-related studies. Studies in this field have shown that the expression of...

Synthesis & Characterization of Au-HKUST-1 Nanocomposite and Evaluation of Plasmonic Properties of Gold Nanoparticles in this Nanocomposite

, M.Sc. Thesis Sharif University of Technology Moazzeni, Hamid Reza (Author) ; Madaah Hosseini, Hamid Reza (Supervisor)

Abstract

In the past few years, many research works on the controllable integration of metal nanoparticles and metal-organic frameworks were done, since the obtained composite material shows a synergism effect in catalysis and photocatalysis, drug delivery applications, gas, and energy storage, as well as sensing. For the first time, in this study, we employed template-assisted growth to synthesize Au-HKUST-1 Nanocomposite. XRD analysis entirely confirms that employing this strategy in synthesizing Au-HKUST-1 was wholly successful, and the plasmonic properties of this nanostructure were studied via UV-visible spectroscopy. In the course of synthesis, gold nanoparticles with 70nm diameter were...

Additive manufacturing of bioactive glass biomaterials

, Article Methods ; Volume 208 , 2022 , Pages 75-91 ; 10462023 (ISSN) Simorgh, S ; Alasvand, N ; Khodadadi, M ; Ghobadi, F ; Malekzadeh Kebria, M ; Brouki Milan, P ; Kargozar, S ; Baino, F ; Mobasheri, A ; Mozafari, M ; Sharif University of Technology

Academic Press Inc 2022

Abstract

Tissue engineering (TE) and regenerative medicine have held great promises for the repair and regeneration of damaged tissues and organs. Additive manufacturing has recently appeared as a versatile technology in TE strategies that enables the production of objects through layered printing. By applying 3D printing and bioprinting, it is now possible to make tissue-engineered constructs according to desired thickness, shape, and size that resemble the native structure of lost tissues. Up to now, several organic and inorganic materials were used as raw materials for 3D printing; bioactive glasses (BGs) are among the most hopeful substances regarding their excellent properties (e.g., bioactivity...

Synthesis of Magnetite (Fe3O4)-Avastin Nanocomposite as a Potential Drug for AMD Treatment

, M.Sc. Thesis Sharif University of Technology Zargarzadeh, Mehrzad (Author) ; Maddah Hosseini, Hamid Reza (Supervisor) ; Delavary, Hamid (Co-Advisor)

Abstract

Age-related macular degeneration (AMD) is the most common cause of vision loss in those aged over 50. There are two main types of AMD, Wet and Dry form. Wet AMD is more severe though more treatable. There are three conventional treatments for AMD including laser therapy, surgery and intravitreal injection of anti-VEGF into the eye. Delivery of drugs to the posterior segment of the eye is still challenging and several implants and devices are currently under investigation for their ability to stimulate the retina, producing visual percepts. The application of intravitreal bevacizumab (Avastin) has expanded tremendously from the time of its introduction into ophthalmic care since 3 years ago....

Detection of Central Nodes in Social Networks

, Ph.D. Dissertation Sharif University of Technology Mahyar, Hamid Reza (Author) ; Movaghar, Ali (Supervisor) ; Rabiee, Hamid Reza (Supervisor)

Abstract

In analyzing the structural organization of many real-world networks, identifying important nodes has been a fundamental problem. The network centrality concept deals with the assessment of the relative importance of network nodes based on specific criteria. Central nodes can play significant roles on the spread of influence and idea in social networks, the user activity in mobile phone networks, the contagion process in biological networks, and the bottlenecks in communication networks. High computational cost and the requirement of full knowledge about the network topology are the most significant obstacles for applying the general concept of network centrality to large real-world social...

Cost-Sensitive Classifiers and Their Applications

, M.Sc. Thesis Sharif University of Technology Ahmadi, Zahra (Author) ; Beigy, Hamid (Supervisor)

Abstract

Decision making often has different effects and results with unequal importance. Most of classifiers try to minimize the rate of misclassified instances. These classifiers assume equal costs for different misclassification types. However, this assumption is not true in many real world problems and different misclassification types have different costs. These differences can be applied by introducing the cost in the process of learning. In this manner, total cost of misclassification will be the evaluation metric of classification. In order to apply this metric to the problems, new learning algorithms are needed. Cost-sensitive learning is the related area of machine learning which deals with...

Data Stream Classification in Presence of Concept Drift Using Ensemble Learning

, M.Sc. Thesis Sharif University of Technology Sobhani, Parinaz (Author) ; Beigy, Hamid (Supervisor)

Abstract

Traditional classification techniques of machine learning assume that data have stationary distributions. This assumption for recent challenges where tremendous amount of data are generated at unprecedented rates with evolving patterns, is not true anymore. Classification of data streams has become an important area of machine learning, as the number of applications facing these challenges increases. Examples of such data streams applications include text streams, surveillance video streams, credit card fraud detection, market basket analysis, information filtering, computer security, etc. An appropriate method for such problems should adapt to drifting concepts by revising and refining the...

