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Sweet potatoes are one of the most common starches in Taiwan, and sweet potato peels hold significant potential to make biodegradable plastics which can alleviate the environmental impact of conventional petroleum-based plastics. In this paper, Tsai et al created starch-based bioplastics derived from sweet potato peels and manipulated the amount of added glycerol to alter the plastic’s strength and flexibility properties. Their results indicated that higher concentrations of glycerol yield more malleable plastics, providing insights into how recycled agricultural waste material might be used to slow down the rate of pollution caused by widespread production of conventional plastics.

In this study the author undertakes a careful characterization of a special type of chemical reaction, called an oscillating Belousov-Zhabotinsky (or B-Z) reaction, which has a number of existing applications in biomedical engineering as well as the potential to be useful in future developments in other fields of science and engineering. Specifically, she uses experimental measurements in combination with computational analysis to investigate whether the reaction is cohesive – that is, whether the oscillations between chemical states will remain consistent or change over time as the reaction progresses. Her results indicate that the reaction is not cohesive, providing an important foundation for the development of future technologies using B-Z reactions.

In recent years, usage of interactive electronic devices such as computers, smartphones, and tablets has increased dramatically. Many studies have examined the potential adverse effects of excessive usage of such devices on children and adolescents, but the effects on adults are not well understood. In this study, the authors examined the relationship between adult usage of interactive electronic devices and a variety of clinical measures of psychological well-being. They found that according to some metrics, higher usage of interactive electronic devices is associated with several adverse psychological outcomes, suggesting a need for more careful consideration of such usage patterns in clinical settings.

The authors test the ability of aloe vera gel to purify water of four separate contaminants. Aloe reduced the levels of copper, iron, and phosphate, but not nitrate. Potential applications of this purification system are discussed.

This study investigates how the hyperparameters epochs and batch size affect the classification accuracy of a convolutional neural network (CNN) trained on pulsar candidate data. Our results reveal that accuracy improves with increasing number of epochs and smaller batch sizes, suggesting that with optimized hyperparameters, high accuracy may be achievable with minimal training. These findings offer insights that could help create more efficient machine learning classification models for pulsar signal detection, with the potential of accelerating pulsar discovery and advancing astrophysical research.

Crohn’s disease is a chronic inflammatory bowel condition with symptoms like abdominal pain, fatigue, diarrhea, and malnutrition. Though there's no cure, various treatments help manage it. This study explored the potential impact of Massa Medicata Fermentata (MMF), a fermented Chinese herbal medicine containing Saccharomyces cerevisiae, on Crohn’s disease.

Here the authors explored the development of biodegradable bioplastic films derived from mango peels as a sustainable solution to plastic pollution and greenhouse gas emissions from fruit waste. They optimized the film's mechanical properties and water resistance through adjusting processing conditions and incorporating plasticizers and a hydrophobic coating, ultimately demonstrating its potential as a bacteriostatic and biodegradable alternative to conventional plastic food wrap.

Here, the authors used machine learning to analyze microscopic images of hair, quantifying various features to distinguish individuals, even within families where traditional DNA analysis is limited. The Discriminant Analysis (DA) model achieved the highest accuracy (88.89%) in identifying individuals, demonstrating its potential to improve the reliability of hair evidence in forensic investigations.

Pediatric cancers pose unique challenges due to their rarity and distinct biological factors, emphasizing the need for accurate survival prediction to guide treatment. This study integrated generative AI and machine learning, including synthetic data, to analyze 9,184 pediatric cancer patients, identifying age at diagnosis, cancer types, and anatomical sites as significant survival predictors. The findings highlight the potential of AI-driven approaches to improve survival prediction and inform personalized treatment strategies, with broader implications for innovative healthcare applications.

Coronary artery disease, the leading cause of death worldwide, results from cholesterol build-up in coronary arteries, limiting blood and oxygen flow to the heart. This study investigated the use of gold and silver nanoparticles coated with aspirin and activated by near-infrared light to improve blood flow in a clogged artery model. The nanoparticles increased simulated blood flow rates, demonstrating potential as a less invasive and more targeted treatment for cardiovascular disease.