THE PROBLEM OF TRANSLATING METAPHOR IN AN ARTISTIC TEXT (ON THE MATERIAL OF RUSSIAN AND ARABIC LANGUAGES)

Introduction and Aim: Kruppel Like Factor 14 (KLF14) gene plays an important role in metabolic illnesses and is also involved in the regulation of many other biological processes. This study's objective was to determine whether or not the KLF14 single-nucleotide-polymorphism (SNP) known as rs972283 was linked to an increased risk of peptic ulcer disease in the population that was being investigated.   Materials and Methods: Participants in this study included 71 people who had been diagnosed with peptic ulcers and 50 people who were considered to be healthy controls. In order to genotype the KLF14 SNP rs972283, an amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) was carried out, and the PCR results were

One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

The researcher studied transportation problem because it's great importance in the country's economy. This paper which ware studied several ways to find a solution closely to the optimization, has applied these methods to the practical reality by taking one oil derivatives which is benzene product, where the first purpose of this study is, how we can reduce the total costs of transportation for product of petrol from warehouses in the province of Baghdad, to some stations in the Karsh district and Rusafa in the same province. Secondly, how can we address the Domandes of each station by required quantity which is depending on absorptive capacity of the warehouses (quantities supply), And through r

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

The study was conducted at the fields of the Department of Horticulture and Landscape Gardening,College of Agriculture, University of Baghdad during the growing seasons of 2013- 2014 .forPerformance of Evaluation Vegetative growth and yield traits and estimate some important geneticparameter on seven selected breed of tomato which (S1-S7 ) Pure line. the results found significantdifferences between breeds in all study trails except clusters flowering number .S1 significantly plantlength which reached 227.3 .Also S1,S2 and S4 were significantly increased the number fruit for plant,Fruit weight Increased in S3 ,S6 and plant yield. Increased in S1, S4 ,S5. Genetic variation valueswere low in Floral clusters , TSS and fruit firmest and medium i

Linear regression is one of the most important statistical tools through which it is possible to know the relationship between the response variable and one variable (or more) of the independent variable(s), which is often used in various fields of science. Heteroscedastic is one of the linear regression problems, the effect of which leads to inaccurate conclusions. The problem of heteroscedastic may be accompanied by the presence of extreme outliers in the independent variables (High leverage points) (HLPs), the presence of (HLPs) in the data set result unrealistic estimates and misleading inferences. In this paper, we review some of the robust

<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T