This study illustrates the impact of non-thermal plasma (Cold Atmospheric Plasma CAP) on the lipids blood, the study in vivo. The lipids are (cholesterol, HDL-Cholesterol, LDL-Cholesterol and triglyceride) are tested. (FE-DBD) scheme of probe diameter 4cm is used for this purpose, and the output voltage ranged from (0-20) kV with variable frequency (0-30) kHz. The effect of non-thermal atmospheric plasma on lipids were studied with different exposure durations (20,30) sec. As a result, the longer plasma exposure duration decreases more lipids in blood.

In this research we have been studied the 3rd order spherical aberration for an optical system consisted of obscured circular aperture with non central circular obscuration through the calculation of point spread function (P.S.F) in presence of the obscuration in the center and comparing the obtained results with that results of moving obscuration far away from the center, where the results showed significant improvement for(P.S.F) value. The study was done of different obscurities ratios in addition to the different 3rd order spherical aberration values (W40=0.25 ,0.5 ,0.75 ,1 ).

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

A study of characteristics of the lubricant oils and the physical properties is essential to know the quality of lubricant oils. The parameters that lead to classify oils have been studied in this research. Three types of multi-grades lubricant oils were applied under changing temperatures from 25 ^oC to 78^oC to estimate the physical properties and mixture compositions. Kinematic viscosity, viscosity gravity constant and paraffin (P), naphthenes (N) and aromatics (A) (PNA) analysis are used to predict the composition of lubricants oil. Kinematic viscosity gives good behaviors and the oxidation stability for each lubricant oils. PNA analysis predicted fractions of paraffin (X_P), naphthenes (X_N),

This study investigates the characterization and growth dynamics of a Magnetically Stabilized Gliding Arc Discharge (MSGAD) system, generating non-thermal plasma with argon gas under atmospheric pressure and flow rates of 1-5 L/min. The electrical properties and growth patterns concerning gas flow rates and applied voltages were examined utilizing a magnetic field for stability. Using a digital oscilloscope, a correlation between voltage reduction and increased current was uncovered. An algorithm analyzes digital images to compute arc length, area, and volume. Results reveal how gas flow rate and applied voltage directly impact arc growth. Furthermore, the magnetic field's role in guiding and stabilizing the plasma discharge was explored. T

  The current research tries to identify the employment of the digital technology in the formation of the theatrical show space. The researcher started with the significant importance of the digital technology and its workings in the formation of the contemporary theatrical show being a modern, artistic, aesthetic, intellectual and technological means to convey the topic in an integrated manner, as well as its close connection with the creative directive vision and the creative designing vision. It provides a variety of models of numerous implications in terms of transmission and advancement of the relationships represented by clarifying the scenography and dramatic conflict forms according to the numerous motivations of the directo

A vascular necrosis (AVN) is defined as cellular death of bone components due to interruption of the blood supply; the bone structures then collapse, resulting in bone destruction, pain, and loss of joint function. AVN is associated with numerous conditions and usually involves the epiphysis of long bones, such as the femoral head. In clinical practice, AVN is most commonly encountered in the hip. Early diagnosis and appropriate intervention can delay the need for joint replacement. However, most patients present late in the disease course. Without treatment, the process is almost always progressive, leading to joint destruction within 5 years. Treatment of a vascular necrosis depends mainly on early diagnosis which mainly based on clinical

PC-based controller is an approach to control systems with Real-Time parameters by controlling selected manipulating variable to accomplish the objectives. Shell and tube heat exchanger have been identified as process models that are inherently nonlinear and hard to control due to unavailability of the exact models’ descriptions. PC and analogue input output card will be used as the controller that controls the heat exchanger hot stream to the desired temperature.
The control methodology by using four speed pump as manipulating variable to control the temperature of the hot stream to cool to the desired temperature.
In this work, the dynamics of cross flow shell and tube heat exchanger is modeled from step changes in cold water f

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