A pioneering idea for increasing the thermal performance of heat transfer fluids was to use ultrafine solid particles suspended in the base fluid. Nanofluids, synthesized by mixing solid nanometer sized particles at low concentrations with the base fluid, were used as a new heat transfer fluid and developed a remarkable effect on the thermophysical properties and heat transfer coefficient. For any nanofluid to be usable in heat transfer applications, the main concern is its long-term stability. The aim of this research is to investigate the effect of using four different surfactants (sodium dodecyl benzene sulfonate (SDBS), sodium dodecyl sulfate (SDS), cetyl trimethylammonium bromide (CTAB), and gum Arabic (GA)), each with three different

A simple, sensitive and accurate spectrophotometric method has been developed for the determination of salbutamol sulphate (SAB) and isoxsuprine hydrochloride (ISX) in pure and pharmaceutical dosage. The method involved oxidation of (SAB) and (ISX) with a known excess of N-bromosuccinamid in acidic medium, and subsequent occupation of unreacted oxidant in decolorization of Evans blue dye (EB). This, in the presence of SAB or ISX was rectilinear over the ranges 1.0-12.0, 1.0-11.0 µg/mL, with molar absorptivity 4.21×10⁴ and 2.58×10⁴ l.mol^-1.cm^-1 respectively. The developed method had been successfully applied for the determination of the studied drugs in their pharmaceutical dosage resulting i

العلاقة بين تعبير المعلمات المناعية ل (P53) وعدم استقرار الساتل الميكروي  (MSI) مع العوامل السريرية المرضية لسرطان المعدة الغدي باستخدام الكيمياء النسيجية المناعية. الخلاصة الخلفية: يحدث سرطان المعدة الغدي بسبب عدم استقرار الكروموسومات، وطفرات TP53، واختلال الصيغة الصبغية، والانتقالات، والجينات الورمية الأولية، والتغيرات الجينية المثبطة للورم.عدم استقرار الساتل الميكروي(MSI)  يسبب فشل إصلاح عدم تطابق الحم

Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation