Sharif Digital Repository

Rapid isolation of white blood cells (WBCs) from whole blood is an essential part of any WBC examination platform. However, most conventional cell separation techniques are labor-intensive and low throughput, require large volumes of samples, need extensive cell manipulation, and have low purity. To address these challenges, we report the design and fabrication of a passive, label-free microfluidic device with a unique U-shaped cross-section to separate WBCs from whole blood using hydrodynamic forces that exist in a microchannel with curvilinear geometry. It is shown that the spiral microchannel with a U-shaped cross-section concentrates larger blood cells (e.g., WBCs) in the inner... 

Local three-stranded DNA/RNA hybrid regions of genomes (R-loops) have been detected either by binding of a monoclonal antibody (DRIP assay) or by enzymatic recognition by RNaseH. Such a structure has been postulated for mouse and human telomeres, clearly suggested by the identification of the complementary RNA Telomeric repeat-containing RNA “TERRA”. However, the tremendous disparity in the information obtained with antibody-based technology drove us to investigate a new strategy. Based on the observation that DNA/RNA hybrids in a triplex complex genome co-purify with the double-stranded chromosomal DNA fraction, we developed a direct preparative approach from total protein-free cellular... 

The novel coronavirus pandemic has rapidly spread around the world since December 2019. Various techniques have been applied in identification of SARS-CoV-2 or COVID-19 infection including computed tomography imaging, whole genome sequencing, and molecular methods such as reverse transcription polymerase chain reaction (RT-PCR). This review article discusses the diagnostic methods currently being deployed for the SARS-CoV-2 identification including optical biosensors and point-of-care diagnostics that are on the horizon. These innovative technologies may provide a more accurate, sensitive and rapid diagnosis of SARS-CoV-2 to manage the present novel coronavirus outbreak, and could be... 

Background: Once aligned, long-reads can be a useful source of information to identify the type and position of structural variations. However, due to the high sequencing error of long reads, long-read structural variation detection methods are far from precise in low-coverage cases. To be accurate, they need to use high-coverage data, which in turn, results in an extremely time-consuming pipeline, especially in the alignment phase. Therefore, it is of utmost importance to have a structural variation calling pipeline which is both fast and precise for low-coverage data. Results: In this paper, we present SVNN, a fast yet accurate, structural variation calling pipeline for PacBio long-reads... 

The novel coronavirus pandemic has rapidly spread around the world since December 2019. Various techniques have been applied in identification of SARS-CoV-2 or COVID-19 infection including computed tomography imaging, whole genome sequencing, and molecular methods such as reverse transcription polymerase chain reaction (RT-PCR). This review article discusses the diagnostic methods currently being deployed for the SARS-CoV-2 identification including optical biosensors and point-of-care diagnostics that are on the horizon. These innovative technologies may provide a more accurate, sensitive and rapid diagnosis of SARS-CoV-2 to manage the present novel coronavirus outbreak, and could be... 

Background: Once aligned, long-reads can be a useful source of information to identify the type and position of structural variations. However, due to the high sequencing error of long reads, long-read structural variation detection methods are far from precise in low-coverage cases. To be accurate, they need to use high-coverage data, which in turn, results in an extremely time-consuming pipeline, especially in the alignment phase. Therefore, it is of utmost importance to have a structural variation calling pipeline which is both fast and precise for low-coverage data. Results: In this paper, we present SVNN, a fast yet accurate, structural variation calling pipeline for PacBio long-reads... 

Due to the widespread use of pesticides and their harmful effects on humans and wildlife, monitoring their residual amounts in crops is critically essential but still challenging regarding the development of high-throughput approaches. Herein, a colorimetric sensor array has been proposed for discrimination and identification of triazole fungicides using monometallic and bimetallic silver and gold nanoparticles. Aggregation-induced behavior of AgNPs, AuNPs, and Au-AgNPs in the presence of four triazole fungicides produced a fingerprint response pattern for each analyte. Innovative changes to the metal composition of nanoparticles leads to the production of entirely distinct response patterns... 

A novel method involving focusing of magnetic particles at the inner wall of a curved microchannel and secondary Dean flow-based exchange of their fluid was investigated. Solution exchange occurred in a hybrid microchip at very high throughput and with unprecedented solution exchange and particle isolation efficiencies of 99.2% and 90%, respectively. © 17CBMS-0001  

Concentration gradient generators (CGGs) help biologists to perform large scale, fast and high-throughput experiments. This paper introduces a design tool called Tree-like Concentration gradient generator Design Tool (TCDT). The performance of this tool is validated both numerically and experimentally. Three CGGs were fabricated using three different fabrication methods and design parameters. The performance of these devices was examined using the measurement of fluorescent and dye intensity. The performance of the design tool for non-linear and multi-drug concentration gradient generations was investigated as well. In addition, a method was developed to investigate the multi-drug... 

Many problems in applied machine learning deal with graphs (also called networks), including social networks, security, web data mining, protein function prediction, and genome informatics. The kernel paradigm beautifully decouples the learning algorithm from the underlying geometric space, which renders graph kernels important for the aforementioned applications. In this article, we give a new graph kernel, which we call graph traversal edit distance (GTED). We introduce the GTED problem and give the first polynomial time algorithm for it. Informally, the GTED is the minimum edit distance between two strings formed by the edge labels of respective Eulerian traversals of the two graphs.... 

