Seven isolates were identified as Pseduomonas aeruginosa from clinical samples. Antibiotic sensitivity test were done to determine their sensitivity to number of antibiotics, the results illustrated all that isolates were resistant to most used antibiotics. The ability of Pseduomonas isolates to produce haemolysin, protease and pyocyanin were detected in this study, all isolates had the ability to produce pyocyanin pigment, hemolysis and protease. The antimicrobial activity of the ethanolic extracts of Thuja orientalis and green tea against P.aeruginosa were investigated. The results showed that both these plant extracts have inhibitory effect against Pseduomonas isolates and it was shown that ethanolic extract of green tea was more efficie

Renewable energy resources have become a promissory alternative to overcome the problems related to atmospheric pollution and limited sources of fossil fuel energy. The technologies in the field of renewable energy are used also to improve the ventilation and cooling in buildings by using the solar chimney and heat exchanger. This study addresses the design, construction and testing of a cooling system by using the above two techniques. The aim was to study the effects of weather conditions on the efficiency of this system which was installed in Baghdad for April and May 2020. The common weather in these months is hot in Baghdad. The test room of the design which has a size of 1 m3 was situated to face the geographical south. The te

The sale of facial features is a new modern contractual development that resulted from the fast transformations in technology, leading to legal, and ethical obligations. As the need rises for human faces to be used in robots, especially in relation to industries that necessitate direct human interaction, like hospitality and retail, the potential of Artificial Intelligence (AI) generated hyper realistic facial images poses legal and cybersecurity challenges. This paper examines the legal terrain that has developed in the sale of real and AI generated human facial features, and specifically the risks of identity fraud, data misuse and privacy violations. Deep learning (DL) algorithms are analyzed for their ability to detect AI genera

Aim: This study aimed to investigate the impact of rabbit serum on skin wound healing with the help of histological examination. Materials and Methods: A total of ten indigenous rabbits were used in this study. The animals were divided into two groups: control and serum- treated. The histological assessment was done with a paraffin embedding technique and the histological sections were stained with H&E stain. Results: Severe infiltration of polymorphonuclear leukocytes with severe fibrin deposits were seen in serum treated group at 2 days post-injury; at 7 days post-injury the changes revealed moderate fibroplasia, fibrin deposit and severe infiltration of both mononuclear and polymorphonuclear leukocytes; at 14 days post-inju

Optimizing system performance in dynamic and heterogeneous environments and the efficient management of computational tasks are crucial. This paper therefore looks at task scheduling and resource allocation algorithms in some depth. The work evaluates five algorithms: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Firefly Algorithm (FA) and Simulated Annealing (SA) across various workloads achieved by varying the task-to-node ratio. The paper identifies Finish Time and Deadline as two key performance metrics for gauging the efficacy of an algorithm, and a comprehensive investigation of the behaviors of these algorithms across different workloads was carried out. Results from the experiment

The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

The work reported in this study focusing on the abrasive wear behavior for three types of pipes used in oil industries (Carbone steel, Alloy steel and Stainless steel) using a wear apparatus for dry and wet tests, manufactured according to ASTM G65. Silica sand with
hardness (1000-1100) HV was used as abrasive material. The abrasive wear of these pipes has been measured experimentally by measuring the wear rate for each case under different sliding speeds, applied loads, and sand conditions (dry or wet). All tests have been conducted using sand of particle size (200-425) µm, ambient temperature of 34.5 °C and humidity 22% (Lab conditions).
The results show that the material loss due to abrasive wear increased monotonically with