Artificial intelligence techniques are reaching us in several forms, some of which are useful but can be exploited in a way that harms us. One of these forms is called deepfakes. Deepfakes is used to completely modify video (or image) content to display something that was not in it originally. The danger of deepfake technology impact on society through the loss of confidence in everything is published. Therefore, in this paper, we focus on deepfakedetection technology from the view of two concepts which are deep learning and forensic tools. The purpose of this survey is to give the reader a deeper overview of i) the environment of deepfake creation and detection, ii) how deep learning and forensic tools contributed to the detection

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

 The integration of AI technologies is revolutionizing various aspects of the apparel and textile industry, from design and manufacturing to customer experience and sustainability. Through the use of artificial intelligence algorithms, workers in the apparel and textile industry can take advantage of a wealth of opportunities for innovation, efficiency and creativity.
The research aims to display the enormous potential of artificial intelligence in the clothing and textile industry through published articles related to the title of the research using the Google Scholar search engine. The research contributes to the development of the cultural thought of researchers, designers, merchants and the consumer with the importance of integ

Brucellosis in swine is caused by Brucella suis, a bacterial infection of nearly worldwide distribution. Brucella suis is also transmissible to humans, dogs and cattle and is considered a reemerging disease of public health concern. To date, there is no effective vaccine for swine. This prompted us to investigate the potential use of the commercially available vaccine for cattle or the live attenuated vaccine candidate S19ΔvjbR. As the first step, we sought to study the safety of the vaccine candidates when administered in pregnant sows, since one of the major drawbacks associated with vaccination using Live Attenuated Vaccines (LAV) is the induction of abortions when administered in pregnant animals. Fifteen pregnant gilts at mid-gestatio

         Fibromyalgia (FM) is a common, debilitating, and chronic pain syndrome. The women are more likely to have more tender points on examination than are their male counterparts. Iraqi study showed that FM occur in 1.5% among adolescents of Iraqi population. In compare to normal healthy women, present study was revealed that Iraqi women with FM have significant elevation of calcium (p = 0.003) with significant reduction of magnesium (p = 0.001), whereas the inorganic phosphorous was not differs (p = 0.31). In conclusion, magnesium and calcium would play a crucial role in etiopathogenesis of fibromyalgia.

Key words: calcium, magnesium, phosphorous, Fibromyalgia.

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