This study investigated the effect of applying an external magnetic field on the characteristics of laser-induced plasma, such as its parameters plasma, magnetization properties, emission line intensities, and plasma coefficients, for plasma induced from zinc oxide: aluminum composite (ZO:AL) at an atomic ratio of 0.3 %. Plasma properties include magnetization and emission line intensities. The excitation was done by a pulsed laser of Nd:YAG with 400 mJ energy at atmospheric pressure. Both the electron temperature and number density were determined with the help of the Stark effect principle and the Boltzmann-Plot method. There was a rise in the amount of (n_e) and (T_e) that was produced

Low incoming discharge upstream of Samarra-Al Tharthar System leads to sediment accumulation and forming islands, especially an island upstream of Al Tharthar Regulator. This island and the sedimentation threaten the stability of the structure and reduce the efficiency of the system. This study aims to hydraulically identify the sedimentation problem mentioned above, to find solutions of how to control the sediment problems, and to develop the capacity of
the system for 500 years return period flood of 15060 m3/s. Surface Water Modeling System (SMS10.1) with two dimensional depth average models (RMA-2) software were used to simulate and analyze the system. The results of analysis showed that the maximum permissible discharge through t

Abstract Since unmethylated CpG motifs are more common in DNA from bacteria than vertebrates, and the unmethylated CpG motif has recently been reported to have stimulatory effects on lymphocytes, we speculated that bacterial DNA may induce inflammation in the urinary tract. To determine the role of bacterial DNA in lower UTI, we intraurethrally injected prokaryotic DNA (extracted from E. coli) in white mice and performed histopathological study for the kidneys and urinary bladders, 24 h after the exposure. The results showed infiltration of inflammatory cells, shrinkage of glomerulus and increase the capsular space, as well as edema formation in kidney tissues. Moreover, urinary bladder sections showed infiltration of inflammatory cells.

PV connected systems are worldwide installed because it allows consumer to reduce energy consumption from the electricity grid. This paper presents the results obtained from monitoring a 1.1 kWp. The system was monitored for nine months and all the electricity generated was fed to the fifth floor for physics and renewable energy building   220 V, 50 Hz. Monthly, and daily performance parameters of the PV system are evaluated which include: average generated of system Ah per day, average system efficiency, solar irradiation around these months. The average generated kWh per day was 8 kWh/day, the average solar irradiation per day was 5.6 kWh/m²/day, the average inverter efficiency was 95%, the average modules efficien

 Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.

The research aims to extrapolate the repercussions of the use of expert systems in the work of the external auditor on the quality of audit, as the research problem was that despite the use of these techniques in audit work, there is a problem related to the efficiency and effectiveness of these technological systems used in audit work, the feasibility of their use and the extent of their impact: The quality of the audit process.

The researchers adopted the questionnaire as a tool for collecting study data from a community composed of auditors in auditing offices and companies in Iraq, and the auditors of the Iraqi Federal Financial Supervision Bureau. The number of recovered and valid qu

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings