Sharif Digital Repository

This paper addresses the numerical simulation of thermo-fluid characteristics of triangular jets. The results of spatially developing, three dimensional jets from isosce-les and equilateral nozzles at different Reynolds numbers and distances between jets are presented. The system of governing equations, subject to the proper boundary condi-tions is solved with the finite volume method with collo-cated grid arrangement. SIMPLEC algorithm was used for the pressure-velocity coupling to discrete the governing equations of flow and energy. The turbulent stresses are approximated using k-ε model. The velocity and tempera-ture fields are presented and rates of their decay at jet cen-terline are... 

This paper describes optimization of the combustion chamber geometry and injection timing of a new generation of EF7 engine, where CNG is directly injected to the combustion chamber, with the aim of providing the best mixture at low and high speeds. The Multi-Objective Genetic Algorithm (MOGA) is coupled with the KIVA Computational Fluid Dynamics (CFD) code, with grid generation, in order to maximize the flammable mass of the mixture. This would result in better combustion and improved fuel economy. The optimization variables related to the combustion chamber are seven geometry variables and injection timing. Through the present optimization, a great improvement in mixture distribution is... 

This study presents a semi analytical solution for the transient weakly underexpanded jet. Different polytropic processes are compared with available experimental data in the literature to assess the best process for steady and transient weakly underexpanded jets. The steady state results agree reasonably well with the experimental and analytical data. It is also shown that isentropic process evaluates steady injection better than other processes. Tip penetration of transient results was compared with available data in literature, and no exact agreement for isothermal and isentropic is observed. This appears due to the linearization of equation of state. It is suggested that more accurate... 

Despite great advances, molecular cancer pathology is often limited to the use of a small number of biomarkers rather than the whole transcriptome, partly due to computational challenges. Here, we introduce a novel architecture of Deep Neural Networks (DNNs) that is capable of simultaneous inference of various properties of biological samples, through multi-task and transfer learning. It encodes the whole transcription profile into a strikingly low-dimensional latent vector of size 8, and then recovers mRNA and miRNA expression profiles, tissue and disease type from this vector. This latent space is significantly better than the original gene expression profiles for discriminating samples... 

Solar energy-driven generation units can assist in moderating energy-linked environmental issues. For this target, a new solar heliostat-based generation unit is suggested for electricity generation as the crucial product. A heliostat-based solar unit with a closed Brayton cycle and thermal energy storage unit is coupled with a Kalina cycle and an absorption refrigeration unit through a single-effect absorption chiller as an inimitable series of power plants. Exergy, economic, and energy investigations are carried out to scrutinize the efficiency of the introduced unit, and a thorough parametric evaluation is performed. Multi-aspect optimization is implemented to identify the optimum... 

Natural gas has widely been used as a fuel in conventional Diesel and spark ignition engines. The better understanding of injector parameters on the jet structure is helpful for the combustion optimization. This paper presents an experimental and numerical study on the jet structure of gaseous fuel injector in spark ignition direct injection engine by Schlieren technique and numerical procedure. Helium was injected through a gaseous injector at the different pressure ratios and nozzle diameters to understand the effects of nozzle geometry and pressure ratio for a dedicated correlation of CNG-SIDI injector. It was found that higher pressure ratio and exit nozzle diameter led to more tip... 

To mitigate global warming and fossil fuel shortages a novel oxy-fuel combustion power plant integrated with a power to gas system is proposed. A net-zero emission MATIANT cycle with inherent CO2 capture ability is selected as the power cycle also providing the CO2 and power demand of the power to gas system, which comprises a proton exchange membrane electrolyzer for hydrogen production and a Sabatier reactor for methanation. A techno-economic investigation, a multi-objective optimization, and a sensitivity analysis are carried out. A comprehensive economic method that covers all economic aspects is utilized, and a Sabatier reactor model which considers the possibility of the presence of... 

In budding yeast, the 3′ end processing of mRNA and the coupled termination of transcription by RNAPII requires the CF IA complex. We have earlier demonstrated a role for the Clp1 subunit of this complex in termination and promoter-associated transcription of CHA1. To assess the generality of the observed function of Clp1 in transcription, we tested the effect of Clp1 on transcription on a genomewide scale using the Global Run-On-Seq (GRO-Seq) approach. GRO-Seq analysis showed the polymerase reading through the termination signal in the downstream region of highly transcribed genes in a temperature-sensitive mutant of Clp1 at elevated temperature. No such terminator readthrough was observed... 

