CoFeO/PANI/MWCNTs ternary hybrid composites. Synthesis, characterization, the effect of MWCNTs ratio and dye removal capability.

We have synthesized cobalt ferrite (CoFeO) using the sucrose auto-combustion method and subsequently employed the in situ polymerization technique to fabricate ternary composites comprising CoFeO, polyaniline (PANI), and multi-walled carbon nanotubes (MWCNTs). In this novel investigation, we explored the influence of varying MWCNTs ratios on these composites' structural, magnetic, thermal, and electrical properties. The crystal structures of the synthesized composites were analyzed using X-ray diffraction (XRD), while Fourier transform infrared (FT-IR) spectroscopy revealed changes in bonding patterns, including the disappearance of ferrite bonds and the emergence of new ones.

Epidemiology, clinical characteristics and risk factors of COVID-19 among children in Saudi Arabia: a multicenter chart review study.

Background: The Coronavirus Disease 2019 (COVID-19) has affected over 100 million cases worldwide. Children accounted for 1-5% of all cases with less reported symptoms and better prognosis compared to adults. This study aimed to describe the epidemiological characteristics and outcomes of pediatric COVID-19 cases in Saudi Arabia in addition to identifying risk factors associated with disease severity.

The COVID-19 Infection Diffusion in the US and Japan: A Graph-Theoretical Approach.

Coronavirus disease 2019 (COVID-19) was first discovered in China; within several months, it spread worldwide and became a pandemic. Although the virus has spread throughout the globe, its effects have differed. The pandemic diffusion network dynamics (PDND) approach was proposed to better understand the spreading behavior of COVID-19 in the US and Japan.

Neural Decoding of EEG Signals with Machine Learning: A Systematic Review.

Electroencephalography (EEG) is a non-invasive technique used to record the brain's evoked and induced electrical activity from the scalp. Artificial intelligence, particularly machine learning (ML) and deep learning (DL) algorithms, are increasingly being applied to EEG data for pattern analysis, group membership classification, and brain-computer interface purposes. This study aimed to systematically review recent advances in ML and DL supervised models for decoding and classifying EEG signals.

The Chaotic Behavior of the Spread of Infection During the COVID-19 Pandemic in the United States and Globally.

In December 2019, China announced the breakout of a new virus identified as coronavirus SARS-CoV-2 (COVID-19), which soon grew exponentially and resulted in a global pandemic. Despite strict actions to mitigate the spread of the virus in various countries, COVID-19 resulted in a significant loss of human life in 2020 and early 2021. To better understand the dynamics of the spread of COVID-19, evidence of its chaotic behavior in the US and globally was evaluated.