AQUILA: A laboratory facility for the irradiation of astrochemical ice analogs by keV ions.

The detection of various molecular species, including complex organic molecules relevant to biochemical and geochemical processes, in astronomical settings, such as the interstellar medium or the outer solar system, has led to the increased need for a better understanding of the chemistry occurring in these cold regions of space. In this context, the chemistry of ices prepared and processed at cryogenic temperatures has proven to be of particular interest due to the fact that many interstellar molecules are believed to originate within the icy mantles adsorbed on nano- and micro-scale dust particles. The chemistry leading to the formation of such molecules may be initiated by ionizing radiation in the form of galactic cosmic rays or stellar winds, and thus, there has been an increased interest in commissioning experimental setups capable of simulating and better characterizing this solid-phase radiation astrochemistry.

Ethnobotanical study of wild edible plants in Arsi Robe district of East Arsi Zone, Ethiopia.

Background: Wild edible plants (WEPs) are usually considered to constitute all plant resources that are neither cultivated nor domesticated but are used as nutritional supplements by local people. WEPs play a vital role in ensuring food and livelihood security for countless families and communities around the world. The objective of the study was to assess and document wild edible plants used by communities in the Arsi Robe district as food.

Accuracy of a Non-Invasive Home Glucose Monitor for Measurement of Blood Glucose.

Introduction: Patients with diabetes mellitus monitor their blood glucose at home with monitors that require a drop of blood or use a continuous glucose monitoring device that implants a small needle in the body. However, both cause discomfort to the patients which may inhibit them for regular blood glucose checks. Photoplethysmogram (PPG) sensing technology is an approach for non-invasive blood glucose measurement and PPG sensors can be used to predict hypoglycaemic episodes.

Assessing the Utilization of Large Language Models in Medical Education: Insights From Undergraduate Medical Students.

Background Artificial intelligence (AI) has the potential to be integrated into medical education. Among AI-based technology, large language models (LLMs) such as ChatGPT, Google Bard, Microsoft Bing, and Perplexity have emerged as powerful tools with capabilities in natural language processing. With this background, this study investigates the knowledge, attitude, and practice of undergraduate medical students regarding the utilization of LLMs in medical education in a medical college in Jharkhand, India.