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 paper, 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 graph traversal edit distance is the minimum edit distance between two strings formed by the edge labels of respective Eulerian traversals... 

Understanding cell identity is an important task in many biomedical areas. Expression patterns of specific marker genes have been used to characterize some limited cell types, but exclusive markers are not available for many cell types. A second approach is to use machine learning to discriminate cell types based on the whole gene expression profiles (GEPs). The accuracies of simple classification algorithms such as linear discriminators or support vector machines are limited due to the complexity of biological systems. We used deep neural networks to analyze 1040 GEPs from 16 different human tissues and cell types. After comparing different architectures, we identified a specific structure... 

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.... 

Graph Traversal Edit Distance (GTED) is a measure of distance (or dissimilarity) between two graphs introduced. This measure is based on the minimum edit distance between two strings formed by the edge labels of respective Eulerian traversals of the two graphs. GTED was motivated by and provides the first mathematical formalism for sequence coassembly and de novo variation detection in bioinformatics. 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,... 

The human protein disulfide isomerase (hPDI), is an essential four-domain multifunctional enzyme. As a result of disulfide shuffling in its terminal domains, hPDI exists in two oxidation states with different conformational preferences which are important for substrate binding and functional activities. Here, we address the redox-dependent conformational dynamics of hPDI through molecular dynamics (MD) simulations. Collective domain motions are identified by the principal component analysis of MD trajectories and redox-dependent opening-closing structure variations are highlighted on projected free energy landscapes. Then, important structural features that exhibit considerable differences... 

Background MicroRNAs (miRNAs) are frequently deregulated in various types of cancer. While antisense oligonucleotides are used to block oncomiRs, delivery of tumour-suppressive miRNAs holds great potential as a potent anti-cancer strategy. Here, we aim to determine, and functionally analyse, miRNAs that are lowly expressed in various types of tumour but abundantly expressed in multiple normal tissues. Methods The miRNA sequencing data of 14 cancer types were downloaded from the TCGA dataset. Significant differences in miRNA expression between tumor and normal samples were calculated using limma package (R programming). An adjusted p value < 0.05 was used to compare normal versus tumor miRNA... 

A mobile robot should be able to analyze what it is seeing in real time rate and decide accordingly. Fast and reliable analysis of image data is one of the key points in soccer robot performance. In this paper we suggest a very fast method for object finding which uses the concept of perspective view. In our method, we introduce a set of jump points in perspective on which we search for objects. An object is estimated by a rectangle surrounding it. A vector based calculation is introduced to find the distance and angle of a robot from objects in the field. In addition we present a new color model which takes its components from different color models. The proposed method can detect all... 

Arvand is the name of robots specially designed and con-structed by sharif CE team for playing soccer according to RoboCup rules and regulations for the middle size robots. Two different types of robots are made, players and the goal keeper. A player robot consists of three main parts: mechanics (motion mechanism and kicker), hard-ware (image acquisition, processing unit and control unit) and software (image processing, wireless communication, motion control and decision making). The motion mechanism is based on two drive unit, two steer units and a castor wheel. We designed a special control board which uses two microcontrollers to carry out the software system decisions and transfers them... 

Arvand is a robot specially designed and constructed for playing soccer according to RoboCup rules and regulations for the medium size robots. This robot consists of three main parts: mechanics (motion mechanism and kicker), hardware (image acquisition, processing unit and control unit) and software (image processing, wireless communication, motion control and decision making). The motion mechanism is based on a drive unit, a steer unit and a castor wheel. We designed a special control board which uses two microcontrollers to carry out the software system decisions and transfers them to the robot mechanics. The software system written in C++ performs real time image processing and object... 

The vacuum sector of the Brans-Dicke theory is studied from the viewpoint of a non-conformally invariant gravitational model. We show that, this theory can be conformally symmetrized using an appropriate conformal transformation. The resulting theory allows a particle interpretation, and suggests that the quantum aspects of matter may be geometrized