Browse Articles

People with Type One diabetes often rely on Continuous Blood Glucose Monitors (CGMs) to track their blood glucose and manage their condition. Researchers are now working to help people with Type One diabetes more easily monitor their health by developing models that will future blood glucose levels based on CGM readings. Jalla and Ghanta tackle this issue by exploring the use of AI models to forecast blood glucose levels with CGM data.

Here, the authors investigated the ability to use fruit peels to help soil retain moisture, a property that is essential to agriculture. Across a 96-hour observation period, orange, banana, and kiwi peel water emulsions were evaluated for their effects on soil moisture. They found that orange peels retained the most moisture, but banana and kiwi peels also offered improvements over their control sample.

The authors look at how different food types impact the ability of bacteria to produce electricity.

In this study the authors look at the use of Indole 3 Carbinol as a treatment for Type II Diabetes finding that it may be an effective treatment.

In this study, the authors test whether providing a larger dataset of glass transition temperatures (T_g) to train the machine-learning platform Polymer Genome would improve its accuracy. Polymer Genome is a machine learning based data-driven informatics platform for polymer property prediction and T_g is one property needed to design new polymers in silico. They found that training the model with their larger, curated dataset improved the algorithm's T_g, providing valuable improvements to this useful platform.

The authors looked at how vocabulary is impacted in Alzheimer's disease and whether it could be used a predictor of disease onset.

The authors use blood smears from individuals with sickle cell disease to correlate sickle cell frequency with the occurrence of vaso-occlusive crises.

The study explored converting Gracilaria seaweed waste—known for releasing toxic hydrogen sulfide when decomposed—into biochar as a sustainable solution for waste management and soil improvement.

The authors train a neural network to detect text-based emotions including joy, sadness, anger, fear, love, and surprise.

Here, seeking to better understand how facial features provide important visual cues to help convey emotions, the authors evaluated the accuracy and reaction time of participants in regards to experimental photographs where a person's eyebrows were obscured and ones where they were not. Their findings revealed that removing eyebrows resulted in a significant decrease in a participant's ability to recognize anger, with adolescents most likely to misidentify emotions.