Providing Quality-of-Service (QoS) in many-core network-on-chip (NoC) platforms is critical due to the high level of resource sharing in such systems. This article presents a hard-built Equality-of-Service (EoS) and Differential-Service (DS) as subsets of QoS in NoC using weighted round-robin arbitration policy. In the proposed technique, packets can be injected with variable initial weights. An enhanced dynamic weight incremental technique is proposed that automatically increases the weights according to the contention degree that packets face along their paths. The proposed technique provides EoS for all packets that are injected with equal initial weights. Furthermore, the router's input... 

The inertial microfluidic technique, as a powerful new tool for accurate cell/particle separation based on the hydrodynamic phenomenon, has drawn considerable interest in recent years. Despite numerous microfluidic techniques of particle separation, there are few articles in the literature on separation techniques addressing external outlet geometry to increase the throughput efficiency and purity. In this work, we report on a spiral inertial microfluidic device with high efficiency (>98%). Herein, we demonstrate how changing the outlet geometry can improve the particle separation throughput. We present a complete separation of 4 and 6 μm from 10 μm particles potentially applicable to... 

Animal models and traditional cell cultures are essential tools for drug development. However, these platforms can show striking discrepancies in efficacy and side effects when compared to human trials. These differences can lengthen the drug development process and even lead to drug withdrawal from the market. The establishment of preclinical drug screening platforms that have higher relevancy to physiological conditions is desirable to facilitate drug development. Here, a heart-on-a-chip platform, incorporating microgrooves and electrical pulse stimulations to recapitulate the well-aligned structure and synchronous beating of cardiomyocytes (CMs) for drug screening, is reported. Each chip... 

Cell-laden hydrogel microcapsules enable the high-throughput production of cell aggregates, which are relevant for three-dimensional tissue engineering and drug screening applications. However, current microcapsule production strategies are limited by their throughput, multistep protocols, and limited amount of compatible biomaterials. We here present a single-step process for the controlled microfluidic production of single-core microcapsules using enzymatic outside-in cross-linking of tyramine-conjugated polymers. It was hypothesized that a physically, instead of the conventionally explored biochemically, controlled enzymatic cross-linking process would improve the reproducibility,... 

In this paper, we consider a wireless cooperative network with a wireless-powered energy harvesting (EH) relay. The relay employs a time switching (TS) policy that switches between the EH and data decoding (DD) modes. Both energy and data buffers are kept at the relay to store the harvested energy and decoded data packets, respectively. In this paper, we derive static and dynamic TS policies that maximize the system throughput or minimize the average transmission delay. In particular, in the static policies, the EH or DD mode is selected with a pre-determined probability. In contrast, in a dynamic policy, the mode is selected dynamically according to the states of data and energy buffers. We... 

The widespread growth of Big Data and the evolution of Internet of Things (IoT) technologies enable cities to obtain valuable intelligence from a large amount of real-time produced data. In a Smart City, various IoT devices generate streams of data continuously which need to be analyzed within a short period of time; using some Big Data technique. Distributed stream processing frameworks (DSPFs) have the capacity to handle real-time data processing for Smart Cities. In this paper, we examine the applicability of employing distributed stream processing frameworks at the data processing layer of Smart City and appraising the current state of their adoption and maturity among the IoT... 

In this paper, we study the secrecy throughput in a massive Multiple-Input-Multiple-Output (MIMO) full-duplex wireless powered communication network (WPCN). The network consists of a massive MIMO base station (BS) and two groups of single- antenna sensor nodes which harvest energy from the BS. The first group, referred to as information transmitters (ITs), use the harvested energy to transmit information back to the BS; the second group, referred to as energy receivers (ERs), use the harvested energy for non- transmission related operations. We consider a two-slot protocol. In the first time slot, all nodes harvest energy from the BS. In the second slot, ITs transmit information to the BS,... 

In this paper, we study the secrecy throughput of a full-duplex wireless powered communication network (WPCN) for Internet of Things (IoT). The WPCN consists of a full-duplex multiantenna base station (BS) and a number of sensor nodes. The BS transmits energy all the time, and each node harvests energy prior to its transmission time slot. The nodes sequentially transmit their confidential information to the BS, and the other nodes are considered as potential eavesdroppers. We first aim to optimize the sum secrecy throughput of the nodes. The optimization variables are the duration of the time slots and the BS beamforming vectors in different time slots. The optimization problem is shown to... 

In this paper, we investigate the secrecy throughput for a full-duplex wireless powered communication network. A multi-antenna base station (BS) transmits energy towards nodes all the time and each node harvests energy prior to its transmission time slot. Nodes sequentially transmit their confidential information to the BS in presence of other nodes which are considered as potential eavesdroppers. We derive the secrecy rate and formulate the sum secrecy throughput optimization of all nodes. The optimization variables are the time slot duration and the BS beamforming during different transmission phases. The problem is non-convex and non-trivial. We propose a suboptimal approach in which the... 

Energy consumption and performance metrics have become critical issues for scheduling parallel task-based applications in high-performance computing systems such as cloud datacenters. The duplication and clustering strategy, as well as Dynamic Voltage Frequency Scaling (DVFS) technique, have separately been concentrated on reducing energy consumption and optimizing performance parameters such as throughput and makespan. In this paper, a dual-phase algorithm called EATSDCD which is an energy efficient time aware has been proposed. The algorithm uses the combination of duplication and clustering strategies to schedule the precedence-constrained task graph on datacenter processors through DVFS....