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- PublicationHeart Rate Variability Analysis Reveals a Non-monotonic Relationship between Humanin Concentration and Cardiac Autonomic Regulation(2022)Oxidative stress (OS) has been shown to have a negative effect on the autonomic nervous system (ANS) and on ANS modulation of heart rate. Mitochondrial ATP production is the main source of reactive oxygen species (ROS) and hence the regulation of ROS becomes an important issue in maintaining optimal ANS functionality. Humanin (HN), a mitochondrial-derived peptide, plays an important role in lowering OS. Sympathovagal balance was assessed in 124 healthy participants through heart rate variability (HRV) analysis and compared across changes in HN concentrations divided into quintiles, with values of HN ranging from 64.6 to 343.2 pg/mL. Significant differences included various frequency domain and nonlinear HRV parameters, particularly between first and fourth HN quintiles with p values < 0.001 for recurrence plot analysis (RPA), detrended fluctuation analysis (DFA) a1 and Poincaré plot ratio SD1/SD2. The results revealed non-monotonic relationships between measures of HRV and HN concentration. A mitohormetic type of relationship was observed with HRV features increasing and then decreasing with increasing HN concentration. These results are consistent with previous findings of the importance of HN levels in regulating OS and extend these by revealing a concomitant effect on the modulation of cardiac rhythm by the ANS.
- PublicationA Review of the Genetic Algorithm and JAYA Algorithm Applications(2022)This study throws the light on two metaheuristic algorithms and enable researchers to leverage the potential of adapting them in whatever applications they may have either in engineering, computer science, or business. The two algorithms are the GA and the JAYA. The JAYA algorithm is a modern population-based meta heuristic algorithm, its applications are presented in this work. The JA Y A algorithm integrates evolutionary algorithms' survival of the fittest concept with the productivity and richness of heuristic search methodologies. On the other a well-known and somewhat older evolutionary based method called the Genetic Algorithm with applications is also presented here. The recent two algorithms; the JA Y A and the GA have broad comparable applications in computer science and engineering applications.
- PublicationFace Sketch Synthesis using Generative Adversarial Networks(2022)Face Sketch Synthesis is crucial for a wide range of practical applications, including digital entertainment and law enforcement. Recent approaches based on Generative Adversarial Networks (GANs) have shown compelling results in image-to-image translation as well as face photo-sketch synthesis. However, these methods still have considerable limitations as some noise appears in synthesized sketches which leads to poor perceptual quality and poor preserving fidelity. To tackle this issue, in this paper, we propose a Face Sketch Synthesis technique using conditional GAN to generate facial sketches from facial photographs named cGAN-FSS. Our cGAN-FSS framework generates high perceptual quality of face sketch synthesis while maintaining high identity recognition accuracy. Image Quality Assessment metrics and Face Recognition experiments confirm our proposed framework's performs better than the state-of-the-art methods.
- PublicationEvaluation of Pre-Trained CNN Models for Geographic Fake Image Detection(2022)Thanks to the remarkable advances in generative adversarial networks (GANs), it is becoming increasingly easy to generate/manipulate images. The existing works have mainly focused on deepfake in face images and videos. However, we are currently witnessing the emergence of fake satellite images, which can be misleading or even threatening to national security. Consequently, there is an urgent need to develop detection methods capable of distinguishing between real and fake satellite images. To advance the field, in this paper, we explore the suitability of several convolutional neural network (CNN) architectures for fake satellite image detection. Specifically, we benchmark four CNN models by conducting extensive experiments to evaluate their performance and robustness against various image distortions. This work allows the establishment of new baselines and may be useful for the development of CNN-based methods for fake satellite image detection.
- PublicationAssessing the Use of Oil and Gas Produced Water for Soil Aquifer Treatment in Abu Dhabi(2022)The United Arab Emirates originally lack for sufficient natural water resources. A major source of water in the UAE is groundwater, which includes water in surface wells that are normally renewed by seasonal rains, and deep wells which are refilled via ancient geological formations. The deficit in water availability due to the increasing demand and shortage in water resources availability can be met by utilizing non-conventional sources such as desalinated water, and recycling wastewater. This paper aims to present a scientific assessment of the possibility of using treated oil and gas-produced water for recharging the underground aquifer in Abu Dhabi through Soil aquifer treatment (SAT). Core samples from the unsaturated zone layers of sand, sandstone, siltstone, and conglomerates layers from the Abu Dhabi area were collected and characterized. Adsorption experiments have been carried out to investigate the capacity of the soil samples for the removal of hazardous contaminants i.e. heavy metals and dissolved organic from synthesized oil-produced water samples. The obtained data were used to calculate the required time for the hazardous contaminants to reach the underground water.