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

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

This field experiment was conducted at Research Station B, Department of Horticulture and Landscape Engineering, College of Agricultural Engineering Sciences, University of Baghdad, Jadiriyah during the fall season of 2019-2020 to evaluate the effect of cultivation dates and soil fertilization source on the growth, yield and quality of broccoli. A split plot design within the RCBD design with three replicates was applied as the Max F1 hybrid broccoli seedlings were transferred to the field at two dates 25, Sep. 2019 and 15, Oct. 2019, which were symbolized as A and B, respectively, and occupied at the main plot. After two weeks of cultivation, the soil fertilizers were applied three times during the season in 20 days between each applicati

The influence of process speed (PS) and tillage depth (TD) , on growth of corn (Zea mays L) yield, for Maha cultivar, were tested at two ranges of PS of 2.483 and 4.011 km.hr-1, and three ranges of TD of 15,20 and 25cm. The experiments were conducted in a factorial experiment under complete randomized design with three replications. The results showed that the PS of 2.483 km.hr-1 was significantly better than the PS of 4.011km.hr-1 in all studied conditions. The , slippage ratio (SR) and the machine efficiency (ME), the physical soil characteristics represented by the soil density and porosity (SBD and TSP), and the plant characteristics represented the roots dry weight, PVI and the crop productivity (CP), except adjective of the fu

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

 Abstract

In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons

Increasing material prices coupled with the emission of hazardous gases through the production and construction of Hot Mix Asphalt (HMA) has driven a strong movement toward the adoption of sustainable construction technology. Warm Mix Asphalt (WMA) is considered relatively a new technology, which enables the production and compaction of asphalt concrete mixtures at temperatures 15-40 °C lower than that of traditional hot mix asphalt. The Resilient modulus (Mr) which can be defined as the ratio of axial pulsating stress to the corresponding recoverable strain, is used to evaluate the relative quality of materials as well as to generate input for pavement design or pavement evaluation and analysis. Based on the aforementioned preface, it is

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

Solid waste generation and composition in Baghdad is typically affected by population growth, urbanization, improved economic conditions, changes in lifestyles and social and cultural habits.

A burning chamber was installed to burn cellulosic waste only. It was found that combustion reduced the original volume and weight of cellulosic waste by 97.4% and 85% respectively.

A batch composting study was performed to evaluate the feasibility of co-composting organic food waste with the cellulosic bottom ash in three different weight ratios (w/w) [95/5, 75/25, 50/50].

The composters were kept in controlled aerobic conditions for 7 days. Temperature, moisture, and pH were measured hourly as process succe