Using Transductive Learning Classification in Bioinformatics

, M.Sc. Thesis Sharif University of Technology Tajari, Hossein (Author) ; Beigy, Hamid (Supervisor)

Abstract

Classification is one of the most important problems in machine learning area. Reliable and successful classification is essential for diagnosing patients for further treatment. In many applications such as bioinformatics unlabeled data is abundant and available. However labeling data is much more difficult and expensive to obtain. This dissertation presents a novel transductive approach for the development of robust microarray data classification. The transduction problem is to estimate the value of classification function at the given points in the working set. This contrasts with the standard inductive learning problem of estimating the classification method at all possible values and...

Concept Drift Detection in Data Streams Using Ensemble Classifiers

, M.Sc. Thesis Sharif University of Technology Dehghan, Mahdie (Author) ; Beigy, Hamid (Supervisor)

Abstract

Concept drift is a challenging problem in the context of data stream processing. As a result of increasing applications of data streams, including network intrusion detection, weather forecasting, and detection of unconventional behavior in financial transactions; numerous studies have been conducted in the field of concept drift detection. In order to solve the problem of concept drift detection, an ideal method should be able to quickly and correctly identify a variety of changes, adapt quickly to new concepts, in the presence of limitations of memory and processing power. In this thesis, a new explicit concept drift detection method based on ensemble classifiers has been proposed for data...

Call Admission Control Schemes in WiMAX Networks

, M.Sc. Thesis Sharif University of Technology Mokhtari, Zeinab (Author) ; Beigy, Hamid (Supervisor)

Abstract

The rapid growth of broadband wireless access (BWA) has increased the demand of new application such as VoIP, video conferencing, online gaming each of which has different requirement for quality of service. Due to limited bandwidth provided for these networks, one of the most important issues is how effective we manage bandwidth in order to support requests. The quality of service is an important indicator of the effective management of bandwidth. Using mechanisms of call admission control is a commonly accepted method for balance between quality of service and increase of utilization resource in cellular mobile networks. In fact, ...

Multi-Label Text Classification

, M.Sc. Thesis Sharif University of Technology Kamali, Sajjad (Author) ; Beigy, Hamid (Supervisor)

Abstract

Nowadays, with the increasing size of data,it’s impossible to collect data and fast classification by human, and needs for an automated classification and data analysis, is more interested. Data classification is a process of giving the training data along with their class labels to the learning agent, which learns the relation between the instances and the labels. Then make a prediction to the label of the training data.In this thesis we will observe the classification of the multi-label data. Multi-label data have more than one label. In other words, each instance appears with a vector of labels.In this thesis, a method based on nearest neighbor is proposed to classify the multi-label...

An Active Learning Algorithm for Spam Filtering

, M.Sc. Thesis Sharif University of Technology Shadloo, Maryam (Author) ; Beigy, Hamid (Supervisor)

Abstract

Content-based spam filtering problem is defined as classifying input emails into spam and legitimate emails. so it is considered as an application of supervised-learning. The supervised learning methods often require a large training set of labelled emails to attain good accuracy and the users should label huge amount of emails. In reality, it is not reasonable to expect users to do this. To address this issue and reduce number of labelling request from user active learning techniques can be used. The goal of active Learning algorithms is to achieve appropriate accuracy by using fewer amounts of labelled data in comparison with supervised-learning methods.In this thesis two active learning...

An Outlier Detection and Cleaning Algorithm in Classification Applications

, M.Sc. Thesis Sharif University of Technology Kasaeian, Mojtaba (Author) ; Beigy, Hamid (Supervisor)

Abstract

Increasing information in real world needs the special instrument for data saving, cleaning and processing. Data cleaning is so important steps in machine learning application that include various kind of procedures such as, duplicate detection, fill out missing value and outlier detection. Outliers are observation, which deviates so much from other observations as to arouse suspicions that it was generated by a different mechanism. Many researches has been carried out in the machine learning field with regards to the outlier detection that has applications in real world, like: Intrusion detection for network security, fraud detection in credit cards, fault detection for security in critical...

Multi-cass Semi-srvised Classification of Data Streams

, M.Sc. Thesis Sharif University of Technology Sepehr, Arman (Author) ; Beigy, Hamid (Supervisor)

Abstract

Recent advances in storage and processing have provided the ability of automatic gathering of information which in turn leads to fast and contineous flow of data. The data which are produced and stored in this way are named data streams. It has many applications such as processing financial transactions, the recorded data of various sensors or the collected data by web sevices. Data streams are produced with high speed, large size and much dynamism and have some unique properties which make them applicable in precise modeling of many real data mining applications. The main challenge of data streams is the occurrence of concept drift which can be in four types: sudden, gradual, incremental or...