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Viruses are the most abundant living things and a source of genetic variation. Despite recent research, we know little about their biodiversity and geographic distribution. We used different bioinformatics tools, MG-RAST, genome detective web tools, and GenomeVx, to describe the first metagenomic examination of haloviruses in Wadi Al-Natrun. The discovered viromes had remarkably different taxonomic compositions. Most sequences were derived from double-stranded DNA viruses, especially from Myoviridae, Podoviridae, Siphoviridae, Herpesviridae, Bicaudaviridae, and Phycodnaviridae families; single-stranded DNA viruses, especially from the family Microviridae; and positive-strand RNA viruses, especially from the family Potyviridae. Additionally, our results showed that Myohalovirus chaoS9 has eight Contigs and is annotated to 18 proteins as follows: tail sheath protein, tco, nep, five uncharacterized proteins, HCO, major capsid protein, putative pro head protease protein, putative head assembly protein, CxxC motive protein, terl, HTH domain protein, and terS Exon 2. Additionally, Halorubrum phage CGphi46 has 19 proteins in the brine sample as follows: portal protein, 17 hypothetical proteins, major capsid protein, etc. This study reveals viral lineages, suggesting the Virus's global dispersal more than other microorganisms. Our study clarifies how viral communities are connected and how the global environment changes. [ABSTRACT FROM AUTHOR]

Real-time estimation of transmission line (TL) parameters is essential for proper management of transmission and distribution networks. These parameters can be used to detect incipient faults within the line and hence avoid any potential consequences. While some attempts can be found in the literature to estimate TL parameters, the presented techniques are either complex or impractical. Moreover, none of the presented techniques published in the literature so far can be implemented in real time. This paper presents a cost-effective technique to estimate TL parameters in real time. The proposed technique employs easily accessible voltage and current data measured at both ends of the line. For simplicity, only one quarter of the measured data is sampled and utilized in a developed objective function that is solved using the whale optimization algorithm (WOA) to estimate the TL parameters. The proposed objective function comprises the sum of square errors of the measured data and the corresponding estimated values. The robustness of the proposed technique is tested on a simple two-bus and the IEEE 14-bus systems. The impact of uncertainties in the measured data including magnitude, phase, and communication delay on the performance of the proposed estimation technique is also investigated. Results reveal the effectiveness of the proposed method that can be implemented in real time to detect any incipient variations in the TL parameters due to abnormal or fault events. [ABSTRACT FROM AUTHOR]