Objective. Glass-ionomer and resin-modified glass-ionomer cements are versatile materials with the ability to form a direct bond with tooth tissues. The aim of this study was to formulate a novel class of dental bio-interactive restorative material (pRMGIC) based on resin-modified glass-ionomer cements via the inclusion of an organophosphorus monomer, ethylene glycol methacrylate phosphate, with a potential to improve the mechanical properties and also function as a reparative restorative material. Methods. pRMGIC was formulated with modification of the resin phase by forming mixes of ethylene glycol methacrylate phosphate (EGMP; 0–40%wt) and 2-hydroxyethyl methacrylate monomer into the liquid phase of a RMGIC (Fuji II LC, GC Corp.).

Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this

New Schiff base ligand (E)-6-(2-(4-(dimethylamino)benzylideneamino)-2-(4-hydroxyphenyl)acetamido)-3,3- dimethyl-7-oxo-4-thia-1- azabicyclo[3.2.0]heptane-2-carboxylic acid = (HL) was synthesized via condensation of Amoxicillin and 4(dimethylamino)benzaldehyde in methanol. Figure -1 Polydentate mixed ligand complexes were obtained from 1:1:2 molar ratio reactions with metal ions and HL, 2NA on reaction with MCl2 .nH2O salt yields complexes corresponding to the formulas [M(L)(NA)2Cl],where M=Fe(II),Co(II),Ni(II),Cu(II),and Zn(II), A=nicotinamide .

In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

This study examines how Sahar Mustafah's book The Beauty of Your Face (2020) examines the intersectional aspects of Arab American identity. The novel traces the life of the Palestinian Arab American woman, Afaf Rahman who is a school principal. She negotiates the intricacies of gendered, religious, and cultural identities in America after 9/11. The analysis uses an intersectional lens to look at how Afaf's experiences as a woman, a Muslim, and an immigrant combine to influence how she sees herself and how she interacts with society at large. The book explores racial prejudice, misogyny, and Islamophobia, bringing to light the many difficulties Arab American women experience. Additionally, it shows the protagonist's autonomy and tenacity as

      That corruption with all its forms,  has prevailed over the whole world, but  with  different degrees relaying on the one who leads these countries of rulers, followers and officials who have been deemed  the main reason for that corruption, but if these  rulers  were righteous, These countries would have blessed and elevated and were corrupt unjust tyrants who were the disaster that befell the chiefs of those countries  with ruin, misery, and backwardness. This is what we sought to prove and clarify by considering the verses of the Holy Qur’an in respect with this topic. The research includes an introduction, two topics, and a conclusion.

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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

Erbil city is located in the northern Iraq with a population of over one million people. Due to water crises farmers usually use wastewater and well water for the agricultural production. In this study six stations were designed to sample waste water and three from well water to define waste water and ground water characteristics. In this study, Residual Na⁺ Carbonate, Mg⁺⁺ hazard, salinity hazard, Kelley index, %sodium, total hardness, permeability index, potential salinity, sodium adsorption ratio, and Irrigation Water Quality Index (IWQI) were determined. The order of average cation concentrations in water was Mg²⁺> Ca²⁺ > Na⁺ > K⁺. While the proportion of main

Physical model tests were simulated non-aqueous phase liquid (NAPL) spill in two-dimensional
domain above the water table. Four laboratory experiments were carried out in the sand-filled
tank. The evolution of the plume was observed through the transparent side of this tank and the
contaminant front was traced at appropriate intervals. The materials used in these experiments
were Al-Najaf sand as a porous medium and kerosene as contaminant.
The results of the experiments showed that after kerosene spreading comes to a halt (ceased) in
the homogeneous sand, the bulk of this contaminant is contained within a pancake-shaped lens
situated on top of the capillary fringe.