Enhancement of the photocatalytic activity of rGO/NiO/Ag nanocomposite for degradation of methylene blue dye.

The current study focuses on boosting the photocatalytic ability of reduced graphene oxide (rGO) by decorating the rGO nano-sheets with nickel oxide (NiO) and silver (Ag) nanomaterials. The developed ternary nanomaterials were investigated using FTIR, XRD, FESEM, TEM, Raman, and UV-vis to evaluate the photo-degradation process. The rGO/NiO/Ag ternary system showed promising photocatalytic dye degradation under simulated sunlight irradiance.

Sunlight driven photocatalytic degradation of organic pollutants using a MnVO/BiVO heterojunction: mechanistic perception and degradation pathways.

In the field of photocatalysis, fabrication of a heterojunction structure with effective charge separation at the interface and charge shift to enhance the photocatalytic activity has acquired extensive consideration. In the present investigation, MnVO/BiVO heterojunction samples with excellent photocatalytic performance under sunlight irradiation were conveniently synthesized by a hydrothermal technique, and characterized by UV-Vis, FTIR, XRD, FESEM, HRTEM, PL, BET and XPS techniques. The prepared samples were investigated as photocatalysts for degrading MB and RhB dyes under sunlight.

Software system to predict the infection in COVID-19 patients using deep learning and web of things.

Since the end of 2019, computed tomography (CT) images have been used as an important substitute for the time-consuming Reverse Transcriptase polymerase chain reaction (RT-PCR) test; a new coronavirus 2019 (COVID-19) disease has been detected and has quickly spread through many countries across the world. Medical imaging such as computed tomography provides great potential due to growing skepticism toward the sensitivity of RT-PCR as a screening tool. For this purpose, automated image segmentation is highly desired for a clinical decision aid and disease monitoring.

COVID-19 pandemic and transmission factors: An empirical investigation of different countries.

The present work evaluates the impact of age, population density, total population, rural population, annual average temperature, basic sanitation facilities, and diabetes prevalence on the transmission of COVID-19. This research is an effort to identify the major predictors that have a significant impact on the number of COVID-19 cases per million population for 83 countries. The findings highlight that a population with a greater share of old people (aged above 65) shows a higher number of COVID-19 positive cases and a population with a lower median age has fewer cases.