In the present study, histological study was carried out on adult chickens to shed light on the effects of GH and IGF-1 on the heart, liver, and gizzard. The microscopic examination had shown that GH and IGF1 promote protein synthesis in the heart tissue. The herein work referred to the presence of a considerable amount of adipose tissue among the bundles of cardiac muscles, which is related to the metabolic process. The results also revealed that GH and IGF-1 promote both protein synthesis and Mitosis in the tissues of the liver and gizzard Moreover, the above hormones stimulate apoptosis, regeneration and secretory activity in gizzard secretory glands

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

All major organs may be impacted by the connective disease systemic lupus erythematosus, a separate risk factor for coronary artery disease (CAD). Adhesion molecules like intercellular adhesion molecules (ICAM) and vascular cell adhesion molecules (VCAM) can detect endothelial damage and dysfunction, which appear to play a crucial role. This study investigated whether people with SLE had elevated subclinical and clinical atherosclerosis risk factors. Traditional CAD risk factors such as smoking, hypertension, and hyperlipidemia cannot entirely explain this elevation. It is thought that immunological dysfunction also increases CAD risk in SLE patients. The study aimed to assess early endothelial changes in SLE Iraqi female patients w

Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. The major idea is to generate course timetables automatically while discovering the area of constraints to get an optimal and flexible schedule with no redundancy through the change of a viable course timetable. The main contribution in this work is indicated by increasing the flexibility of generating opti

Signal denoising is directly related to sample estimation of received signals, either by estimating the equation parameters for the target reflections or the surrounding noise and clutter accompanying the data of interest. Radar signals recorded using analogue or digital devices are not immune to noise. Random or white noise with no coherency is mainly produced in the form of random electrons, and caused by heat, environment, and stray circuitry loses. These factors influence the output signal voltage, thus creating detectable noise. Differential Evolution (DE) is an effectual, competent, and robust optimisation method used to solve different problems in the engineering and scientific domains, such as in signal processing. This paper looks

An automatic text summarization system mimics how humans summarize by picking the most ‎significant sentences in a source text. However, the complexities of the Arabic language have become ‎challenging to obtain information quickly and effectively. The main disadvantage of the ‎traditional approaches is that they are strictly constrained (especially for the Arabic language) by the ‎accuracy of sentence feature ‎functions, weighting schemes, ‎and similarity calculations. On the other hand, the meta-heuristic search approaches have a feature tha

This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that