Leucine aminopepotidase (LAP)[EC:3.4.11.1] activity has been assayed in (50) serum samples of patients with diabeties naphrophathy D.N (non-insulin dependent diabetic (NIDD) , and (50)serum sample of healthy individuals without any clinically detectable diseases have been as control group. The aim of this study is to measure leucine aminopeptidase activity and partially purifying the enzyme from sera of patients with diabetes nephropathy The results of this study revealed that Leucine aminopeptidase (LAP) activity of nephropathy patient’s serum shows a high signifiacant increase (p < 0.001) compared to that of the healthy subjects.LAP was purified from the serum of patients with diabetes nephropathy by dialysis and gel filtration (Se

Cytokines are A type of protein that is made by certain immune and non-immune cells and has an effect on the immune system. Some cytokines stimulate the immune system and others slow it down. Interleukins (ILs) can be divided into several families with more than 40 subfamily members. They can interact with a variety of cells that alter the immune system and act on a wide range of cancers. In the past several years, ILs have attracted substantial attention because of their distinct roles in CRC that provide a new and promising strategy for CRC. In general, ILs facilitate CRC by promoting tumorigenesis, tumour growth, angiogenesis, and cancer cell invasion and metastasis and inhibit CRC via complex pathways. The Bioassay Technology Human Inte

Rainwater harvesting could be a possible solution to decrease the consequences of water scarcity and energy deficiency in Iraq and the Kurdistan Region of Iraq (KRI). This study aims to calculate the water and energy (electricity) saved by rainwater harvesting for rooftops and green areas in Sulaimani city, KR, Iraq. Various data were acquired from different formal entities in Sulaimani city. Moreover, Google Earth and ArcMap 10.4 software were used for digitizing and calculating the total rooftop and green areas. The results showed that for the used runoff coefficients (0.8 and 0.95), the harvested rainwater volumes were 2901563 and 12197131 m³ during the study period (2005 – 2006) and (2019-2020). Moreover, by compa

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

The load shedding  scheme has been extensively implemented as a fast solution for unbalance conditions. Therefore, it's crucial to investigate supply-demand balancing in order to protect the network from collapsing and to sustain stability as possible, however its implementation is mostly undesirable. One of the solutions to minimize the amount of load shedding is the integration renewable energy  resources, such as wind power, in the electric power generation could contribute significantly to minimizing power cuts as it is ability to positively improving the stability of the electric grid. In this paper propose a method for shedding the load base on the priority demands with incorporating the wind po

The accurate identification of internal and external pressures in thick-walled hyperelastic vessels is a challenging inverse problem with significant implications for structural health monitoring, biomedical devices, and soft robotics. Conventional analytical and numerical approaches address the forward problem effectively but offer limited means for recovering unknown load conditions from observable deformations. In this study, we introduce a Graph-FEM/ML framework that couples high-fidelity finite element simulations with machine learning models to infer normalized internal and external pressures from measurable boundary deformations. A dataset of 1386 valid samples was generated through Latin Hypercube Sampling of geometric and l

Anumerical solutions is presented to investigate the effect of inclination angle (θ) , perforation ratio (m) and wall temperature of the plate (T_w) on the heat transfer in natural convection from isothermal square flat plate up surface heated (with and without concentrated hole). The flat plate with dimensions of (128 mm) length × (64 mm) width has been used five with square models of the flat plate that gave a rectangular perforation of (m=0.03, 0.06, 0.13, 0.25, 0.5). The values of angle of inclination were (0^o, 15^o 30^o 45^o 60^o) from horizontal position and the values of wall temperature (50^oC, 60 ^oC, 70 ^oC, 90 ^oC, 100^o<

The performance and durability of the asphalt pavement structure mainly depend on the strength of the bonding between the layers. Such a bond is achieved through the use of an adhesive material (tack coat) to bond the asphalt layers. The main objective of this study is to evaluate the effect of moisture in conjunction with repeated traffic loads on the strength of the bonding between asphalt layers using two types of tack coats with different application rates. Using the nominal maximum size of aggregate (NMAS), the layers were graded (25/19) and (19/9.5) mm. The slabs of multilayer asphalt concrete were prepared using a roller compactor using two types of tack coats to bond between layers, namely rapid curing cut back a