Diabetic kidney disease is an illness of the glomerulus that interferes with the glomerular filtration barrier (GFB), which is worked to enable kidney to selective purification of water and solutes in addition to limiting the movement of large macromolecules such as albumin. In the glomerular endothelium, mesangial cells, foot cells, and the brush border of the proximal tubules, ACE-2 is expressed and that the kidneys represent the highest-expressing region of this enzyme. Thus, the current study aimed to evaluate ACE-2 level in this case compared to healthy condition. The study Conducted with 120 male and female ranging in age (30-65) years old. Ninety patients with type 2 diabetes subdivided into three groups on the basis of A

SAPO-11 is synthesized from silicoaluminophosphate in the presence of di-n-propylamine as a template. The results show that the sample obtained has good crystallinity, 396m2/g BET surface area, and 0.35 cm3/g pore volume. The hydroisomerization activity of (0.25)Pt (1)Zr (0.5)W/SAPO-11 catalyst was determined using n-decane and base oil. All hydroisomerization experiments of n-decane were achieved at a fixed bed plug flow reactor at a temperature range of 200-275°C and  LHSV 0.5-2h-1.  The results show that the n-decane conversion increases with increasing temperature and decreasing LHSV, the maximum conversion of 66.7 % was achieved at temperature 275°C and LHSV of 0.5 h-1. Meanwhile, the same catalyst was used to improve base oil spec

   SAPO-11 is synthesized from silicoaluminophosphate in the presence of di-n-propylamine as a template. The results show that the sample obtained has good crystallinity, 396m²/g BET surface area, and 0.35 cm³/g pore volume. The hydroisomerization activity of (0.25)Pt (1)Zr (0.5)W/SAPO-11 catalyst was determined using n-decane and base oil. All hydroisomerization experiments of n-decane were achieved at a fixed bed plug flow reactor at a temperature range of 200-275°C and  LHSV 0.5-2h^-1.  The results show that the n-decane conversion increases with increasing temperature and decreasing LHSV, the maximum conversion of 66.7 % was achieved at temperature 275°C and LHSV of 0.5 h^-1

New nanotechnology-based approaches are increasingly being investigated for enhanced oil recovery (EOR), with a particular focus on heavy oil reservoirs. Typically, the addition of a polymer to an injection fluid advances the sweep efficiency and mobility ratio of the fluid and leads to a higher crude oil recovery rate. However, harsh reservoir conditions, including high formation salinity and temperature, can limit the performance of such polymer fluids. Recently, nanofluids, that is, dispersions of nanoparticles (NPs) in a base fluid, have been recommended as EOR fluids; however, such nanofluids are unstable, even under ambient conditions. In this work, a combination of ZrO2 NPs and the polyacrylamide (PAM) polymer (ZrO2 NPs–PAM) was us

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

Construction projects have become a changing dramatically in recent decades and that the goal of the beneficiaries of the implementation of structural project is to complete the work with less time and within the cost of the specific and the best possible quality may sometimes happen that highlights the importance of time on the rest of the items at the implementation of projects for various reasons, including the need to use the project as soon as possible possible change rapidly to customer's requests, but the high cost of the project represents the biggest obstacle for entrepreneurs with its effects on the quality and the time workers, and is a measure of those elements in monetary terms is the key to integration between them, so the

This investigation aimed to explain the mechanism of MFCA by applying this method on air-cooled engine factory which was suffering from high production cost. The results of this study revealed that MFCA is a useful tool to identify losses and inefficiencies of the production process. It is found that the factory is suffering from high losses due to material energy and system losses. In conclusion, it is calculated that system losses are the highest among all the losses due to inefficient use of available production capacity.

Controlling cost in construction projects is an essential issue. This study investigates the most critical problems that cause weakness in cost control in Iraqi construction projects. The quantitative technique was used by conducting a survey directed to professionals who work on construction projects. One hundred and sixty-four questionnaire forms were distributed to private sector companies, government companies, and government institutions, and the responses were subjected to the required statistical analysis. The results indicate that the most influential factors are the weakness in keeping up with the use of modern concepts, methods, and technologies, the delay in receiving the amounts due for work done from the owner, fluctuat