Agricultural chemicals on a large scale of use throughout the world, and there are many studies about these chemicals and its disadvantages, but most of them were limited to its impact on mammals such as rodents in determine. This study was designed to determine the impact of these chemicals on DNA damage for E. coli bacteria from Iraq. The DNA is similar in terms of structure and function in all living organisms with a different in number and sequence of the nitrogenous bases among living organisms.            This study showed that snails and slugs killer material Metaldehyde are strongly bind with the DNA extracted from bacteria, and herbicides Glyph

 This study attempts to address the importance of communicative digitization in the field of various arts for the sake of continuity of shopping and aesthetic, artistic and intellectual appreciation of artistic achievements by the recipient on various places of their residence in light of the COVID 19 crisis, and to highlight the importance of the plastic arts of the Iraqi painter exclusively and how it expresses in a contemporary way the environment or life reality in Iraq in light of this crisis. With all its implications affecting the life reality from various aspects and methods of its negative and positive employment. As for the research procedures, the researcher reviewed the research methodology represented by the descriptive ana

    Diabetic nephropathy (DN) is the most common microvascular complication that may lead to chronic renal failure in diabetic patients. Till now microalbuminuria, with its restrictions, is the early marker of DN, appeared after the disease exacerbation. Thus, new biomarkers are required to predict the early onset of DN before the appearance of microalbuminuria. The aim of this study is to investigate the possible use of uVDBP in the early prediction of DN. Fifty diabetic patients with DN and 40 diabetic patients without DN for both types of diabetes were enrolled in this study. All patients were tested for uACR, uVDBP (measured by ELISA), and blood HbA1c. The results demonstrated a highly significant elevation of uAC

  The phenomenon of child labor, any activity performed by a child and represents a contribution to the production, this phenomenon had been rife in Iraqi society, after that the proportion of child labor for the age group (6-14 years) amounting to 3% in 2006, became for  the same age group of 8% in 2008*.                                                      

It is recognized that each phenomenon reasons, the phenomenon which our atten

              Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breat

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

The COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is fre

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol