Racial inequality has been a major issue throughout the history of the United States. In recent years, however, especially with the election of America's first black president, many have claimed that we have made progress and are moving towards a post-racial society. The authors of this study sought to test that claim by evaluating whether high school age students still experience a phenomenon known as white guilt. White guilt is defined as remorse or shame felt by people of Caucasian descent about racial inequality.

Modern artificial neural networks have been remarkably successful in various applications, from speech recognition to computer vision. However, it remains less clear whether they can implement abstract concepts, which are essential to generalization and understanding. To address this problem, the authors investigated the above vs. below task, a simple concept-based task that honeybees can solve, using a conventional neural network. They found that networks achieved 100% test accuracy when a visual target was presented below a black bar, however only 50% test accuracy when a visual target was presented below a reference shape.

The authors created a board game to teach young children about healthy eating habits to see whether an interactive and family-oriented method would be effective at introducing and maintaining a love for fruits and veggies. Results showed that children developed a liking for fruits and vegetables, and none regressed. Half maintained their level of enjoyment for fruits and vegetables during the research period, while the other half had a positive increase. The results show that a simple interactive game can shape how young children relate to food and encourage them to maintain healthy habits.

Plants, and all other multi-cellular organisms, develop through the coordinated action of many sets of genes. The authors here investigate the genes, in a class named KNOX, potentially responsible for organizing a certain part of Aquilegia (columbine) flowers called petal spurs. Through the technique Reverse Transcription-Polymerase Chain Reaction (RT-PCR), they find that certain KNOX genes are expressed non-uniformly in petal spurs, suggesting that they may be involved, perhaps in a cell-specific manner. This research will help guide future efforts toward understanding how many beautiful flowers develop their unique shapes.

This paper presents findings on Carcharhinus leucas (bull shark) and Carcharhinus amblyrhynchos (grey reef shark) aggression towards humans at Beqa Adventure Divers in Shark Reef Marine Reserve, Fiji. We hypothesized that grey reef sharks would receive more prods than bull sharks because grey reef sharks are typically more aggressive than bull sharks. The results supported our hypothesis, as an individual grey reef shark received 2.44 prods on average per feed, while a bull shark had an average of 0.61. These findings are meaningful not only to the world’s general understanding of shark aggression, but also to human protection against grey reef sharks as well as public education on bull sharks and the conservation of the species.

Parkinson’s disease (PD) is a prevalent neurodegenerative disorder in the U.S., second only to Alzheimer’s disease. Current diagnostic methods are often inefficient and dependent on clinical exams. This study explored using machine and deep learning to enhance PD diagnosis by analyzing spiral drawings affected by hand tremors, a common PD symptom.

The purpose of this study was to test devices installed on a gabled roof to see which reduced the actual uplift forces best. Three gabled birdhouse roofs were each modified with different mitigation devices: a rounded edge, a barrier shape, or an airfoil. The barrier edge had no significant effect on the time for the roof to blow off. The addition of airfoil devices on roofs, specifically in areas that are prone to hurricanes such as Florida, could keep roofs in place during hurricanes, thus reducing insurance bills, overall damage costs, and the loss of lives.

Collisions of heavy ions, such as muons result in jets and noise. In high-energy particle physics, researchers use jets as crucial event-shaped observable objects to determine the properties of a collision. However, many ionic collisions result in large amounts of energy lost as noise, thus reducing the efficiency of collisions with heavy ions. The purpose of our study is to analyze the relationships between properties of muons in a dimuon collision to optimize conditions of dimuon collisions and minimize the noise lost. We used principles of Newtonian mechanics at the particle level, allowing us to further analyze different models. We used simple Python algorithms as well as linear regression models with tools such as sci-kit Learn, NumPy, and Pandas to help analyze our results. We hypothesized that since the invariant mass, the energy, and the resultant momentum vector are correlated with noise, if we constrain these inputs optimally, there will be scenarios in which the noise of the heavy-ion collision is minimized.