In this work, the effect of partial amounts of gases in gas mixture of a CW CO2 laser on the output power was investigated. Also their effect on the condition determining the glow-discharge self-sustaining required for pumping the active medium was studied. Two fit relations were derived to predict the output laser power and the electric field to unit pressure ratio as functions to the partial amounts of gases. Results presented in this work could be used fruitfully to determine some of the optimum operational conditions of glow-discharge low-power CW CO2 lasers.

This research study the effect of Titanium dioxide on the tensile properties of
Polystyrene (PS) and Polycarbonate (PC) polymers. The stress – strain curve for pure PS
and pure PC, shows that Young modulus for PS is higher than Young modulus for PC,
because PS have higher ultimate strength than PC.
The addition of TiO2 to PS and PC will reduce the Young modulus and ultimate stress,
because the TiO2 particles will reduces or freeze the orientation of these molecular chain
and reduced the toughness of PC, while when the TiO2 were added to PS, the value of
toughness will be stabilized because TiO2 particles make these chains interlocked and the
mobility of the chains will be restrict.

Nuclear shell model is adopted to calculate the electric quadrupole moments for some Calcium isotopes 20Ca (N = 21, 23, 25, and 27) in the fp shell. The wave function is generated using a two body effective interaction fpd6 and fp space model. The one body density matrix elements (OBDM) are calculated for these isotopes using the NuShellX@MSU code. The effect of the core-polarizations was taken through the theory microscopic by taking the set of the effective charges. The results for the quadrupole moments by using Bohr-Mottelson (B-M) effective charges are the best. The behavior of the form factors of some Calcium isotopes was studied by using Bohr-Mottelson (B-M) effective charges.

MRSA is one of the major pathogens in hospitals and the community, which have the ability to produce biofilm as a virulence factor, the impact of chalcone on biofilm formation, the synergism effect of chalcone and antibiotic in both in vitro and in vivo experiments, the gene expression of virulence genes (srtA, fnbA, fnbB) before and after treatment of it on MRSA biofilm cells in vitro, all these were the prime aims of this study. Chalcone at MBIC (20 μg/ml), significantly reduced the biofilm formation to 21.45% and at sub MBIC (15 μg/ml) to 36.58 %. While, Chalcone at MIC(5 μg/ml) reduced MRSA planktonic cells to 49.61%. Susceptibility of MRSA isolates against eight antibiotics showed that all isolates were sensitive to vancomycin and n

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

Abstract

The study seeks to use one of the techniques (Data mining) a (Logic regression) on the inherited risk through the use of style financial ratios technical analysis and then apply for financial fraud indicators,Since higher scandals exposed companies and the failure of the audit process has shocked the community and affected the integrity of the auditor and the reason is financial fraud practiced by the companies and not to the discovery of the fraud by the auditor, and this fraud involves intentional act aimed to achieve personal and harm the interests of to others, and doing (administration, staff) we can say that all frauds carried out through the presence of the motives and factors that help th

Objective: to assess the risk factors of coronary artery disease patients.
Methodology: A non-probability (purposive) sample of (100) patients. The study population consisted of
a sample of adults from both genders whose ages were 30 years and more, and was newly diagnosed as
having CAD by coronary angiography in the cardiac catheterization unit of An Nasiriyah heart center.
Results: The result of the study showed that the most common modifiable risk factors were low HDL-C
levels (58%), smoking (53%), hypertension (46%), diabetes mellitus (34%), obesity (30%), high
triglycerides (19%), hypercholesterolemia (17%), and high LDLC (14%). All these factors were positively
and significantly associated with the development

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct