The effect of three ionic liquids viz., 1-hexyl-3-methylimidazolium tetrafluoroborate (ILE), 1-hexyl-3-metylimidazolium hexafluorophosphate (ILF) and 1-octyl-3-methylimidazolium tetrafluoroborate (ILG) when used as surfactants on the performance of dissolved air floatation (DAF) was investigated.

   Experiments were conducted at a temperature of 30-35 ºC, 10ppm ferric chloride as coagulant, 50% recycle ratio, pH 8, and 10 minutes treatment time  to find oil and grease (OG) and turbidity removal efficiencies at saturation pressure (2-6) bar.

ILs were used at concentration of 50 µl/liter of treated water in two positions in DAF system; the saturation vessel and the treatment tank. The performance using ILs

The catalytic cracking of three feeds of extract lubricating oil, that produced as a by-product from the process of furfural extraction of lubricating oil base stock in AL-Dura refinery at different operating condition, were carried out at a fixed bed laboratory reactor. The initial boiling point for these feeds was 140 ºC for sample (1), 86 ºC for sample (2) and 80 ºC for sample (3). The catalytic cracking processes were carried out at temperature range 325-400 ºC and initially at atmospheric pressure after 30 minutes over 9.88 % HY-zeolite catalyst load. The comparison between the conversion at different operating conditions of catalytic cracking processes indicates that a high yield was obtained at 375°C, according to gasoline pr

In the present work, the critical micelle concentration (CMC) of the solution of Sodium dodecyl sulfate (SDS) as anionic surfactant, Cocamidopropyl Betaine (CAPB) as amphoteric surfactant, and their mixture have been determined using surface tension and conductivity measurements at a temperature range 293 -323 K. The adsorption and thermodynamic micellization parameters (?G?m, ?G?ads, ?max ,Amin,?cmc ) for individual surfactants was calculated. Rosen model which is focuses on the adsorbed mixed surfactant film at the air/solution interface was used to calculate the interaction parameter ( ?? ) at the interface and the activity coefficients g1 and g2. The results indicate that the CMC of the individual surfactants was affected by

Hematological malignancies are important diseases that need more powerful therapeutics. Even with current targeting therapies, such as rituximab and other chemotherapeutic agents, there is a need to develop new treatment strategies. Combination therapy seems the best option to target the tumor cells by different mechanisms. Virotherapy is a very promising treatment modality, as it is selective, safe, and causes cancer destruction. The Iraqi strain of Newcastle disease virus (NDV) has proved to be effective both in vitro and in vivo. In the current work, we tested its ability on anti-hematological tumors and enhanced current treatments with combination therapy, and studied this combination using Chou–Talalay analysis. p53 concentration was

      Strategies to reduce obesity have become main priority for many health institution and health staff around the world, as the prevalence of obesity has risen and exacerbated in most of the world mainly because of the modern life style which tend to be more sedentary with an increase eating unhealthy fast western food. Many years ago, the lipid-lowering drug simvastatin; and omega-3 were considered as a traditional lipid-lowering drug that have been well-documented to possess anti-inflammatory, cardioprotective and triglyceride-lowering properties; and their co-administration may demonstrate a complementary effect in lowering patients' triglycerides and total cholesterol to treat atherosclerosis. Many previous studies have

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet