Metal oxide nanoparticles, including iron oxide, are highly considered as one of the most important species of nanomaterials in a varied range of applications due to their optical, magnetic, and electrical properties. Iron oxides are common compounds, extensive in nature, and easily synthesized in the laboratory. In this paper, iron oxide nanoparticles were prepared by co-precipitation of (Fe⁺²) and (Fe⁺³) ions, using iron (II and III) sulfate as precursor material and NH₄OH solution as solvent at 90°C. After the synthesis of iron oxide particles, it was characterized using X-ray diffraction (XRD), infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). These tests confirmed the obtaining o

The heavy metal cadmium is extremely harmful to both humans and animals. Zinc supplementation protects the biological system and reduces cadmium-induced toxicity. This study aimed to determine whether zinc chloride (ZnCl2) could protect male mice with the damaged liver induced by cadmium chloride (CdCl2). The protective role of zinc chloride and expression of the metallothionein (MT), Ki-67, and Bcl-2 apoptotic proteins in hepatocytes were studied after subchronic exposure of mice to cadmium chloride for 21 days. Thirty male mice were randomly categorized into 6 groups (5 mice/group) as follows: a control group that did not receive any treatment, a group given ZnCl2 at 10 mg/kg alone, and two groups received ZnCl2 (10 mg/kg) i

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

Particulate matter (PM) emitted from diesel engine exhaust have been measured in terms of mass, using
99.98 % pure ethanol blended directly, without additives, with conventional diesel fuel (gas – oil),to
get 10 % , 15 %, 20 % ethanol emulsions . The resulting PM collected has been compared with those
from straight diesel. The engine used is a stationary single cylinder, variable compression ratio Ricardo
E6/US. This engine is fully instrumented and could run as a compression or spark ignition.
Observations showed that particulate matter (PM) emissions decrease with increasing oxygenate
content in the fuel, with some increase of fuel consumption, which is due to the lower heating value of
ethanol. The reduction in

Background: Poly (methyl methacrylate) has several disadvantages (poor mechanical properties) like impact and transverse strength. In order to overcome these disadvantages, several methods were used to strengthen the acrylic resin by using different fibers or fillers. This study was conducted to evaluate the effect of Plasma treatment of the fiber on mechanical properties Poly (methyl methacrylate) denture base material. Materials and methods: Specimens were prepared from poly methyl metha acrylic (PMMA) divided according to present of fiber into 4 groups (first group without fiber as control group, second group with Plasma treated polyester fibers, third group with Plasma treated polyamide fibers and fourth group Plasma treated combination

The present work elucidates the utilization of activated carbon (AC) and activated carbon loaded with silver nanoparticles (AgNPs-AC) to remove tetracycline (TC) from synthetically polluted water. The activated carbon was prepared from tea residue and loaded with silver nanoparticles. Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET) were used to characterize the activated carbon (AC) and silver nanoparticles-loaded activated carbon (AgNPs-AC). The impact of various parameters on the adsorption effectiveness of TC was examined. These variables were the initial adsorbate concentration (Co), solution acidity (pH), adsorption time (t), and dosag