Portland cement concrete is the most commonly used construction material in the world for decades. However, the searches in concrete technology are remaining growing to meet particular properties related to its strength, durability, and sustainability issue. Thus, several types of concrete have been developed to enhance concrete performance. Most of the modern concrete types have to contain supplementary cementitious materials (SCMs) as a partial replacement of cement. These materials are either by-products of waste such as fly ash, slag, rice husk ash, and silica fume or from a geological resource like natural pozzolans and metakaolin (MK). Ideally, the utilization of SCMs will enhance the concrete performance, minimize

This research presents an experimental investigation on the influence of metakaolin replacement percentage upon some properties of different concrete types. Three types of concrete were adopted (self- compacted concrete, high performance concrete and reactive powder concrete) all of high sulphate (SO3) percentage from the fine aggregate weight, 0.75%. Three percentages of metakaolin replacement were selected to be studied (5, 7 and 10) %. Three types of concrete properties (compressive, flexural and splitting tensile strength) were adopted to achieve better understanding for the influence of adding metakaolin.. The output results indicated that the percentage of metakaolin had a different level of positive effect on the compressive strength

The Canal lining is usually used to decrease seepage loss and raise water transport efficiency. Traditional unlined irrigation canals often suffer from significant water loss due to leakage and low water levels, negatively impacting hydraulic performance and irrigation efficiency. Despite the widespread use of irrigation canal lining, there have been few studies to evaluate the effect of different lining types in controlling seepage under varying conditions. This paper focuses on assessing the effect of two different types of concrete lining and concrete quilt on improving the hydraulic performance of the Bani Hassan irrigation canal. A one-dimensional steady-state hydraulic model was created using HEC-RAS version 6.6 software to si

Abstract

This study aims to identify the empathy of University Students, as well as the significant differences in sympathy in terms of gender and specialization. To achieve the aims of the study, a scale of empathy was administered to a sample of (450) students collected randomly from Baghdad university. The results showed that the study sample has a level of empathy. There is a significant difference between males and females in empathy, in favor of the female students. There is no significant difference in empathy in terms of specialization (scientific, humanities), and the interaction between males and females. The study came out with a number of recommendations and suggestions. 

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Objective:- Women's behavior during pregnancy which can affect the health of their infant , may be influenced by their attitude toward the pregnancy. The study was carried out to assess the pattern of health behaviors for pregnant women. Methodology: A descriptive study was carried out to select randomized (100) pregnant women attending Baghdad Teaching hospital. The data were collected through personal interview by using questionnaire form constructed for the purpose of the study. Results:- The result of the study revealed that the highest percentage of study sample were in age group (21-25) years, primary graduated and house wife . The results showed that the highest percentage( 64%) of them were primigravida, (72%) of them have (1-2)

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are