Prevalence of Trismus in Head and Neck Cancer Patients in Kerala, South India.

Introduction: Trismus is a common complication of head and neck cancer (HNC) treatment. Understanding its prevalence and its risk factors is vital for enhancing clinical outcomes and the overall quality of life of these patients.

Objective: The study aimed to assess the prevalence and the factors associated with trismus among HNC patients.

Electroceuticals: Unlocking the promise of therapies.

Objectives: Electroceuticals refers to the constantly growing disciplines of bioelectric and bioelectronic medication. These include a broad variety of devices that have been invented and are now being utilized in medical implants, wearable medical electronics, and bioelectronics. The primary aim of this study is to encompass several facets of electroceuticals, their applications, and recent advancements in the field of medical challenges.

AgOTf-catalyzed cascade annulation of 5-hexyn-1-ols and aldehydes: enabling the diastereoselective synthesis of [6,6,6]-trioxa-fused ketals and hexahydro-2-chromenes.

We report the unprecedented diastereoselective synthesis of novel [6,6,6]-trioxa-fused ketals AgOTf-catalyzed cascade annulation of 5-hexyn-1-ols (with primary or secondary hydroxyl groups) and aldehydes through a [2+2+1+1] pathway. In contrast, 5-hexyn-1-ols with tertiary hydroxyl groups yield hexahydro-2-chromenes a [3+1+1+1] pathway.

Advanced battery management system enhancement using IoT and ML for predicting remaining useful life in Li-ion batteries.

This study highlights the increasing demand for battery-operated applications, particularly electric vehicles (EVs), necessitating the development of more efficient Battery Management Systems (BMS), particularly lithium-ion (Li-ion) batteries used in energy storage systems (ESS). This research addresses some of the key limitations of current BMS technologies, with a focus on accurately predicting the remaining useful life (RUL) of batteries, which is a critical factor for ensuring operational efficiency and sustainability. Real-time data are collected from sensors via an Internet of Things (IoT) device and processed using Arduino Nano, which extracts values for input into a Long Short-Term Memory (LSTM) model.