Evaluation of machine learning and deep learning models for daily air quality index prediction in Delhi city, India.

The air quality index (AQI), based on criteria for air contaminants, is defined to provide a shared vision of air quality. As air pollution continues to rise in global cities due to urbanization and climate change, air pollution monitoring and forecasting models for effective air quality monitoring that gather and forecast information about air pollution concentration are essential in every city. Air quality predictions have evolved to be more helpful for management.

A systematic search, heuristic evaluation and analysis of dental trauma mobile applications.

Background: Despite the exponential growth of mobile device applications in promoting awareness on traumatic dental injuries (TDIs), the overall validity of existing applications in content, engagement, usability, functionality, esthetics, and user perception remains largely uncertain.

Aims: The primary aim was to systematically search and assess the quality, functionality, perceived impact and usability of available applications related to TDIs using the User Version of the Mobile Application Rating Scale (uMARS) and the Coventry, Aberdeen, and London-Revised (CA-LO-RE) scale. A heuristic evaluation was additionally performed.

Numerical Methodology to Evaluate Trackability and Pushability of PTCA Balloon Catheter.

Purpose: During percutaneous coronary intervention (PCI), the ability to navigate a catheter without causing injury to the vessel and damage to the device is crucial outcome of the procedure. This study aimed to develop a numerical model to analyse the percutaneous transluminal coronary angioplasty (PTCA) catheter navigation in coronary vessels.

Methods: Trackability and pushability are two major parameters used to characterize the navigation of PTCA balloon catheters, and they are influenced by vessel tortuosity, contact interactions and catheter design.