Learning the vocabulary of a language has great impact on acquiring that language. Many scholars in the field of language learning emphasize the importance of vocabulary as part of the learner's communicative competence, considering it the heart of language. One of the best methods of learning vocabulary is to focus on those words of high frequency. The present article is a corpus based approach to the study of vocabulary whereby the research data are analyzed quantitatively using the software program "AntWordprofiler". This program analyses new input research data in terms of already stored reliable corpora. The aim of this article is to find out whether the vocabularies used in the English textbook for Intermediate Schools in Iraq are consistent with the vocabulary selection criteria already established in the field in terms of high/low frequency, coverage, word families and recycling. The findings of this study reveal that the Iraqi first intermediate school English textbook (English for Iraq) contains numerous number of vocabulary with low frequency, low number of word families, an average around 90% of coverage, and no/ or insufficient recycling. Therefore, a re-evaluation and modification was suggested to be done for this course.
المواقف افي الدول العربية قراءة تحليلية في مواقف لدولية من التغيير (الولايات المتحدة - الاتحاد الاوروبي - روسيا)
حزب العمال الكردستاني ودوره في تطوير القضية الكردية في تركيا من 1991-2013
Objective: The study aimed to assess Leucine-rich alpha-2-glycoprotein-1 biomarker serum level in hospitalized COVID-19 patients. Methods: The case control study from multi-centers in Baghdad included 45 adult patients (19 females and 26 males) with COVID-19, diagnosed with a positive real-time reverse transcription polymerase chain reaction and excluded negative RT-PCR for COVID-19 and comorbidity conditions. Second group, was 43 control (20 females and 23 males). Results: This study found a decrease Leucine-rich alpha-2-glycoprotein-1 biomarker serum level in these patients and a significant difference in D. dimer, neutrophil count, lymphocyte count, and the neutrophil-lymphocyte ratio between the patients and controls at a P valu
... Show MoreRecently, Systemic lupus erythematosus (SLE) was considered as one of the autoimmune diseases that the genetic and environmental factors contributed in the disease etiological profile. According to the environmental factors, infectious agents have been concluded to have a role in the etiology and pathogenesis of SLE. Chlamydia pneumoniae and Mycoplasma pneumoniae are among these infectious agents that have been suggested to be involved in the etiology of SLE. Accordingly, the current study was designed to assess the anti-C. pneumoniae and anti-M. pneumoniae IgG antibody status by enzyme linked immunosorbent assay (ELISA) in the sera of 64 Iraqi SLE females' patients and 32 Iraqi healthy females as controls. The patients' group were distribu
... Show MoreBackground: Occupational exposure to hazardous drugs occurs in all aspects of anticancer drug handling. Proper recommendations and guidelines should be applied to control and reduce exposure. Objective: To assess pharmacists' knowledge and practice regarding the safe handling of anticancer drugs. Methods: A cross-sectional study was conducted at seven major hospitals in Baghdad City, Iraq, from December 2023 to February 2024. A pre-designed questionnaire was given to pharmacists who handled anticancer drugs in chemotherapy units. The questionnaire comprises sociodemographic data, knowledge of the safe handling of cytotoxic drugs and thoughts about exposure and risk, practices for safely handling cytotoxic drugs, and challenges for s
... Show MoreIn this research prepared two composite materials , the first prepared from unsaturated polyester resin (UP) , which is a matrix , and aluminum oxide (Al2O3) , and the second prepared from unsaturated polyester resin and aluminum oxide and copper oxide (CuO) , the two composites materials (Alone and Hybrid) of percentage weight (5,10,15)% . All samples were prepared by hand layup process, and study the electrical and thermal conductivity. The results showed decrease electrical conductivity from (10 - 2.39) ×10-15 for (Up+ Al2O3) and from (10 - 2.06)×10-15 for (Up+ Al2O3+ CuO) .But increase thermal conductivity from( 0.17 - 0.505) for (Up+ Al2O3) and from (0.17 - 0.489) for (Up+ Al2O3+ CuO).
Nuclear structure of 29-34Mg isotopes toward neutron dripline have been investigated using shell model with Skyrme-Hartree–Fock calculations. In particular nuclear densities for proton, neutron, mass and charge densities with their corresponding rms radii, neutron skin thicknesses and inelastic electron scattering form factors are calculated for positive low-lying states. The deduced results are discussed for the transverse form factor and compared with the available experimental data. It has been confirmed that the combining shell model with Hartree-Fock mean field method with Skyrme interaction can accommodate very well the nuclear excitation properties and can reach a highly descriptive and predictive power when investiga
... Show MoreThe question about the existence of correlation between the parameters A and m of the Paris function is re-examined theoretically for brittle material such as alumina ceramic (Al2O3) with different grain size. Investigation about existence of the exponential function which fit a good approximation to the majority of experimental data of crack velocity versus stress intensity factor diagram. The rate theory of crack growth was applied for data of alumina ceramics samples in region I and making use of the values of the exponential function parameters the crack growth rate theory parameters were estimated.
Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin
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