The aim of the research is to identify the losses resulting from the terrorist operations and then find a proposed accounting treatment for the losses resulting from the terrorist operations and to indicate their impact on disclosure in the financial statements by reviewing the international standards and local rules and the unified accounting system and not dealing with these losses, Of the financial statements and therefore adversely affect the accounting disclosure as well as the weak commitment of economic units to apply the requirements of accounting measurement and disclosure of losses of terrorist operations in a manner consistent with local and international standards to achieve the Reliability in the financial statement.

Catalase (EC 1.11.1.6) is a well known enzyme which exists in almost all living creatures exposing to oxygen (such as plants, bacteria, and animals). It is a very necessary enzyme to protect the cell from oxidative detriment by reactive oxygen species (ROS). The aim of this study is the partial purification and characterization of Catalase enzyme from Banana peels. In this study, fresh banana peels are treated with 70 % ethanol ,further separated with chloroform ,water and ethyl acetate respectively .The supernatant of the enzymatic sample which is treated with chloroform is loaded into gel filtration column with Sephadex G-100 (1.0 x 90 cm) equilibrated with pH7 buffer media (phosphate buffer 0.1 M). Kinetic studies of the purified en

Back ground: Oral isotretinoin is recommended
for sever nodulocystic acne in the doses 0.5-
2mg/kg/day which is usually associated with higher
incidence of adverse effects. To reduce the
incidence of side-effects and to make it more costeffective,
the lower dose regimen of isotretinoin has
been used.
Aim: To compare the efficacy and tolerability of
oral isotretinoin 10mg and 20mg/day in acne
vulgaris.
Methods: one hundred and twenty patients with
acne vulgaris were randomized into two treatment
regimens each consisting of 60 patients. The first
was treated with 10mg/day and the second group
with 20mg/day for 24 weeks. Fifty five patients
from the first group and 47 patients from the second

In this work, Kinetic Phosphorescence Analyzer (KPA) has been used to measure the concentrations of uranium (UC) and Amorphous crystals (AMO) in urine samples of breast cancer patients in Baghdad. Additionally, a relation between UC and AMO with respect to patient's age has been deduced and studied.
Forty one urine samples of patients and five for healthy were taken from females lived in different residential area of Baghdad. The measured maximum UC value for urine samples of patients was 2.35 ± 0.053, the minimum value was 0.86 ± 0.034 μg/L, and an overall average was 1.6 ± 0.027 μg/L while the average UC for healthy females was 1.03 ± 0.020 μg/L.
From these results, AMO concentrations were found for all breast cancer patie

Community detection is one of the most fundamental applications in understanding the structure of complicated networks. Furthermore, it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships. Networking structures are highly sensitive in social networks, requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks. In addition, they miss out on accurately identifying clusters. Since single-objective optimization cannot always generate accurate and comprehensive results, as multi-objective optimization can.Therefore,we utilized two objective

Early and accurate detection of COVID-19 from chest computed tomography (CT) scans are becoming essential for effective clinical decision-making and disease control. This study is proposing a robust deep learning framework that integrates a convolutional self-attention network (CSAN), gamma correction for image enhancement, and a voting-based ensemble classifier to improving diagnostic performance. The model is being evaluated on a dataset of 2,271 CT images and is achieving an accuracy of 95.12%, sensitivity of 97.25%, specificity of 98.11%, F1-score of 96.46%, and area under the curve (AUC) of 0.977. Experimental results are demonstrating that the proposed method significantly surpasses baseline models, including standalone CSAN,