Sharif Digital Repository

Motivation: The interactions among proteins and the resulting networks of such interactions have a central role in cell biology. Aligning these networks gives us important information, such as conserved complexes and evolutionary relationships. Although there have been several publications on the global alignment of protein networks; however, none of proposed methods are able to produce a highly conserved and meaningful alignment. Moreover, time complexity of current algorithms makes them impossible to use for multiple alignment of several large networks together.Results: We present a novel algorithm for the global alignment of protein-protein interaction networks. It uses a greedy method,... 

In this paper, the performance of a novel HDH solar desalination system equipped with a combination of heat pipe (HP), evacuated tube collector (ETC) and air bubble column humidifier is experimentally investigated. This novel HDH system uses advantages of ETC-HP as a highly efficient thermal absorption and conductor device, and at the same time employs the advantages of an air bubble column humidifier, i.e. high interface area and effective mixing in order to heat the water and humidify the air, respectively. The effects of various parameters including incoming air flow rate into the humidifier, initial depth of water in the humidifier, and adding fluids such as oil and water in the space... 

Image fusion means to integrate information from one image to another image. Medical images according to the nature of the images are divided into structural (such as CT and MRI) and functional (such as SPECT, PET). This article fused MRI and PET images and the purpose is adding structural information from MRI to functional information of PET images. The images decomposed with Nonsubsampled Contourlet Transform and then two images were fused with applying fusion rules. The coefficients of the low frequency band are combined by a maximal energy rule and coefficients of the high frequency bands are combined by a maximal variance rule. Finally, visual and quantitative criteria were used to... 

Echocardiography as a common place device has been widely used for diagnosis. Segmentation of left ventricle just using the standard level set formulation based on the magnitude of intensity cannot restrict the contour evolution completely due to the lack of sharp edges. This paper aims to introduce a robust method for segmentation of three-dimensional echocardiography images based on two boundary maps namely distance map and probabilistic map as stopping criteria of contour evolution which are extracted using two different approaches. The distance map is extracted by applying Free Form Deformation (FFD) method on manually determined landmarks of initial spherical volume to register the... 

In this paper, an efficient approach for ultrasonic object segmentation with special application for left ventricle segmentation in echocardiography images is proposed. At first, an efficient hybrid trend for ultrasonic image edge detection is suggested. Then, a modified level set approach is introduced based on the extracted edges and the computed probabilistic map as the stopping criteria for the contour evolution. Both synthetic and clinical images are utilized as validation measures with respect to the prior techniques which indicate outperform results quantitatively and qualitatively. Left ventricle segmentation using proposed method illustrates expert-approved performance, providing a... 

The substitution of conventional mathematical models with fast and accurate modeling tools can result in the further development of desalination technologies and tackling the need for freshwater. Due to the great capability of data-driven methods in analyzing complex systems, several attempts have been made to study various desalination systems using data-driven approaches. In this state-of-the-art review, the application of various artificial intelligence and design of experiment data-driven methods for analyzing different desalination technologies have been thoroughly investigated. According to the applications of data-driven methods in the field of desalination, the reviewed... 

Automatic extraction of the varying regions of magnetic resonance images is required as a prior step in a diagnostic intelligent system. The sparsest representation and high-dimensional feature are provided based on learned dictionary. The classification is done by employing the technique that computes the reconstruction error locally and non-locally of each pixel. The acquired results from the real and simulated images are superior to the best MRI segmentation method with regard to the stability advantages. In addition, it is segmented exactly through a formula taken from the distance and sparse factors. Also, it is done automatically taking sparse factor in unsupervised clustering methods... 

Sparse representation is a powerful tool for image processing, including noise removal. It is an effective method for Gaussian noise removal by taking advantage of a fixed and learned dictionary. In this study, the variable distribution of Rician noise is reduced in magnetic resonance (MR) images by sparse representation based on reconstruction error sets. Standard deviation of Gaussian noise is used to find these errors locally. The proposed method represents two formulas for local error calculation using standard deviation of noise. The acquired results from the real and simulated images are comparable, and in some cases, better than the best Rician noise removal method due to the... 

A novel combined power and refrigeration cycle is introduced and analyzed from the thermodynamic standpoint. The proposed cycle is an integration of a Kalina cycle equipped with an ejector (EKalina) and an ejector refrigeration cycle (ERC). In order to enhance the overall cycle performance, the possibility of employing two-phase ejectors in combined power and refrigeration cycles is studied. A parametric analysis is conducted to investigate the effects of the key thermodynamic parameters namely turbine inlet pressure, split ratio, basic ammonia concentration, heat source and evaporator temperatures on the cycle performance. The developed model is also verified with available data and it is... 

