Sharif Digital Repository

From a long time ago cancer has been threatening human’s health, and researchers have been grappling with the phenomenon for numerous years. In the annals of this struggle, the number of cancer victims has outnumbered the survivals in a way that,until recently, suffering from cancer was perceived to be equivalent to death. Permanent defeat against cancer stems from the incomplete recognition of the phenomenon. In recent years, with the advent of technologies to extract information from the heart of cells and at the genome and transcriptome levels, man has been able to acquire a deeper understanding of cancer, its behavior and operation. Now that cancer is regarded to be a genetic disease,... 

Thermal barrier coatings (TBCs) are used for increasing the efficiency and reducing pollutants of internal combustion engines (ICEs). In this paper, an optimization framework is developed in order to obtain the optimal dimensions for conventional coat, and the optimal dimensions and material property for functionally graded (FG) coat of a partially coated piston. A thermo mechanical analysis is investigated for Nano coat by finite element method. The conventional and Nano coats are made of MgZrO_3 as the insulating ceramic overlay and NiCrAl as the metallic bond-coat. The properties of the FG coat is assumed to vary according to power law through the thickness. For all tree conventional, FG... 

As a result of extraction from underground oil and gas reservoirs, the pore pressure in the reservoir decreases and the effective stress increases accordingly. Although the gradual consolidation of underground reservoirs and their compaction due to the extraction can improve the production process (Compaction Drive) and facilitate the release of hydrocarbon fluid, it may cause some problems. Field measurements in the past two decades have shown that in addition to the change of effective stress, the total horizontal and vertical stress field can also change in and around the reservoir. As a result of the settlement that occurs at the upper part of the reservoir due to the consolidation... 

Enzyme immobilization/drying operations are among the important operations of many biotechnological industrial units. The enzyme used in this study is bacterial alpha-amylase, which is widely used in various industries, including detergents. The production of alpha-amylase enzyme contains a large percentage of water in its composition; therefore, a wet wall tower was designed to conduct the experiments to evaporate the water present in the enzyme liquor, analyze its effects on activity, and also to validate the device. The results showed that in a flow of air around 240m3/hr and ambient temperature of 20◦C, enzyme liquor has a 250% increase in biological activity, which indicates the... 

In this thesis an algorithm has been implemented for automatic landing of a quadrotor under the ground effect. In this regard the six degrees of freedom equations of motion using the Newton-Euler method has been designed. Then, the ground effect has been modeled by inspiring from the similar available models in the literature. The proposed models and proportional-integral-derivative attitude control loops have been simulated in MATLAB/Simulink environment. Also, two control strategies, a classical proportional-integral-derivative controller and a sliding mode controller have been utilized for height control loop.Since sliding mode controller requires all state variables to generate control... 

Sight is probably our most important sense. Every day, humans are exposed to many visual stimuli in their surroundings. The human brain is able to identify and prioritize important and valuable stimuli and memorize them. Identifying and remembering these valuable stimuli is vital to meeting the needs and maintaining survival. The aim of the proposed research is to find the effect of reward learning on the coding of visual objects in the human brain. Previous results have shown that long-term reward-object association make valuable objects more recognizable behaviorally. Studies have also shown that visual stimuli and the pattern of activity of primary visual cortex neurons are closely... 

Prediction of crack growth is one of the greatest achievements of continuum mechanics in 20th century. However, in spite of Griffith’s achievements, nowadays lots of subjects remain unchallenged in the field of Fracture Mechanics. Concrete and asphalt concrete are two of the most popular material in civil engineering and crack growth prediction in these materials are very important. Cohesive crack model is one of the models which is used for prediction of crack growth in quasi-brittle material such as concrete and it has been used widely in recent years because of simplicity and good agreement with experiment.The aim of this thesis is three-dimensional static and dynamic cohesive modeling of... 

The common experience of the citizens in metropolitan areas is facing a large volume of private car traffic. Accordingly, the discussion of managing the demand for intra-city travel by private cars has become widespread. Factors influencing the demand and decision of citizens to travel by car, like the demand for any other product, are divided into several groups, including commodity price, related goods price, income, and advertisement. One of the most critical and generalized variables that affect the final price of goods and subsequently affects demand is the costs incurred in the decision and demand for goods. The demand for trips with private cars is associated with the following two... 

We consider a manifold M equipped with 1-forms eta(1)...eta(s) which satisfy certain contact like properties. We prove a generalization of the classical Darboux theorem for such manifolds  

Triple Negative Breast Cancer (TNBC) is an invasive subtype of breast cancer. Finding prognostic biomarkers is helpful in choosing the appropriate treatment procedure for patients of this cancer. In recent years, the role of microRNAs in various biological processes, including cancer, has been identified, and their accessibility and stability have made these types of molecules an ideal biomarker. In the first phase of this study, with the aim of overcoming the limitations of previous studies, a new bioinformatics protocol has been proposed to investigate the prognostic miRNAs of triple negative breast cancer. First, using survival analysis, 56 prognostic miRNAs which had a significant... 

