Molecular docking based comparative study of antiviral compounds on SARS-CoV-2 spike protein.

The urgent need for effective therapeutic interventions against SARS-CoV-2 has prompted extensive exploration of potential drug candidates. Among the viral proteins, the spike (S) protein presents an attractive target due to its critical role in viral entry and infection. In this study, we employed molecular docking techniques to investigate the binding affinities and interaction profiles of a panel of active compounds against the SARS-CoV-2 spike protein.

Multifuse multilayer multikernel RVFLN+ of process modes decomposition and approximate entropy data from iEEG/sEEG signals for epileptic seizure recognition.

In this paper, the extracted features using variational mode decomposition (VMD) and approximate entropy (ApEn) privileged information of the input EEG signals are combined with multilayer multikernel random vector functional link network plus (MMRVFLN+) classifier to recognize the epileptic seizure epochs efficaciously. In our experiment Bonn University single-channel intracranial electroencephalogram (iEEG) and Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) multichannel scalp EEG (sEEG) recordings are considered to evaluate the efficacy of the proposed method. The VMD is applied on chaotic, non-stationary, nonlinear, and complex EEG signal to decompose it into three band-limited intrinsic mode functions (BLIMFs).

Controlled differential evolution based detection of neovascularization on optic disc using support vector machine.

The severe stage of Diabetic Retinopathy (DR) is characterized by the growth of new blood vessels which is called Neovascularization (NV). The abnormally grown blood vessels on the disc are breakable in nature thus the patient is at high risk of sudden blindness. Therefore, the significance of early and accurate detection of Neovascularization on Disc (NVD) should not be neglected.

Correlation-based ECG Artifact Correction from Single Channel EEG using Modified Variational Mode Decomposition.

Background And Objective: Ambulatory based healthcare system use limited electrodes for electroencephalogram (EEG) acquisition at concerned electrode position, to minimize the instrumentation and computational complexity. But, again the possibility of contamination is inevitable depending on the electrode position on the scalp. This paper proposes an electrocardiogram (ECG) artifact correction algorithm in the absence of coherent ECG for automatic analysis/diagnosis of the acquired contaminated single channel EEG signal.