Background: Postoperative morbidity after extraction of the impacted mandibular third molar (IMTM) is inevitable. One of the most common postoperative complication is alveolar osteitis (AO) which is a painful non healed socket. Many researches were attempted to prevent the occurrence of AO by introducing and applying a new materials inside the extraction socket. Platelet rich fibrin (PRF) is a biological complex fibrin matrix where autologous platelets and leucocytes are present, used to enhance tissue healing process and reduce the early adverse effects of the inflammation. Aims: To evaluate the effect of PRF on the incidence of AO. Also to assess PRF effect on pain, swelling, and trismus following the surgical removal of IMTM and compa

This study aims to assess the removal efficiency andestablish the BOD5 and COD statisticalcorrelation of the sewage flowing in Al-Diwaniyah wastewater treatment plant in Iraq during the study period (2005-2016). The strength of the influent wastewater entering the plant varied from medium to high in strength. High concentrations of BOD5 and COD in the effluent were obtained due to the poor performance of the plant. This was observed from the BOD5 /COD ratios that did not confirm with the typical ratios for the treated sewage. To improve the performance of this plant, regression equations for BOD5 and COD removal percentages were suggested which can be used to facilitate evaluation of liquid waste and optimal control process. The equations

The possibility of predicting the mass transfer controlled CaCO₃ scale removal   rate has been investigated.

Experiments were carried out using chelating agents as a cleaning solution at different time and Reynolds’s number. The results of CaCO₃ scale removal or (mass transfer rate) (as it is the controlling process) are compared with proposed model of prandtl’s and Taylor particularly based on the concept of analogy among momentum and mass transfer.

Correlation for the variation of Sherwood number ( or mass transfer rate ) with Reynolds’s number have been obtained .

In the present work, a study is carried out to remove chromium (III) from aqueous solution by: activated charcoal, attapulgite and date palm leaflet powder (pinnae). The effect of various parameters such as contact time, and temperature has been studied. The isotherm equilibrium data were well fitted by Freundlich and Langmuir isotherm models. The adsorption capacity of chromium (III) that was observed by activated charcoal, attapulgite and date palm leaflet powder (pinnae) increased with the rise of temperature when the concentrations of Cr (III) were 600, 700 and 100mg/L respectively. The greatest adsorption capacity ofactivated charcoal, attapulgite and date palm leaflet powder (pinnae) at 10°C was 7.51, 5.39 and 0.77mg.gˉ¹ respective

Release of industrial effluents comprising dyes in water bodies is one of the foremost causes of water pollution. Therefore, the proper and proficient treatment of these dyes contaminated left-over material before their release is crucial. Herein, an eco-friendly biological macromolecule Gum-Acacia (GA) integrated Fe3O4 nanoparticles composite hydrogel was manufactured via co-precipitation technique for effective adsorption of Congo red (CR) dye existing in water bodies. The as-prepared magnetic GA/Fe3O4 composite hydrogel was characterized by FTIR, XRD, EDX, VSM, SEM, and BET techniques. These studies discovered the fruitful fabrication of biodegradable magnetic GA/Fe3O4 composite hydrogel possessing porous structure with large surface are

Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.

The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed