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In this paper, we explore the property of being a cordial graphic and establish that it corresponds to an Alexandroff topological space. We analyze how the characteristics of cordial graphs align with the principles of Alexandroff topology and provide insights into their topological structure.

Abstract Type-II transmembrane serine proteases are effective pharmacological targets for host defence against viral entry and in certain cancer cell progressions. These serine proteases cleave viral spike proteins to expose the fusion peptide for cell entry, which is essential to the life cycle of the virus. TMPRSS2 inhibitors can also fight against respiratory viruses that employ them for cell entry. Our study combining virtual screening, all-atom molecular dynamics, and well-tempered metadynamics simulation identifies vicenin-2, neohesperidin, naringin, and rhoifolin as promising TMPRSS2 antagonists. The binding energies obtained are − 16.3, − 15.4, − 13.6, and − 13.8 kcal/mol for vicenin-2, neohesperidin, naringin, and rhoifolin respectively. The RMSD, RMSF, PCA, DCCM, and binding free energy profiles also correlate with the stable binding of these ligands at the active site of TMPRSS2. The study reveals that these molecules could be promising lead molecules for combating future outbreaks of coronavirus and other respiratory viruses.

In this article, a new class of sets namely neutrosophic resolvable sets in neutrosophic topological space have been introduced. We present the neutrosophic resolvable functions between neutrosophic topological spaces by neutrosophic resolvables sets. Also we examine the characteristics of neutrosophic resolvable sets and neutrosophic resolvable functions with the existing sets.

The focus of this article is to introduce a new class of sets namely neutrosophic semi j-open and neutrosophic semi j-closed sets in neutrosophic topological space. Using this, we present the new spaces neutrosophic hyperconnected and neutrosophic semi j-hyperconnected. Also we explore the characteristics of neutrosophic semi j-open sets, neutrosophic semi j-closed set, neutrosophic hyperconnectedness. Finally we examine the properties of neutrosophic semi j-hyperconnectedness with some existing sets.

In this article, we implement a new notion of sets namely neutrosophic nano j-closed set, neutrosophic nano generalized closed set, neutrosophic nano generalized j-closed set and neutrosophic nano generalized j*-closed set in neutrosophic nano topological spaces. We also provide some appropriate examples to study the properties of these sets. The existing relations between some of these sets in neutrosophic nano topological space have been investigated.

Speckle is modeled as a signal dependent noise, which tends to reduce the image resolution and contrast, thereby reducing the diagnostic values of the ultrasound imaging modality. Reduction of speckle noise is one of the most important processes to increase the quality of biomedical images. Filters are used to improve the quality of ultrasound images by removing the noise. This paper compares the performance of the thresholding technique Bayes Shrink in despeckling the medical ultrasound images with other classical speckle reduction filters like Lee, Frost, Median, Kaun, Wavelet Bayes, Anisotropic diffusion and Wavelet. The performance of these filters is analyzed by the statistical measures such as Peak Signal-to Noise Ratio, Mean Square Error and Equivalent Number of Looks. To produce a better quality resolution picture, the filter should have high Peak Signal to Noise Ratio, low Mean Square Error, high Equivalent Number of Looks. The results obtained are presented in the form of filtered images, statistical tables and graphs. Finally, the best filter has been recommended based on the statistical and experimental results. From the results obtained Lee and Frost filter outperforms the other mentioned filters in terms of high PSNR and low MSE for high variance of noise where as anisotropic diffusion filter outperforms with high PSNR and low MSE with maximum ENL for low variance values of noise.