Unsupervised neural spike sorting is a crucial tool in studying neural systems in the resolution of a neural cell. In extracellular recording from neural cells, the voltage of media is captured by the electrodes. The situation is possible that an electrode record activity of multiple neurons at the same time. The spike sorting goal is assigning each spike (extracellular recorded neural action potential) to a neural cell that generates it. Conventionally, more than one electrode is used to recording media voltages. The electrodes are placed in a small space as a single device called a multi-electrode array. After the spike sorting procedure, the occurrence time of activity of several cells is... 

Traditional techniques use invasive histology techniques to diagnose cancer. Cancer tissue is sampled directly in this method, which is very painful for the patient. In recent years, scientists have discovered that the cell world is released into the blood plasma after cell death, obtaining useful cancer information. Since methylation changes in cancer cells are very significant and the death rate of cancer cells is high, the methylation of each tissue is different from the other. Furthermore, they were diagnosing the type of cancer.On the other hand, due to the different patterns in methylated DNA with normal DNA and the use of bisulfite treatment technique to detect the degree of... 

The advent and advance of single-cell technologies have enabled us to measure the cell function and identity by using different assays and viewing it by different technologies. Nowadays, we are able to measure multiple feature vectors from same- single cells from multiple abstract molecular levels (genome, transcriptome, proteome, ...) simultaneously. Hence, the analysts can view the cell from different yet correlated angles and study their behaviours. Such progress in joint single-cell assessments plus the development and spread of more common single-cell assays - that measure one feature vector per cell - caused the growing need for computational tools to integrate these datasets in order... 

With the growing use of machine learning algorithms, especially in deep neural networks, the need for annotated data for supervised learning has also increased. In many cases, it is possible to collect data widely, but annotating all of these data is usually very time-consuming, expensive, and even impossible in some cases. The goal of active learning algorithms is to maximize the model’s performance with the least annotated data. Active learning algorithms are iterative algorithms that train the model in each iteration with the current annotated data. Then, using the results of the model on the remaining data without annotation, select some new data to annotate. This process usually... 

The Major Histocompatibility Complex (MHC) Class I molecules play a crucial role in the immune system. These molecules present peptides derived from intracellular proteins on the cell surface to be recognized by T cells. This process is vital for identifying and eliminating cancerous or infected cells. In cancer therapy, particularly in the development of personalized vaccines, accurately selecting peptides that can effectively bind to MHC Class I and stimulate a strong immune response is a significant challenge. This research introduces an innovative neural network model that utilizes a cross-encoder architecture and leverages a pre-trained model to simultaneously process peptide and MHC... 

In this research, a polyethylene / thermoplastic film containing ethylene adsorbent nanostructure was fabricated to package agricultural products and increase the shelf life of fruits and vegetables. The thermoplastic starch containing 60 wt% starch and 40 wt% plasticizers with weight ratios of 5: 1, 4: 1, and 3: 1 sorbitol to glycerol was added to the polyethylene film to determine the composition of the final film. The film was prepared by a combination of low-density polyethylene with 10wt % linear low-density polyethylene, 30 wt% thermoplastic starch (4: 1 sorbitol to glycerol ratio), and 3wt% PE-g-MA as compatibilizer. Then, halloysite nanotubes were added to the film as ethylene... 

DNA methylation in one of the most important epigenetic variations, which causes significant variations in gene expressions of mammalians. Our current knowledge about DNA methylation is based on measurments from samples of bulk data which cause ambiguity in intracellular differences and analysis of rare cell samples. For this reason, the ability to measure DNA methylation in single-cells has the potential to play an important role in understanding many biological processes including embryonic developement, disease progression including cancer, aging, chromosome instability, X chromosome inactivation, cell differentiation and genes regulation. Recent technological advances have enabled... 

The human leukocyte antigen protein, commonly known as HLA, has the ability to present small protein fragments called peptides on the surface of cells, whether they originate from within the cell or externally. The binding of these peptides to HLA receptors is a crucial step that triggers an immune response. By estimating the affinity between peptides and HLA class I, we can identify novel antigens that have the potential to be targeted by cancer therapeutic vaccines. Computational methods that predict the binding affinity between peptides and HLA receptors have the potential to expedite the design process of cancer vaccines. Currently, most computational methods exclusively rely on... 

We present a deep neural network to classify dermatological disease from patient images. Using self-supervised learning method we have utilized large amount of unlabeled data. We have pre-trained our model on 27000 dermoscopic images gathered from razi hospital, the best dermatological hospital in Iran, along with 33000 images from ISIC 2020 dataset. We have evaluated our model performance in semi-supervised and transfer learning approaches. Our experiments show that using this approach can improve model accuracy and PRC up to 20 percent on semi-supervised setting. The results also show that pretraining can improve classification PRC up to 20 percent on transfer learning task on HAM10000...