The most common cause of upper respiratory tract infection is coronavirus, which has a crown appearance due to the existence of spikes on its envelope. D-dimer levels in the plasma have been considered a prognostic factor for COVID-19 patients.

In the present work a modification was made on three equations to represent the
experiment data which results for Iraqi petroleum and natural asphalt. The equations
have been developed for estimating the chemical composition and physical properties
of asphalt cement at different temperature and aging time. The standard deviations of
all equations were calculated.
The modified correlation related to the aging time and temperature with penetration
index and durability index of aged petroleum and natural asphalts were developed.
The first equation represents the relationship between the durability index with aging
time and temperature.

log_e(DI)=a₁+0.0123(2log_e T

An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter

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

تعد المحاسبة بشكل عام علماً لكنها ليست من العلوم الصرفة وإنما من العلوم الإجتماعية مما يتطلب للتعامل مع المواضيع المحاسبية الأخذ بنظر الاعتبار الأشخاص المعنيين بالموضوع سواء كانوا المعدين للمخرجات المحاسبية أي المحاسبين، أو الاطراف ذوي المصالح المعنيين والمستفيدين من هذه المخرجات أي المستخدمين، ويعد المحاسب جزءاً من العملية الاجرائية نفسها وبهذا يكون دوره مزدوجاً يجمع بين كونه القائم بالبحث والقي

A spherical-statistical optical model (SOM) has been used to calculate and evaluate the neutron interaction with medium nuclei (40 ). Empirical formulae of the optical potentials parameters are predicted with minimize accuracy compared with experimental bench work data. With these optical formulae an evaluation of the shape and compound elastic scattering cross-section of interaction neutrons with ⁵⁶Fe nuclei at different energy range (1-20) MeV has been calculated and compared with experimental results. Also, volume integrals for real and imaginary potential energies have been evaluated and matched with the standard ABAREX code. Good agreements with have been achieved with the available experimental data.

This study aims to model the flank wear prediction equation in metal cutting, depending on the workpiece material properties and almost cutting conditions. A new method of energy transferred solution between the cutting tool and workpiece was introduced through the flow stress of chip formation by using the Johnson-Cook model. To investigate this model, an orthogonal cutting test coupled with finite element analysis was carried out to solve this model and finding a wear coefficient of cutting 6061-T6 aluminum and the given carbide tool.