The Audit evedances represent the reconciliation tools between the Financial data shown on financial statements, and the level of satisfaction level of the Auditor about these statements. According that, the Auditor try to achieve the highest quantity of These evidances, and the most satisfactive of it…, but that will be so hard sometimes, when the internal controlling system is not good, and when the Auditor had some satisfied evidences, but not sharp… So, this research comes to inspect the relation between the quantity, and the level of satisfaction, and argument to prove that evidences gives. This research assumes that getting enough evidences leads to reduce faults, improves the auditing operation, and avoids risks. The research

In this study, a mathematical model for the kinetics of solute transport in liquid membrane systems (LMSs) has been formulated. This model merged the mechanisms of consecutive and reversible processes with a “semi-derived” diffusion expression, resulting in equations that describe solute concentrations in the three sections (donor, acceptor and membrane). These equations have been refined into linear forms, which are satisfying in the special conditions for simplification obtaining the important kinetic constants of the process experimentally.

Abortion is categorized as the termination of conception caused by the failure or removal of the embryo from the uterus before the conclusion of pregnancy. Microorganisms and genetic factors are two of the many factors associated with abortion. Cytomegalovirus is a widespread congenital virus infection pathogen that affects a wide variety of people. The prothrombin gene is one of the essential causes that trigger blood clotting and the function of abortion women, therefore the aim of the study is to detect and associate Cytomegalovirus and prothrombin gene mutation (Gene ID: 14061 in NCBI) with abortion through genetic and immunological methods. Five ml of whole blood was collected from an intravenous puncture and divided into two tubes,

            Colon cancer is an abnormal growth of cells that occurs in the large intestine. Sometimes growth remains restricted for a relatively long time before it becomes a malignant tumor and then spreads through the intestinal wall to the lymph nodes and other parts of the body. The study aims to estimate the effectiveness and partial purification of lipoxygenase (LOX) enzyme and measure gamma-glutamyle transferase (GGT) activity in serum patients of colon cancer in Baghdad. The study included (80) case male patients with colon cancer with (50) samples of apparently healthy males (control) as comparison group. The result displayed a noteworthy increase in lipoxygenase effectivene

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Abstract Background:Breast cancer is the most common female cancer worldwide. Although mastectomy is considered the treatment of choice for the majority of cases of breast cancer; a noticeable percentage of breast cancer survivors claim they were never advised about reconstruction. It has been proven that breast reconstruction helps breast cancer survivors to overcome the trauma of their diagnosis and improve their psychological well-being.Objectives: To assess the level of awareness and expectations regarding breast reconstruction surgery among female with breast cancer survivors in Baghdad, and to find if there is association between sociodemographic data and expectations of breast reconstruction.Methodology: This is a cross sectional stu

In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and