This research aims to solve the nonlinear model formulated in a system of differential equations with an initial value problem (IVP) represented in COVID-19 mathematical epidemiology model as an application using new approach: Approximate Shrunken are proposed to solve such model under investigation, which combines classic numerical method and numerical simulation techniques in an effective statistical form which is shrunken estimation formula. Two numerical simulation methods are used firstly to solve this model: Mean Monte Carlo Runge-Kutta and Mean Latin Hypercube Runge-Kutta Methods. Then two approximate simulation methods are proposed to solve the current study. The results of the proposed approximate shrunken methods and the numerical

Manual probing and periodontal charting are the gold standard for periodontal diagnosis that have been used in practice over a century. These methods are affordable and reliable but they are associated with some drawbacks that cannot be avoided. Among these issues is their reliance on operator’s skills, time-consuming and tedious procedure, lack sensitivity especially in cases of early bone loss, and causing discomfort to the patient. Availability of a wide range of biomarkers in the oral biofluids, dental biofilm, and tissues that potentially reflect the periodontal health and disease accurately encouraged their use as predictive/diagnostic/monitoring tools. Analysing biomarkers during care-giving to the patient using chairside kits i

Background: Ischemic heart diseases (I.H.D) become the most common cause of sudden death, and is also the most common reason for death of man and women over 20 years of age in the world. Many Factors Play a role in pathogenesis of I.H.D. among those could be Immune – inflammatory markers which may lead to development of this disease.The present study was conducted to obtain more clarification about the impact of some immuno – inflammatory markers (IL- 8 , IL- 4 and IFN- Ճ) on the Clinical expression of heart disease among Iraqi patients .
Patients and methods: Hundred Iraqi patient with I.H.D. (80 male and 20 female) ages ranged between 20 to 80 year were involved in this study, include 4 subgroups:

    In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne

The pandemic of coronavirus disease 2019 (COVID-19), first reported in China, in December 2019 and since then the digestive tract involvement of  COVID-19 has been progressively described. In this review, I summed recent studies, which have addressed the pathophysiology of COVID-19-induced gastrointestinal symptoms, their prevalence, and bowel pathological and radiological findings of infected patients. The effects of gut microbiota on SARS-CoV-2 and the challenges of nutritional therapy of the infected patients are depicted.  Moreover, I provide a concise summary of the recommendations on the management of inflammatory bowel disease, colorectal cancer, and performing endoscopy in the COVID era. Finally, the COVID pancreatic re

The present study aims to investigate the long-term histopathological, and physiological effects of different concentrations of a commercially available energy drink (Tiger) on liver and kidney of young mice. Sixteen Balb/c male mice,6 -week old, were divided into 4 groups (n=4). Two groups consumed the energy drink at a concentration of 28µl energy drink/ml water. One group were killed after 10 days (T1), another group were killed after 20 days (T2). Other group of mice consumed the energy drink at a final concentration of 14µl/ml for 20 days (T3). The last group was provided only with water and served as control. Mice of all groups drank around 3 ml per day. The histopathological study on liver of treated groups showed many changes s

Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

Background: Coronary artery disease remains the main cause of death despite several preventive programs. Epicardial adipose tissue is a visceral fat depot of the heart located along the large coronary arteries and on the surface of ventricles and apex. Intima media thickness is commonly recognized as the initial stage in the development of atherosclerosis. The development of ultrasound machines, advances in echocardiographic devices and high resolution transducers facilitate comprehensive analysis of epicardial fat thickness (EFT) and carotid –intima media thickness (C-IMT).
Aim: To investigate the relationship of echocardiographic epicardial fat thickness (EFT) and carotid –intima media thickness (C-IMT) with the severity of coro

This study was conducted to evaluate the efficiency of some chemicals and biological agents to induce systemic resistance (ISR) against to wheat common bunt disease caused by the two species of fungus Tilletia tritici (Bjerk.) Wint (T. caries (Dac.) Tul.) and T. laevis Kuhn (T. foetida (Wall.) Liro. Trails in the efforts to find an alternative, safe and environmentally friendly means to control the disease. Results of this study which carried out during two consecutive seasons for the years 2012 - 2013 and 2013 - 2014 at two different environmental locations. Seed treatment by (SA 100 and 200 mg/L, 500 ?–aminobutyric acid (BABA) and 1000 mg/L, Effective Microorganisms (EM1) 40 and 150 ml/kg seeds) have led to high significant redu

    The main goal of this research is to determine the impact of some variables that we believe that they are important to cause renal failuredisease by using logistic regression approach.The study includes eight explanatory variables and the response variable represented by (Infected,uninfected).The statistical program SPSS is used to proform the required calculations