Among several separation processes, the air flotation distinguish as remarkably high potential separation process related to its high separation efficiency and throughput, energy-efficient, simple process, cost-effective, applicable to a wide range of oily wastewater and no by-products. The current study aimed to investigate the effect of the type and concentration of surfactant on the stability of oil-water emulsion and efficiency of the separation process. For this purpose, three types of surfactant where used (anionic SDS, mixed nonionic Span 85/Tween 80, and cationic CTAB). The results demonstrated that the Span 85/Tween 80 surfactant has the best stability, and it increases with the surfactant concentration augmentation. The removal ef

Background: The need of the patient for a more reasonable esthetic orthodontic intervention has risen nowadays. Thus, orthodontists make use of esthetic orthodontic materials like brackets, ligature elastics, and arch wires. The esthetic brackets come as different forms of materials, such as ceramic brackets, which have their stainability remaining as the most important consideration for the patients and the orthodontists. This study aimed to compare the staining effects of various staining materials, including black tea, cigarette smoke and Pepsi, as well as the time effect on the color stability of sapphire ceramic brackets bonded with three kinds of light cure orthodontic adhesives: Transbond, Resilience and Enlight. Materials and Met

This study aims to identify the degree of Arabic language teachers at the secondary stage possessing the teaching competencies necessary to develop the skills of literary savor among their students from the perception of educational leaders in Bisha Province. To achieve the objectives of the study, the descriptive approach was used by adopting a comprehensive survey method. The study sample consisted of (48) school principals and Arabic language supervisors in Bisha Province who supervise the teaching of Arabic language at the secondary level in Bisha Province. The necessary data was collected using a questionnaire. The results of the study revealed that the evaluation of the study sample for the degree to which Arabic language teachers

Background: Chronic periodontitis is a bacterial infection that result in bone destruction associated with the increasing level of salivary tumor necrosis alpha and interleukin6 that affect Mother-infant bonding status. The aim of the present study was to assess the relationship between the Mother-infant bonding status in mothers with chronic periodontitis in relation to Salivary Tumor necrosis factor alpha and Salivary Interleukin6. Materials and Methods: The selected sample consisted of mothers with chronic periodontitis compared with mothers with healthy periodontium in postpartum period, their age ranged between 30-40 years. Both groups were subjected to postpartum Bonding Questionnaire (PBQ). Periodontal health status was assessed f

This study aims to determine the reasons for the increase in the frequency of sand and dust storms in the Middle East and to identify their sources and mitigate them. A set of climatic data from 60 years (1960–2022) was analyzed. Sand storms in Iraq are a silty sand mature arkose composed of 72.7% sand, 25.1% silt, and 2.19% clay; the clay fraction in dust storms constitutes 70%, with a small amount of silt (20.6%) and sand (9.4%). Dust and sand storms (%) are composed of quartz (49.2, 67.1), feldspar (4.9, 20.9), calcite (38, 5), gypsum (4.8, 0.4), dolomite (0.8, 1.0), and heavy minerals (3.2, 6.6). Increasing temperatures in Iraq, by an average of 2 °C for sixty years, have contributed to an increase in the number of dust storm

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N