This research was conducted to measure the safety of heat stable enterotoxin a (STa) produced by enterotoxigenic Escherichia coli, through studying its toxic effect on mice since it showed a promising effect in reducing the proliferation of colorectal cancer cells. The cytogenetic effect was determined after giving five different doses (100, 200, 400, 800 and 1600)μg/Kg in comparison with negative (phosphate buffer saline / PBS) and positive (mitomycin C/ MMC, at doses of 2 and 5μg/Kg) controls on mouse bone marrow cells by employing the following parameters: mitotic index, chromosomal aberrations and micronucleus, also, the serum level of liver functional enzymes (GOT, GPT, ALP) was recorded. In addition, lethal dose 50 (LD 50) with cert

News are considered the most press arts that supply the target audiences with daily information and events happened inside and outside society since it is formed by depending on its resources which have a deep relation with formal corporations to gain their satisfaction in order to support their authority and spreading their domination by using mass media in editing their viewpoints and achieving wide acceptance among public opinion. In the field of technological development and changing in the fields of politics, society, culture, economics etc. inside Iraqi society and democratic transition help to convert news agenda from independent variation to a fellow variation while in the past the variation of mass media was the independent one

In this study, the two researchers try to identify the degree of psychological flow among third-stage students in the College of Physical Education and Sports Sciences / University of Baghdad, by constructing a psychometric flow meter for third-stage students in the College of Physical Education and Sports Sciences / University of Baghdad, and the research sample reached 123 female students They represent 100% of the research community, and after conducting the scientific foundations for building the scale, the two researchers reached the final version of the psychometric flow scale with 21 items with four axes.

In this paper, a design of the broadband thin metamaterial absorber (MMA) is presented. Compared with the previously reported metamaterial absorbers, the proposed structure provides a wide bandwidth with a compatible overall size. The designed absorber consists of a combination of octagon disk and split octagon resonator to provide a wide bandwidth over the Ku and K bands' frequency range. Cheap FR-4 material is chosen to be a substate of the proposed absorber with 1.6 thicknesses and 6.5×6.5 overall unit cell size. CST Studio Suite was used for the simulation of the proposed absorber. The proposed absorber provides a wide absorption bandwidth of 14.4 GHz over a frequency range of 12.8-27.5 GHz with more than %90 absorp

In this work, a deep computational study has been conducted to assign several qualities for the graph ⁠. Furthermore, determine the amount of the dihedral subgroups in the Held simple group He through utilizing the attributes of gamma.

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes