Sharif Digital Repository

Cancer diagnosis has recently been at the forefront of recent medical research, with ongoing efforts to develop devices and technologies for detecting cancer in patients. One promising approach for cancer diagnosis is the detection of Circulating Tumor Cells (CTCs) in blood samples. Separating these rare cells from the diverse background of blood cells and analyzing them can provide valuable insights into the disease's stage and lethality. Here we present the design and fabrication of a centrifugal microfluidic platform on a polymeric disk that utilizes centrifugal forces for cell isolation. The separation units exploit both active and passive methods. In other words, in addition to... 

Recovering the 3D surface of a nonrigid surface from a single viewpoint is known to be both ambiguous and challenging. It has been shown that preventing the surface from either shrinking or stretching is an effective way to resolve the ambiguities inherent to this problem. State-of-the-art solutions to nonrigid 3D shape recovery rely on the fact that distances between adjacent surface points must be preserved. Although the results obtained with such a constrained have small reconstruction error, they are still far away from a real-time reconstruction. The authors therefore exploit a two-level weighting schema in a new approach to inextensible and smooth surface reconstruction. This approach... 

Portfolio formation in financial markets is the task of not taking non-necessary risks. Quantitative investment powered by machine learning has opened many new opportunities for more insight generation from financial data resulting in the explosion of ideas to enhance the performance of investments in the stock markets. In this research, we propose a first-introduced model called HHT-XGB to predict the changing trends in the next close price of stocks under the study. The proposed model combines Hilbert–Huang Transform (HHT) as the feature engineering part and the extreme gradient boost (XGBoost) as the Close price trend classifier. The classification output is a sequence of ups and downs... 

Tailored healthcare, an approach focused on individual patients, requires integrating emerging interdisciplinary technologies to develop accurate and user-friendly diagnostic tools. KRAS mutations, prevalent in various common cancers, are crucial determinants in selecting patients for novel KRAS inhibitor therapies. This study presents a novel state-of-the-art Lab-on-a-Disc system utilizing peptide nucleic acids-loop backward (PNA-LB) mediated allele-specific loop-mediated isothermal amplification (LAMP) for detecting the frequent G12D KRAS mutation, signifying its superiority over alternative mutation detection approaches. The designed Lab-on-a-Disc system demonstrated exceptional... 

Prognostication of numerous chronic diseases are in need of identifying circulating tumor cells (CTCs), afterwards, separating and reviving contaminated samples are required. Conventional methods of separating blood cells, namely cytometry or magnetically activated cell sorting, in many cases lose their functionality, or efficiency under different conditions. Hence microfluidic methods of separation have been implemented. Herein, an innovative integrated double stair-shaped microchannel is designed and optimized, capable of ‘separation’, and ‘chemical lysis’ simultaneously in which the lysis reagent concentration can be controlled to tune the lysis intensity. The method of insulator-based... 

Separation and isolation of suspended submicron particles is fundamental to a wide range of applications, including desalination, chemical processing, and medical diagnostics. Ion concentration polarization (ICP), an electrokinetic phenomenon in micro-nano interfaces, has gained attention due to its unique ability to manipulate molecules or particles in suspension and solution. Less well understood, though, is the ability of this phenomenon to generate circulatory fluid flow, and how this enables and enhances continuous particle capture. Here, we perform a comprehensive study of a low-voltage ICP, demonstrating a new electrokinetic method for extracting submicron particles via flow-enhanced... 

Cell lysis is one of the main steps in the deoxyribonucleic acid (DNA) extraction process, which makes vital information about organisms accessible for analysis. In the chemical cell lysis process, cells and lysis buffer mix, and the cell membrane is eliminated, and then DNA and other intracellular components are released. Mixing is not an easy step in microfluidic systems, and it reduces the chemical cell lysis efficiency. Therefore, a novel method has been implemented to address this issue. In this work, a magnetophoretic separation method is utilized to eliminate the mixing process and guide target cells directly inside the lysis buffer flow; integrating cell separation and cell lysis... 

Cell separation plays a crucial role in diagnosing and improving a wide range of diseases, such as cancer, which is a severe reason for the death of people in the current decades. Circulating tumor cells (CTCs) inside the blood can be separated from the other whole blood cells to detect early cancer. Inertial methods are more superficial and cost less than the current CTC separation methods. These methods also have great potential in high-throughput separation in lab-on-a-chip (LOC) and lab-on-a-disk (LOD) devices because of secondary flow generation, especially in serpentine-shaped microchannels. The present study considers a continuous process for separating CTCs from the blood sample.... 

Financial time series have been extensively studied within the past decades; however, the advent of machine learning and deep neural networks opened new horizons to apply supercomputing techniques to extract more insights from the underlying patterns of price data. This paper presents a tri-state labeling approach to classify the underlying patterns in price data into up, down and no-action classes. The introduction of a no-action state in our novel approach alleviates the burden of denoising the dataset as a preprocessing task. The performance of our labeling algorithm is experimented with using machine learning and deep learning models. The framework is augmented by applying the Bayesian... 

Modeling and analysis of information system vulnerabilities helps us to predict possible attacks to networks using the network configuration and vulnerabilities information. As a fact, exploiting most of vulnerabilities result in access rights alteration. In this paper, we propose a new vulnerability analysis method based on the Take-Grant protection model. We extend the initial Take-Grant model to address the notion of vulnerabilities and introduce the vulnerabilities rewriting rules to specify how the protection state of the system can be changed by exploiting vulnerabilities. Our analysis is based on a bounded polynomial algorithm, which generates the closure of the Take-Grant graph... 

We study the translocation of stiff polymers through a nanopore, driven by the chemical-potential gradient exerted by binding proteins (chaperones) on the trans side of the pore. Bound chaperones prevent backsliding through the pore and, therefore, partially rectify the polymer passage. We show that the sequence of chain monomers with different binding affinity for the chaperones significantly affects the translocation dynamics. In particular, we investigate the effect of the nearest-neighbor adjacency probability of the two monomer types. Depending on the magnitude of the involved binding energies, the translocation speed may either increase or decrease with the adjacency probability. We... 

Combining the advection-diffusion equation approach with Monte Carlo simulations we study chaperone driven polymer translocation of a stiff polymer through a nanopore. We demonstrate that the probability density function of first passage times across the pore depends solely on the Péclet number, a dimensionless parameter comparing drift strength and diffusivity. Moreover it is shown that the characteristic exponent in the power-law dependence of the translocation time on the chain length, a function of the chaperone-polymer binding energy, the chaperone concentration, and the chain length, is also effectively determined by the Péclet number. We investigate the effect of the chaperone size on... 

The amount of rippling in graphene sheets is related to the interactions with the substrate or with the suspending structure. Here, we report on an irreversibility in the response to forces that act on suspended graphene sheets. This may explain why one always observes a ripple structure on suspended graphene. We show that a compression-relaxation mechanism produces static ripples on graphene sheets and determine a peculiar temperature Tc, such that for T