This paper presents solid-state ligand exchange of spin-coated colloidal lead sulfide quantum dot (PbS QD) films by methylammonium iodide (MAI) and integration of them in depleted heterojunction solar (DHS) devices having an antireflecting (AR) nanocone plastic structure. Time-resolved photoluminescence measurements determine a shorter lifetime of the charge carries on a semiconductor (TiO2) electron transfer layer for the MAI-passivated QD films as compared with those with long-chain aliphatic or short thiol ligands. Consequently, the DHS device yields improved power conversion efficiency (>125%) relative to oleic-acid-passivated PbS QD films. Using anodized aluminum oxide templates, an... 

Interfacial studies and band alignment engineering on the electron transport layer (ETL) play a key role for fabrication of high-performance perovskite solar cells (PSCs). Here, an amorphous layer of SnO2 (a-SnO2) between the TiO2 ETL and the perovskite absorber is inserted and the charge transport properties of the device are studied. The double-layer structure of TiO2 compact layer (c-TiO2) and a-SnO2 ETL leads to modification of interface energetics, resulting in improved charge collection and decreased carrier recombination in PSCs. The optimized device based on a-SnO2/c-TiO2 ETL shows a maximum power conversion efficiency (PCE) of 21.4% as compared to 19.33% for c-TiO2 based device.... 

The fabrication of efficient perovskite solar cells (PSCs) using all-vacuum processing is still challenging due to the limitations in the vacuum deposition of the hole transporting layer (HTL). Herein, inverted PSCs using copper (II) phthalocyanine (CuPC) as an ideal alternative HTL for vacuum processing are fabricated. After proper optimization, a PSC with a power conversion efficiency (PCE) of 20.3% is achieved, which is much better than the PCEs (16.8%) of devices with solution-based CuPC. As it takes a long time to dissolve CuPC in the solution-based device, the evaporation approach has better advantage in terms of fast processing. In addition, the device with the evaporated CuPC HTL... 

Stability is the main challenge in the field of perovskite solar cells (PSCs). Finding new strategies is required to protect the PSCs from deteriorating agents such as humidity, heating, and illumination. Herein, a new electron transporting layer (ETL), i.e., CdSe/ZnS quantum dots (QDs), is proposed for the fabrication of efficient and stable PSCs. CdSe/ZnS QDs layer not only works as an ETL but also has downshifting property, which can improve both efficiency and stability of the PSCs. Using CdSe/ZnS QDs ETL with green emission, a PSC with maximum power conversion efficiency (PCE) of 18% is achieved. More importantly, the device shows great UV stability, much better than the device with... 

This paper presents the results obtained and the deductions made from a series of microstructural studies and mechanical tests involving gray cast iron which was sand cast using a variety of modules. The effect of cooling rate on the primary dendrite arm spacing (DAS), secondary dendrite arm spacing (SDAS), thickness of ferrite-cementite layer (λe) and the hardness (HB) were evaluated. Results show that the both DAS and SDAS and also λe are highly dependent on the cooling rate, and they decreases as the cooling rate increases. More attempts were also done to correlate the HB with DAS, SDAS and λe. It was found that HB increases as DAS, SDAS and λe decreases  

Performance of a small-scale trigeneration system driven by low-temperature geothermal sources for producing fresh water, heating (hot water) and electricity is investigated from thermodynamic and economic standpoints. This system, utilizing a single stage absorption heat transformer leads to an increase in heat source temperature to be used in single stage evaporation desalination process and also providing water heating. Furthermore, an organic Rankine cycle is used for electric power generation. The developed model is validated with available data and effects of decision variables namely geothermal source, absorber and condenser temperatures on energy and exergy efficiencies of the... 

A new computational algorithm is introduced in the present study to solve multimaterial topology optimization problems. It is based on the penalization of the objective functional by the multiphase volume constrained Ginzburg-Landau energy functional. The update procedure is based on the gradient flow of the objective functional by a fractional step projected steepest descent method. In the first step, the new design is found based on the projected steepest descent method to ensure the reduction in the objective functional, simultaneously satisfying the control constraints. In the second step, regularization step, an H1 regularity of the solution is ensured while keeping the feasibility of... 

The goal of the present study is to predict the formation of solidification induced defects in castings by thermal criteria functions. In a criterion function method, the heat transfer equation is firstly solved, and then the susceptibility of defect formation at every point in the casting is predicted by computing a local function, criterion function, using results of the thermal analysis. In the first part of the paper, some famous criteria functions, in particular, the Pellini and Niyama criteria, are analyzed and their shortcomings are discussed in details. Then, a new criterion function is suggested to decrease the shape-dependency issue of the former criteria. The feasibility of the... 

The minimization of volume constrained vector-valued Ginzburg-Landau energy functional is considered in the present study. It has many applications in computational science and engineering, like the conservative phase separation in multiphase systems (such as the spinodal decomposition), phase coarsening in multiphase systems, color image segmentation and optimal space partitioning. A computationally efficient algorithm is presented to solve the space discretized form of the original optimization problem. The algorithm is based on the constrained nonmonotone L2 gradient flow of Ginzburg-Landau functional followed by a regularization step, which is resulted from the Tikhonov regularization...