Browse Articles

In this article the authors explore the peculiar behavior of sinking bubbles. By investigating the relationship between the viscosity of a fluid and the the formation of stationary bubbles, they identify why bubbles behave differently between in different fluids.

This study investigated how fashion brand personalities are similar to people’s personalities and whether people may prefer a particular clothing brand based on their own personal traits. All together, Stevenson and Scott found that the Big Five Personality Factors are generally not related to participants’ preferred brand personalities. Generally, brands should consider different factors besides the Big Five Personality Factors for identifying potential customers.

Ant invasion causes damage exceeding $5 billion annually in North America. In this study, Ambati and Duvvuri aim to identify natural products with ant-repelling properties using a custom ring apparatus designed to quantify ant-repellence. They report that cinnamon and lemon were the most effective ant repellents of the tested products. These data suggest that compounds found in non-toxic household products, such as cinnamon oil and lemon juice, could be used in low-dose combinations as potent, effective, eco-friendly, and safe ant repellents.

The authors investigate the negative effects stress has on teen mental and physical health. Through a survey, they give Virginia teens a voice in revising the Health and Physical Education curriculum to include a standards of learning (SOL). Notably they identify factors contributing to stress levels including homework level, amount of free and sleep time, parental pressure and family encouragement.

This article investigates the study methodologies, learning strategies, and motives of spelling bee participants. The authors identify several important educational implications of this work.

This article investigates differences in gene expression in the brains of patients with and without Parkinson's disease. The authors identify a crucial transcriptional regulator may be a relevant target for future therapeutic treatment for Parkinson's disease.

Van der Woude syndrome is a common birth defect caused by mutations in the gene Irf6. In this project, students used microarray expression analysis from wild-type and Irf6-deficient mice in order to identify gene networks or pathways differentially regulated due to the Irf6 mutation. They found NF-κB pathway to be activated in deficient mice.

Have you ever wondered what contributes to the popping ability of popcorn? In this study, the authors use Quantitative Trait Locus (QTL) mapping to identify genes that may contribute to specific popping characteristics including kernel size and popping expansion volume (PEV).

Cancer is often caused by improper function of a few proteins, and sometimes it takes only a few proteins to malfunction to cause drastic changes in cells. Here the authors look at the genes that were mutated in patients with a type of pancreatic cancer to identify proteins that are important in causing cancer. They also determined which proteins currently lack effective treatment, and suggest that certain proteins (named KRAS, CDKN2A, and RBBP8) are the most important candidates for developing drugs to treat pancreatic cancer.

The mountain chain of the Western Ghats on the Indian peninsula, a UNESCO World Heritage site, is home to about 200 frog species, 89 of which are endemic. Distinctive to each frog species, their vocalizations can be used for species recognition. Manually surveying frogs at night during the rain in elephant and big cat forests is difficult, so being able to autonomously record ambient soundscapes and identify species is essential. An effective machine learning (ML) species classifier requires substantial training data from this area. The goal of this study was to assess data augmentation techniques on a dataset of frog vocalizations from this region, which has a minimal number of audio recordings per species. Consequently, enhancing an ML model’s performance with limited data is necessary. We analyzed the effects of four data augmentation techniques (Time Shifting, Noise Injection, Spectral Augmentation, and Test-Time Augmentation) individually and their combined effect on the frog vocalization data and the public environmental sounds dataset (ESC-50). The effect of combined data augmentation techniques improved the model's relative accuracy as the size of the dataset decreased. The combination of all four techniques improved the ML model’s classification accuracy on the frog calls dataset by 94%. This study established a data augmentation approach to maximize the classification accuracy with sparse data of frog call recordings, thereby creating a possibility to build a real-world automated field frog species identifier system. Such a system can significantly help in the conservation of frog species in this vital biodiversity hotspot.