Background: Hypothyroidism is a decrease in the production of the thyroid hormones and leads to gland dysfunction. Ashwagandha extract was used as an ayurvedic treatment and supposed to be as antihypothyroidism agent.

Objectives: to investigate the impact of ashwagandha (Ash) extract on propylthiouracil (PTU)-induced hypothyroidism in rats.

Subjects and Methods: The rats were divided into three groups, control group, PTU (hypothyroid) group (6mg/kg/day by oral route), PTU (6mg/kg/day by oral route) +Ash (50mg/kg/day by oral route) treated group. All treatment continued for

The experiment was carried out in the green house of botanical garden belong to Department of Biology/College of Education for Pure Science Ibn AL-Haitham, University of Baghdad for growing season 2017-2018 to evaluate effect of lead stress with concentrations (0, 50, 100, 150) mg.L -1 and Selenium concentrations (0, 15, 30) mg.L-1 on growth of dill plant using pots. The experiment was designed according to completely randomized design (CRD) with three replications. Result indicated that dill plants subjected to lead stress with height concentrations caused decrease in plant parameters (plant height, no. of branches. plant-1, root length, shoot dry weight, the content of nitrogen, phosphorus and potassium, protein concentration, no. of umbe

Abstract:

               The aim of the research is to evaluate the practice of banking departments for strategic foresight represented by its dimensions (environmental scanning, future vision, scenarios, reconfiguration) and its relationship to the organizational brilliance represented by dimensions (brilliance of leadership, brilliance of service and innovation, brilliance of knowledge, brilliance of employees), as the research was applied in A number of private Iraqi commercial banks represented by (Baghdad, Iraqi Investment, Iraqi Middle East Investment, Commercial Gulf, Ashur International Investment, Al Mansour Investment, Via Iraq Invest

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet