Colorectal cancer (CRC) remains a leading cause of cancer-related deaths worldwide, with tumor angiogenesis playing a pivotal role in its progression and metastasis. CD144 (VE-cadherin), a calcium-dependent adhesion molecule, is critical for endothelial cell integrity and has been linked to tumor angiogenesis and cancer stem cell phenotypes. This study aimed to evaluate the immunohistochemical expression of CD144 in benign colorectal lesions, normal adjacent tumor tissue (NRAT), and tumor tissues to elucidate its role in colorectal cancer progression. Multiple techniques, including immunohistochemistry, flow cytometry, Western blot, and qPCR, were used to assess CD144 expression and its association with the VEGF/VEGFR2 signaling pat

The increasing drinking water demand in many countries leads to an increase in the use of desalination plants, which are considered a great solution for water treatment processes. Reverse osmosis (RO) and electro-dialysis (ED) systems are the most popular membrane processes used to desalinate water at high salinity. Both systems work by separating the ionic contaminates and disposing of them as a brine solution, but ED uses electrical current as a driving force while RO uses osmotic pressure. A direct comparison of reverse osmosis and electro-dialysis systems is needed to highlight process development similarities and variances. This work aims to provide an overview of previous studies on reverse osmosis and electro-dial

Economic analysis plays a pivotal role in managerial decision-making processes. This analysis is predicated on deeply understanding economic forces and market factors influencing corporate strategies and decisions. This paper delves into the role of economic data analysis in managing small and medium-sized enterprises (SMEs) to make strategic decisions and enhance performance. The study underscores the significance of this approach and its impact on corporate outcomes. The research analyzes annual reports from three companies: Al-Mahfaza for Mobile and Internet Financial Payment and Settlement Services Company Limited, Al-Arab for Electronic Payment Company, and Iraq Electronic Gateway for Financial Services Company. The paper concl

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

An analytical approach based on field data was used to determine the strength capacity of large diameter bored type piles. Also the deformations and settlements were evaluated for both vertical and lateral loadings. The analytical predictions are compared to field data obtained from a proto-type test pile used at Tharthar –Tigris canal Bridge. They were found to be with acceptable agreement of 12% deviation.

               Following ASTM standards D1143M-07e1,2010, a test schedule of five loading cycles were proposed for vertical loads and series of cyclic loads to simulate horizontal loading .The load test results and analytical data of 1.95

Purpose – The Cloud computing (CC) and its services have enabled the information centers of organizations to adapt their informatic and technological infrastructure and making it more appropriate to develop flexible information systems in the light of responding to the informational and knowledge needs of their users. In this context, cloud-data governance has become more complex and dynamic, requiring an in-depth understanding of the data management strategy at these centers in terms of: organizational structure and regulations, people, technology, process, roles and responsibilities. Therefore, our paper discusses these dimensions as challenges that facing information centers in according to their data governance and the impa

A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone