This research seeks to try to address one of the important issues in society that prevents the state from achieving its social, economic, political and financial goals, represented by the low tax proceeds, through which it can achieve those goals. What is reflected on the tax proceeds, knowing that the General Tax Authority does not take into account the issue of analyzing the opportunity cost of corporate capital as one of the profit indicators when setting the annual controls, which leads to a decrease in the tax proceeds, and therefore the research objective will be to shed light on the importance of adopting the concept of analysis The opportunity cost by the General Tax Authority to achieve a tax proceeds commensurate with t

The aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.

Many oil and gas processes, including oil recovery, oil transportation, and petroleum processing, are negatively impacted by the precipitation and deposition of asphaltene. Screening methods for determining the stability of asphaltenes in crude oil have been developed due to the high cost of remediating asphaltene deposition in crude oil production and processing. The colloidal instability index, the Asphaltene-resin ratio, the De Boer plot, and the modified colloidal instability index were used to predict the stability of asphaltene in crude oil in this study. The screening approaches were investigated in detail, as done for the experimental results obtained from them. The factors regulating the asphaltene precipitation are different fr

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

 Our research was launched in the study of the sustainable conflict of globalization and the rebalancing of the great powers that have made life on the earth unstable and insecure over the past and present eras, the purpose of which is to pay attention to the waste and instability that human societies are exposed to in different proportions between abstract right and continuous deviation.

The purpose of the study is to show the loss, waste and backwardness in managing and governing societies towards private interests, away from the standards of good institutional governance.

The study’s design was based on two demands, the first on the nature and eternity of