APDBN Rashid, 7th International Conference on Multidisciplinary Sciences (7th ICOMUS), 2021

Objectives: This study aims to broaden our knowledge of the role of eDNA in bacterial biofilms and antibiotic-resistance gene transfer among isolates. Methods: Staphylococcus aureus, E. coli, and Pseudomonas aeruginosa were isolated from different non-repeated 170 specimens. The bacterial isolates were identified using morphological and molecular methods. Different concentrations of genomic DNA were tested for their potential role in biofilms formed by study isolates employing microtiter plate assay. Ciprofloxacin resistance was identified by detecting a mutation in gyrA and parC. Results: The biofilm intensity significantly decreased (P < 0.05) concerning S. aureus isolates and insignificantly (P > 0.05) concernin

Abstract
             Shorten the research problem that there is no system or model to evaluate the financial performance of the departments of municipalities where it is not possible for a person or institution both to know or to know their success in terms of the financial work of failure and where it is now than those without assessing the financial performed, authorized to be and necessities FATF is the financial performance assessment, which is the work unfinished aspects without Hence the work came in this study to study and diagnose and analyze financial data in a sample of municipal departments in order to develop a model to assess the financ

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

This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.